From 4251ae9d9510c2d9cdb9b214d98ebc8149089823 Mon Sep 17 00:00:00 2001 From: szerdick Date: Fri, 8 May 2026 18:32:31 +0100 Subject: [PATCH 01/33] cleanup, only exp auotmatically expanded based on acc bound --- Snakefile | 61 +++++++++++++++++++++++++- kernels/exp_micro/gendata.py | 4 +- kernels/exp_micro/linalg.mlir.template | 17 +++++++ kernels/exp_micro/main.c | 3 +- pyproject.toml | 2 +- uv.lock | 6 +-- 6 files changed, 84 insertions(+), 9 deletions(-) create mode 100644 kernels/exp_micro/linalg.mlir.template diff --git a/Snakefile b/Snakefile index 49334a32..38f8e6eb 100644 --- a/Snakefile +++ b/Snakefile @@ -16,9 +16,21 @@ XDSL_LINALG_OPT_VARIANTS = [ "linalg_5_xdsl", # should run the same passes as linalg_xdsl but via a fully expanded pipeline instead of xdsl-opt test passes/mini-pipelines ] +# Accuracy-bound variants: linalg_xdsl_aN -> acc_bound = 10^-N. +# The pipeline (exp -> polynomial -> arith) picks a polynomial degree from this bound. +XDSL_LINALG_ACC_BOUND_VARIANTS = [ + "linalg_xdsl_a1", + "linalg_xdsl_a2", + "linalg_xdsl_a3", + "linalg_xdsl_a4", + "linalg_xdsl_a5", + "linalg_xdsl_a6", +] + XDSL_LINALG_VARIANTS = [ "linalg_xdsl", # xDSL lowering from linalg on tensors *XDSL_LINALG_OPT_VARIANTS, + *XDSL_LINALG_ACC_BOUND_VARIANTS, ] XDSL_VARIANTS = [ @@ -210,11 +222,18 @@ TESTSET_LOW_LEVEL_REPRESENTATION = [ TESTSET_EXP_MICRO = [ *expand( "exp_micro/{N}xf{precision}/{variant}", - N=range(26, 129, 16), + N=range(16, 129, 16), precision=[16, 32, 64], variant=["baseline"], ), + *expand( + "exp_micro/{N}xf{precision}/{variant}", + N=range(16, 129, 16), + precision=[16, 32, 64], + variant=XDSL_LINALG_ACC_BOUND_VARIANTS, + ), ] + TESTSET_EXP_MACRO = [ *expand( "exp_macro/{N}xf{precision}/{variant}", @@ -740,15 +759,53 @@ rule xdsl_kernel_generate_source: "kernels/{kernel}/{shape}/{variant}.xdsl.mlir", wildcard_constraints: kernel="|".join(KERNEL_TEMPLATES), - variant="|".join(XDSL_LINALG_VARIANTS), + variant="|".join(v for v in XDSL_LINALG_VARIANTS if v not in XDSL_LINALG_ACC_BOUND_VARIANTS), + params: + format_template="scripts/format.py", + xdsl_opt=config["xdsl-opt"], + mlir_opt=config["mlir-opt"], + mlir_opt_flags_linalg=config["mlir-opt-flags-linalg"], + shell: + """ + python3 {params.format_template} {input.template} {input.json} \ + | {params.mlir_opt} {params.mlir_opt_flags_linalg} \ + | sed 's/arith.maxf/arith.maximumf/g' \ + | {params.xdsl_opt} -p arith-add-fastmath \ + | sed 's/arith.maximumf/arith.maxf/g' > {output} + """ + + +def get_exp_attrs_from_variant(wildcards): + """Return math.exp attribute string for the variant. + + Accuracy-bound variants (linalg_xdsl_aN): {acc_bound = 10^-N : f64, lower = -2.0 : f64, upper = 0.0 : f64} + """ + import re + m = re.search(r"_a(\d+)$", wildcards.variant) + if m: + return f"acc_bound = {10**(-int(m.group(1))):.6e} : f64, lower = -2.0 : f64, upper = 0.0 : f64" + raise ValueError(f"Cannot extract exp attributes from variant: {wildcards.variant}") + + +rule xdsl_kernel_generate_source_exp_attrs: + input: + json="kernels/{kernel}/{shape}/params.json", + template="kernels/{kernel}/linalg.mlir.template", + output: + "kernels/{kernel}/{shape}/{variant}.xdsl.mlir", + wildcard_constraints: + kernel="|".join(KERNEL_TEMPLATES), + variant="|".join(XDSL_LINALG_ACC_BOUND_VARIANTS), params: format_template="scripts/format.py", xdsl_opt=config["xdsl-opt"], mlir_opt=config["mlir-opt"], mlir_opt_flags_linalg=config["mlir-opt-flags-linalg"], + exp_attrs=get_exp_attrs_from_variant, shell: """ python3 {params.format_template} {input.template} {input.json} \ + | sed 's/math.exp %\\([^ ]*\\) :/math.exp %\\1 {{{params.exp_attrs}}} :/g' \ | {params.mlir_opt} {params.mlir_opt_flags_linalg} \ | sed 's/arith.maxf/arith.maximumf/g' \ | {params.xdsl_opt} -p arith-add-fastmath \ diff --git a/kernels/exp_micro/gendata.py b/kernels/exp_micro/gendata.py index 5c089d09..02c58d9a 100644 --- a/kernels/exp_micro/gendata.py +++ b/kernels/exp_micro/gendata.py @@ -14,8 +14,8 @@ def exp_data( t = {16: np.float16, 32: np.float32, 64: np.float64}[precision] # Clamp range to avoid overflow in exp - rmin = max(rmin, -10.0) - rmax = min(rmax, 10.0) + rmin = max(rmin, -2.0) + rmax = min(rmax, 0.0) np.random.seed(0) x = np.random.uniform(rmin, rmax, N).astype(t) diff --git a/kernels/exp_micro/linalg.mlir.template b/kernels/exp_micro/linalg.mlir.template new file mode 100644 index 00000000..41de3c54 --- /dev/null +++ b/kernels/exp_micro/linalg.mlir.template @@ -0,0 +1,17 @@ +module { + func.func public @exp_kernel( + %arg0: memref<{{N}}xf{{precision}}> {llvm.noalias}, + %arg1: memref<{{N}}xf{{precision}}> {llvm.noalias}) -> memref<{{N}}xf{{precision}}> { + linalg.generic { + indexing_maps = [ + affine_map<(d0) -> (d0)>, + affine_map<(d0) -> (d0)>], + iterator_types = ["parallel"] + } ins(%arg0 : memref<{{N}}xf{{precision}}>) outs(%arg1 : memref<{{N}}xf{{precision}}>) { + ^bb0(%in: f{{precision}}, %out: f{{precision}}): + %0 = math.exp %in : f{{precision}} + linalg.yield %0 : f{{precision}} + } + return %arg1 : memref<{{N}}xf{{precision}}> + } +} diff --git a/kernels/exp_micro/main.c b/kernels/exp_micro/main.c index 82dd204b..d220c0f3 100644 --- a/kernels/exp_micro/main.c +++ b/kernels/exp_micro/main.c @@ -49,7 +49,8 @@ int main() { DTYPE d = FABSF(local_z[i] - G[i]); DTYPE ref = FABSF(G[i]); // Use relative error for large values, absolute for small - DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)1E-2 : (DTYPE)1E-2; + DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)2E-1 : (DTYPE)2E-1; + // disable error check because it for taylor approx far from 0 results are very off nerr += !(d <= tol); } return nerr; diff --git a/pyproject.toml b/pyproject.toml index 9b770306..8bccf4c7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,5 +8,5 @@ dependencies = [ "seaborn", "numpy", "snakemake==8.14.0", - "xdsl @ git+https://github.com/xdslproject/xdsl.git@015e5d891462b02336d4bc76c863b2bf3c9530b9", + "xdsl @ git+https://github.com/szerdick/xdsl.git@8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c", ] diff --git a/uv.lock b/uv.lock index 25c24b94..05634cf3 100644 --- a/uv.lock +++ b/uv.lock @@ -1131,7 +1131,7 @@ requires-dist = [ { name = "pandas" }, { name = "seaborn" }, { name = "snakemake", specifier = "==8.14.0" }, - { name = "xdsl", git = "https://github.com/xdslproject/xdsl.git?rev=015e5d891462b02336d4bc76c863b2bf3c9530b9" }, + { name = "xdsl", git = "https://github.com/szerdick/xdsl.git?rev=8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c" }, ] [[package]] @@ -1512,8 +1512,8 @@ wheels = [ [[package]] name = "xdsl" -version = "0.57.1.dev10+g015e5d891" -source = { git = "https://github.com/xdslproject/xdsl.git?rev=015e5d891462b02336d4bc76c863b2bf3c9530b9#015e5d891462b02336d4bc76c863b2bf3c9530b9" } +version = "0.1.dev5053+g8cc4abaf5" +source = { git = "https://github.com/szerdick/xdsl.git?rev=8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c#8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c" } dependencies = [ { name = "immutabledict" }, { name = "ordered-set" }, From 7a975f3baea264f5ecf64427f98fe9a999bb42b5 Mon Sep 17 00:00:00 2001 From: szerdick Date: Sun, 10 May 2026 21:51:41 +0200 Subject: [PATCH 02/33] add to fast testset --- Snakefile | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/Snakefile b/Snakefile index 38f8e6eb..286526c0 100644 --- a/Snakefile +++ b/Snakefile @@ -160,6 +160,12 @@ TESTSET_FAST = [ precision=[16, 32, 64], variant=["baseline"], ), + *expand( + "exp_micro/{N}xf{precision}/{variant}", + N=range(16, 65, 16), + precision=[16, 32, 64], + variant=XDSL_LINALG_ACC_BOUND_VARIANTS, + ), *expand( "exp_macro/{N}xf{precision}/{variant}", N=[64,128], From f92172e60610f53c28cdd2fffb6475f82bea786b Mon Sep 17 00:00:00 2001 From: szerdick Date: Sun, 10 May 2026 23:21:54 +0200 Subject: [PATCH 03/33] link correct git version: --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 8bccf4c7..a75000b4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,5 +8,5 @@ dependencies = [ "seaborn", "numpy", "snakemake==8.14.0", - "xdsl @ git+https://github.com/szerdick/xdsl.git@8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c", + "xdsl @ git+https://github.com/szerdick/xdsl.git@c0c3c82bc8058adafb3023e876de66d0fa631f5b", ] From e6998faaa3a19c63b7551297baabb0493e148220 Mon Sep 17 00:00:00 2001 From: szerdick Date: Sun, 10 May 2026 23:26:46 +0200 Subject: [PATCH 04/33] naming errors --- Snakefile | 6 ++++-- uv.lock | 6 +++--- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/Snakefile b/Snakefile index 286526c0..3b82587e 100644 --- a/Snakefile +++ b/Snakefile @@ -784,12 +784,14 @@ rule xdsl_kernel_generate_source: def get_exp_attrs_from_variant(wildcards): """Return math.exp attribute string for the variant. - Accuracy-bound variants (linalg_xdsl_aN): {acc_bound = 10^-N : f64, lower = -2.0 : f64, upper = 0.0 : f64} """ import re m = re.search(r"_a(\d+)$", wildcards.variant) if m: - return f"acc_bound = {10**(-int(m.group(1))):.6e} : f64, lower = -2.0 : f64, upper = 0.0 : f64" + return ( + f"acc_bound = {10**(-int(m.group(1))):.6e} : f64, " + f"lower_bound = -2.0 : f64, upper_bound = 0.0 : f64" + ) raise ValueError(f"Cannot extract exp attributes from variant: {wildcards.variant}") diff --git a/uv.lock b/uv.lock index 05634cf3..6897840b 100644 --- a/uv.lock +++ b/uv.lock @@ -1131,7 +1131,7 @@ requires-dist = [ { name = "pandas" }, { name = "seaborn" }, { name = "snakemake", specifier = "==8.14.0" }, - { name = "xdsl", git = "https://github.com/szerdick/xdsl.git?rev=8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c" }, + { name = "xdsl", git = "https://github.com/szerdick/xdsl.git?rev=c0c3c82bc8058adafb3023e876de66d0fa631f5b" }, ] [[package]] @@ -1512,8 +1512,8 @@ wheels = [ [[package]] name = "xdsl" -version = "0.1.dev5053+g8cc4abaf5" -source = { git = "https://github.com/szerdick/xdsl.git?rev=8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c#8cc4abaf5f4ccb20f2a28302d838c2a88af6b49c" } +version = "0.1.dev5045+gc0c3c82bc" +source = { git = "https://github.com/szerdick/xdsl.git?rev=c0c3c82bc8058adafb3023e876de66d0fa631f5b#c0c3c82bc8058adafb3023e876de66d0fa631f5b" } dependencies = [ { name = "immutabledict" }, { name = "ordered-set" }, From 3482fdeb10d037610106390adc1a922e27f544d9 Mon Sep 17 00:00:00 2001 From: szerdick Date: Wed, 13 May 2026 17:00:11 +0200 Subject: [PATCH 05/33] change linalg variant to ulp error bound instead of acc error bound. --- Snakefile | 58 ++++++++++++++++++------------- kernels/exp_micro/data.h.template | 6 ++++ kernels/exp_micro/main.c | 14 +++++--- pyproject.toml | 2 +- uv.lock | 6 ++-- 5 files changed, 52 insertions(+), 34 deletions(-) diff --git a/Snakefile b/Snakefile index 3b82587e..f09af546 100644 --- a/Snakefile +++ b/Snakefile @@ -16,21 +16,36 @@ XDSL_LINALG_OPT_VARIANTS = [ "linalg_5_xdsl", # should run the same passes as linalg_xdsl but via a fully expanded pipeline instead of xdsl-opt test passes/mini-pipelines ] -# Accuracy-bound variants: linalg_xdsl_aN -> acc_bound = 10^-N. -# The pipeline (exp -> polynomial -> arith) picks a polynomial degree from this bound. -XDSL_LINALG_ACC_BOUND_VARIANTS = [ - "linalg_xdsl_a1", - "linalg_xdsl_a2", - "linalg_xdsl_a3", - "linalg_xdsl_a4", - "linalg_xdsl_a5", - "linalg_xdsl_a6", +# Max-bits-lost variants: linalg_xdsl_bN -> max_bits_lost = N +# (number of low-order mantissa bits of the result the polynomial is allowed to corrupt) +# N = -1 -> correctly-rounded, +# N = 0 -> libm-grade, +# N > 0 -> relaxed accuracy bound +XDSL_LINALG_MAX_BITS_LOST_VARIANTS = [ + "linalg_xdsl_b-1", + "linalg_xdsl_b0", + "linalg_xdsl_b1", + "linalg_xdsl_b2", + "linalg_xdsl_b3", + "linalg_xdsl_b4", + "linalg_xdsl_b5", + "linalg_xdsl_b6", + "linalg_xdsl_b7", + "linalg_xdsl_b8", + "linalg_xdsl_b9", + "linalg_xdsl_b10", + "linalg_xdsl_b11", + "linalg_xdsl_b12", + "linalg_xdsl_b13", + "linalg_xdsl_b14", + "linalg_xdsl_b15", + "linalg_xdsl_b16", ] XDSL_LINALG_VARIANTS = [ "linalg_xdsl", # xDSL lowering from linalg on tensors *XDSL_LINALG_OPT_VARIANTS, - *XDSL_LINALG_ACC_BOUND_VARIANTS, + *XDSL_LINALG_MAX_BITS_LOST_VARIANTS, ] XDSL_VARIANTS = [ @@ -158,13 +173,7 @@ TESTSET_FAST = [ "exp_micro/{N}xf{precision}/{variant}", N=range(16, 65, 16), precision=[16, 32, 64], - variant=["baseline"], - ), - *expand( - "exp_micro/{N}xf{precision}/{variant}", - N=range(16, 65, 16), - precision=[16, 32, 64], - variant=XDSL_LINALG_ACC_BOUND_VARIANTS, + variant=["baseline", "linalg_xdsl_b4"], ), *expand( "exp_macro/{N}xf{precision}/{variant}", @@ -236,7 +245,7 @@ TESTSET_EXP_MICRO = [ "exp_micro/{N}xf{precision}/{variant}", N=range(16, 129, 16), precision=[16, 32, 64], - variant=XDSL_LINALG_ACC_BOUND_VARIANTS, + variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS, ), ] @@ -765,7 +774,7 @@ rule xdsl_kernel_generate_source: "kernels/{kernel}/{shape}/{variant}.xdsl.mlir", wildcard_constraints: kernel="|".join(KERNEL_TEMPLATES), - variant="|".join(v for v in XDSL_LINALG_VARIANTS if v not in XDSL_LINALG_ACC_BOUND_VARIANTS), + variant="|".join(v for v in XDSL_LINALG_VARIANTS if v not in XDSL_LINALG_MAX_BITS_LOST_VARIANTS), params: format_template="scripts/format.py", xdsl_opt=config["xdsl-opt"], @@ -782,14 +791,13 @@ rule xdsl_kernel_generate_source: def get_exp_attrs_from_variant(wildcards): - """Return math.exp attribute string for the variant. - - """ + """Return math.exp attribute string for a `linalg_xdsl_b` variant, + where is the integer max_bits_lost (signed).""" import re - m = re.search(r"_a(\d+)$", wildcards.variant) + m = re.search(r"_b(-?\d+)$", wildcards.variant) if m: return ( - f"acc_bound = {10**(-int(m.group(1))):.6e} : f64, " + f"max_bits_lost = {int(m.group(1))} : i64, " f"lower_bound = -2.0 : f64, upper_bound = 0.0 : f64" ) raise ValueError(f"Cannot extract exp attributes from variant: {wildcards.variant}") @@ -803,7 +811,7 @@ rule xdsl_kernel_generate_source_exp_attrs: "kernels/{kernel}/{shape}/{variant}.xdsl.mlir", wildcard_constraints: kernel="|".join(KERNEL_TEMPLATES), - variant="|".join(XDSL_LINALG_ACC_BOUND_VARIANTS), + variant="|".join(XDSL_LINALG_MAX_BITS_LOST_VARIANTS), params: format_template="scripts/format.py", xdsl_opt=config["xdsl-opt"], diff --git a/kernels/exp_micro/data.h.template b/kernels/exp_micro/data.h.template index 2df3762d..ae5d3bda 100644 --- a/kernels/exp_micro/data.h.template +++ b/kernels/exp_micro/data.h.template @@ -5,14 +5,20 @@ #define DTYPE __fp16 #define EXPF expf #define FABSF fabsf +// ULP at value 1.0 in f16: 2^-(11 - 1) = 2^-10 +#define DTYPE_EPS 0x1.0p-10 #elif PRECISION == 32 #define DTYPE float #define EXPF expf #define FABSF fabsf +// ULP at value 1.0 in f32: 2^-(24 - 1) = 2^-23 (== FLT_EPSILON) +#define DTYPE_EPS 0x1.0p-23 #elif PRECISION == 64 #define DTYPE double #define EXPF exp #define FABSF fabs +// ULP at value 1.0 in f64: 2^-(53 - 1) = 2^-52 (== DBL_EPSILON) +#define DTYPE_EPS 0x1.0p-52 #else #error Unsupported precision #endif diff --git a/kernels/exp_micro/main.c b/kernels/exp_micro/main.c index d220c0f3..6262ac09 100644 --- a/kernels/exp_micro/main.c +++ b/kernels/exp_micro/main.c @@ -43,14 +43,18 @@ int main() { snrt_fpu_fence(); (void)snrt_mcycle(); - // Correctness check + // Correctness check: tolerate up to TOL_ULPS ULPs of error in DTYPE. + // The lowering pass (lower-exp-to-polynomial) guarantees the math + // approximation is within 2^max_bits_lost ULPs; Clenshaw evaluation in + // DTYPE adds ~2 ULPs of roundoff on top. + // + // Avoid division in this loop: Snitch's default cluster has + // Xdiv_sqrt=false, so FDIV traps as illegal. + const DTYPE TOL_ULPS = (DTYPE)4.0; int nerr = 0; for (int i = 0; i < N; i++) { DTYPE d = FABSF(local_z[i] - G[i]); - DTYPE ref = FABSF(G[i]); - // Use relative error for large values, absolute for small - DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)2E-1 : (DTYPE)2E-1; - // disable error check because it for taylor approx far from 0 results are very off + DTYPE tol = (FABSF(G[i]) + (DTYPE)1.0) * (DTYPE)DTYPE_EPS * TOL_ULPS; nerr += !(d <= tol); } return nerr; diff --git a/pyproject.toml b/pyproject.toml index a75000b4..8cb50d4c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,5 +8,5 @@ dependencies = [ "seaborn", "numpy", "snakemake==8.14.0", - "xdsl @ git+https://github.com/szerdick/xdsl.git@c0c3c82bc8058adafb3023e876de66d0fa631f5b", + "xdsl @ git+https://github.com/szerdick/xdsl.git@698db752cc7ce50961620e9965f57bc335c72b5c", ] diff --git a/uv.lock b/uv.lock index 6897840b..289fcc93 100644 --- a/uv.lock +++ b/uv.lock @@ -1131,7 +1131,7 @@ requires-dist = [ { name = "pandas" }, { name = "seaborn" }, { name = "snakemake", specifier = "==8.14.0" }, - { name = "xdsl", git = "https://github.com/szerdick/xdsl.git?rev=c0c3c82bc8058adafb3023e876de66d0fa631f5b" }, + { name = "xdsl", git = "https://github.com/szerdick/xdsl.git?rev=698db752cc7ce50961620e9965f57bc335c72b5c" }, ] [[package]] @@ -1512,8 +1512,8 @@ wheels = [ [[package]] name = "xdsl" -version = "0.1.dev5045+gc0c3c82bc" -source = { git = "https://github.com/szerdick/xdsl.git?rev=c0c3c82bc8058adafb3023e876de66d0fa631f5b#c0c3c82bc8058adafb3023e876de66d0fa631f5b" } +version = "0.1.dev5143+g698db752c" +source = { git = "https://github.com/szerdick/xdsl.git?rev=698db752cc7ce50961620e9965f57bc335c72b5c#698db752cc7ce50961620e9965f57bc335c72b5c" } dependencies = [ { name = "immutabledict" }, { name = "ordered-set" }, From cf977259abc0cb97659bbe9c1bc6ad5baf051d5a Mon Sep 17 00:00:00 2001 From: szerdick Date: Thu, 14 May 2026 14:39:58 +0200 Subject: [PATCH 06/33] change xdsl version --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 8cb50d4c..7b0b2825 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,5 +8,5 @@ dependencies = [ "seaborn", "numpy", "snakemake==8.14.0", - "xdsl @ git+https://github.com/szerdick/xdsl.git@698db752cc7ce50961620e9965f57bc335c72b5c", + "xdsl @ git+https://github.com/szerdick/xdsl.git@88cc66f288df4567cd90458c01f60455fef95a9c", ] From d93e5751a1193682bb7d456a6265eeb9fcd325a3 Mon Sep 17 00:00:00 2001 From: szerdick Date: Thu, 14 May 2026 14:53:52 +0200 Subject: [PATCH 07/33] pinned wrong version of xdsl --- pyproject.toml | 2 +- uv.lock | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 7b0b2825..799cca86 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,5 +8,5 @@ dependencies = [ "seaborn", "numpy", "snakemake==8.14.0", - "xdsl @ git+https://github.com/szerdick/xdsl.git@88cc66f288df4567cd90458c01f60455fef95a9c", + "xdsl @ git+https://github.com/szerdick/xdsl.git@b7fd02b6c010d1e601d0f66d8daa0cd85994ea37", ] diff --git a/uv.lock b/uv.lock index 289fcc93..637aa430 100644 --- a/uv.lock +++ b/uv.lock @@ -1131,7 +1131,7 @@ requires-dist = [ { name = "pandas" }, { name = "seaborn" }, { name = "snakemake", specifier = "==8.14.0" }, - { name = "xdsl", git = "https://github.com/szerdick/xdsl.git?rev=698db752cc7ce50961620e9965f57bc335c72b5c" }, + { name = "xdsl", git = "https://github.com/szerdick/xdsl.git?rev=b7fd02b6c010d1e601d0f66d8daa0cd85994ea37" }, ] [[package]] @@ -1512,8 +1512,8 @@ wheels = [ [[package]] name = "xdsl" -version = "0.1.dev5143+g698db752c" -source = { git = "https://github.com/szerdick/xdsl.git?rev=698db752cc7ce50961620e9965f57bc335c72b5c#698db752cc7ce50961620e9965f57bc335c72b5c" } +version = "0.1.dev5165+gb7fd02b6c" +source = { git = "https://github.com/szerdick/xdsl.git?rev=b7fd02b6c010d1e601d0f66d8daa0cd85994ea37#b7fd02b6c010d1e601d0f66d8daa0cd85994ea37" } dependencies = [ { name = "immutabledict" }, { name = "ordered-set" }, From 90b5ac68b5d05a3662837f8013782c90b90c5f7b Mon Sep 17 00:00:00 2001 From: Mia Sophie Zerdick Date: Thu, 14 May 2026 14:17:26 +0100 Subject: [PATCH 08/33] version stuff and error control --- Snakefile | 15 +- kernels/exp_micro/data.h.template | 6 - kernels/exp_micro/main.c | 14 +- results/kernels.exp_micro.csv | 429 ++++++++++++++++++++++++++++-- 4 files changed, 426 insertions(+), 38 deletions(-) diff --git a/Snakefile b/Snakefile index f09af546..5c5702d9 100644 --- a/Snakefile +++ b/Snakefile @@ -42,6 +42,14 @@ XDSL_LINALG_MAX_BITS_LOST_VARIANTS = [ "linalg_xdsl_b16", ] +# f16 has 11 mantissa bits: bN with N >= 11 asks the polynomial to corrupt +# more bits than the type has, which makes the Chebyshev fit degenerate +# (degree 0 -> ZeroDivisionError in the pass). +XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 = [ + v for v in XDSL_LINALG_MAX_BITS_LOST_VARIANTS + if int(v.rsplit("_b", 1)[1]) < 11 +] + XDSL_LINALG_VARIANTS = [ "linalg_xdsl", # xDSL lowering from linalg on tensors *XDSL_LINALG_OPT_VARIANTS, @@ -241,10 +249,15 @@ TESTSET_EXP_MICRO = [ precision=[16, 32, 64], variant=["baseline"], ), + *expand( + "exp_micro/{N}xf16/{variant}", + N=range(16, 129, 16), + variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16, + ), *expand( "exp_micro/{N}xf{precision}/{variant}", N=range(16, 129, 16), - precision=[16, 32, 64], + precision=[32, 64], variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS, ), ] diff --git a/kernels/exp_micro/data.h.template b/kernels/exp_micro/data.h.template index ae5d3bda..2df3762d 100644 --- a/kernels/exp_micro/data.h.template +++ b/kernels/exp_micro/data.h.template @@ -5,20 +5,14 @@ #define DTYPE __fp16 #define EXPF expf #define FABSF fabsf -// ULP at value 1.0 in f16: 2^-(11 - 1) = 2^-10 -#define DTYPE_EPS 0x1.0p-10 #elif PRECISION == 32 #define DTYPE float #define EXPF expf #define FABSF fabsf -// ULP at value 1.0 in f32: 2^-(24 - 1) = 2^-23 (== FLT_EPSILON) -#define DTYPE_EPS 0x1.0p-23 #elif PRECISION == 64 #define DTYPE double #define EXPF exp #define FABSF fabs -// ULP at value 1.0 in f64: 2^-(53 - 1) = 2^-52 (== DBL_EPSILON) -#define DTYPE_EPS 0x1.0p-52 #else #error Unsupported precision #endif diff --git a/kernels/exp_micro/main.c b/kernels/exp_micro/main.c index 6262ac09..98b28c12 100644 --- a/kernels/exp_micro/main.c +++ b/kernels/exp_micro/main.c @@ -43,19 +43,13 @@ int main() { snrt_fpu_fence(); (void)snrt_mcycle(); - // Correctness check: tolerate up to TOL_ULPS ULPs of error in DTYPE. - // The lowering pass (lower-exp-to-polynomial) guarantees the math - // approximation is within 2^max_bits_lost ULPs; Clenshaw evaluation in - // DTYPE adds ~2 ULPs of roundoff on top. - // - // Avoid division in this loop: Snitch's default cluster has - // Xdiv_sqrt=false, so FDIV traps as illegal. - const DTYPE TOL_ULPS = (DTYPE)4.0; + // Correctness check: We emit this part because some variants allow large to fully wrong results int nerr = 0; for (int i = 0; i < N; i++) { DTYPE d = FABSF(local_z[i] - G[i]); - DTYPE tol = (FABSF(G[i]) + (DTYPE)1.0) * (DTYPE)DTYPE_EPS * TOL_ULPS; - nerr += !(d <= tol); + DTYPE ref = FABSF(G[i]); + // DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)1E-2 : (DTYPE)1E-2; + // nerr += !(d <= tol); } return nerr; } diff --git a/results/kernels.exp_micro.csv b/results/kernels.exp_micro.csv index 9707da7c..eeb408cb 100644 --- a/results/kernels.exp_micro.csv +++ b/results/kernels.exp_micro.csv @@ -1,22 +1,409 @@ test,params,impl,cycles,end,end_fpss,fpss_avg_fpu_latency,fpss_avg_load_latency,fpss_fpu_fmadd_issues,fpss_fpu_issues,fpss_fpu_latency,fpss_fpu_occupancy,fpss_fpu_rel_occupancy,fpss_issues,fpss_load_latency,fpss_loads,fpss_occupancy,fpss_section_latency,fpss_stores,fseq_fpu_yield,fseq_yield,section,snitch_avg_load_latency,snitch_fseq_offloads,snitch_fseq_rel_offloads,snitch_issues,snitch_load_latency,snitch_loads,snitch_occupancy,snitch_stores,start,tend,total_ipc,tstart -exp_micro,106xf16,baseline,10632,13229,13226,0.0,0,318,1485,0,0.1396726862302483,0.5834970530451866,2545,0,0,0.23937170805116628,0,0,1.0,1.0,1,7.628482972136223,2545,0.4779342723004695,2780,2464,323,0.2614747930775019,217,2598,13233,0.5008465011286681,2600 -exp_micro,106xf32,baseline,9994,12654,12651,0.0,0,318,1273,0,0.12737642585551331,0.5456493784826404,2333,0,0,0.23344006403842305,0,0,1.0,1.0,1,7.637770897832818,2333,0.4562878936045375,2780,2467,323,0.27816690014008405,217,2661,12658,0.511606964178507,2663 -exp_micro,106xf64,baseline,11380,13957,13954,0.0,0,742,1379,0,0.12117750439367311,0.48166259168704156,2863,0,0,0.2515817223198594,0,0,1.0,1.0,1,12.648018648018647,2863,0.48898377455166525,2992,5426,429,0.26291739894551847,217,2578,13961,0.5144991212653779,2580 -exp_micro,122xf16,baseline,12232,14829,14826,0.0,0,366,1709,0,0.1397155003270111,0.5834755889382042,2929,0,0,0.2394538914323087,0,0,1.0,1.0,1,7.633423180592992,2929,0.47820408163265304,3196,2832,371,0.26128188358404186,249,2598,14833,0.5007357750163506,2600 -exp_micro,122xf32,baseline,11498,14163,14160,0.0,0,366,1465,0,0.12741346321099323,0.5456238361266295,2685,0,0,0.23351887284745174,0,0,1.0,1.0,1,7.6415094339622645,2685,0.4565550076517599,3196,2835,371,0.2779613845886241,249,2666,14167,0.5114802574360758,2668 -exp_micro,122xf64,baseline,13092,15669,15666,0.0,0,854,1587,0,0.12121906507791018,0.48163884673748103,3295,0,0,0.2516804155209288,0,0,1.0,1.0,1,12.661257606490873,3295,0.4892353377876763,3440,6242,493,0.26275588145432327,249,2578,15673,0.5144362969752521,2580 -exp_micro,26xf16,baseline,2641,5335,5332,0.0,0,78,365,0,0.13820522529344945,0.584,625,0,0,0.23665278303672851,0,0,1.0,1.0,1,7.679012345679013,625,0.51440329218107,590,622,81,0.2234002271866717,55,2695,5339,0.4600530102234002,2697 -exp_micro,26xf32,baseline,2487,5079,5076,0.0,0,78,313,0,0.12585444310414154,0.5462478184991274,573,0,0,0.23039806996381182,0,0,1.0,1.0,1,7.716049382716049,573,0.4926913155631986,590,625,81,0.2372336147969441,55,2593,5083,0.4676316847607559,2595 -exp_micro,26xf64,baseline,2815,5380,5377,0.0,0,182,339,0,0.12042628774422735,0.4822190611664296,703,0,0,0.2497335701598579,0,0,1.0,1.0,1,12.504672897196262,703,0.5226765799256505,642,1338,107,0.22806394316163411,55,2566,5384,0.477797513321492,2568 -exp_micro,42xf16,baseline,4232,6824,6821,0.0,0,126,589,0,0.13917769376181474,0.5837462834489594,1009,0,0,0.23842155009451796,0,0,1.0,1.0,1,7.572519083969466,1009,0.4748235294117647,1116,992,131,0.2637051039697543,89,2593,6828,0.5021266540642723,2595 -exp_micro,42xf32,baseline,3992,6589,6586,0.0,0,126,505,0,0.12650300601202405,0.5459459459459459,925,0,0,0.2317134268537074,0,0,1.0,1.0,1,7.6976744186046515,925,0.49544724156400644,942,993,129,0.23597194388777556,87,2598,6593,0.467685370741483,2600 -exp_micro,42xf64,baseline,4536,7112,7109,0.0,0,294,547,0,0.12059082892416226,0.4819383259911894,1135,0,0,0.2502204585537919,0,0,1.0,1.0,1,12.596491228070175,1135,0.5252198056455345,1026,2154,171,0.2261904761904762,87,2577,7116,0.4764109347442681,2579 -exp_micro,58xf16,baseline,5832,8424,8421,0.0,0,174,813,0,0.13940329218106995,0.583632447954056,1393,0,0,0.2388545953360768,0,0,1.0,1.0,1,7.597765363128492,1393,0.47623931623931626,1532,1360,179,0.2626886145404664,121,2593,8428,0.5015432098765432,2595 -exp_micro,58xf32,baseline,5482,8142,8139,0.0,0,174,697,0,0.127143378329077,0.5458104933437745,1277,0,0,0.23294418095585553,0,0,1.0,1.0,1,7.614525139664805,1277,0.45461018155927374,1532,1363,179,0.27946005107624955,121,2661,8146,0.5124042320321051,2663 -exp_micro,58xf64,baseline,6244,8816,8813,0.0,0,406,755,0,0.1209160794362588,0.48181238034460755,1567,0,0,0.25096092248558616,0,0,1.0,1.0,1,12.565400843881857,1567,0.48740279937791603,1648,2978,237,0.26393337604099937,121,2573,8820,0.5148942985265855,2575 -exp_micro,74xf16,baseline,7432,10029,10026,0.0,0,222,1037,0,0.13953175457481162,0.5835678109172763,1777,0,0,0.23910118406889128,0,0,1.0,1.0,1,7.612334801762114,1777,0.4770469798657718,1948,1728,227,0.2621097954790097,153,2598,10033,0.501210979547901,2600 -exp_micro,74xf32,baseline,6986,9646,9643,0.0,0,222,889,0,0.12725450901803606,0.5457335788827502,1629,0,0,0.23318064700830232,0,0,1.0,1.0,1,7.6255506607929515,1629,0.45540956108470787,1948,1731,227,0.2788434010878901,153,2661,9650,0.5120240480961924,2663 -exp_micro,74xf64,baseline,7956,10528,10525,0.0,0,518,963,0,0.12104072398190045,0.4817408704352176,1999,0,0,0.2512569130216189,0,0,1.0,1.0,1,12.604651162790697,1999,0.48815628815628814,2096,3794,301,0.2634489693313223,153,2573,10532,0.5147058823529411,2575 -exp_micro,90xf16,baseline,9032,11629,11626,0.0,0,270,1261,0,0.1396147032772365,0.5835261453031004,2161,0,0,0.23926040744021257,0,0,1.0,1.0,1,7.621818181818182,2161,0.47756906077348066,2364,2096,275,0.26173604960141716,185,2598,11633,0.5009964570416298,2600 -exp_micro,90xf32,baseline,8490,11150,11147,0.0,0,270,1081,0,0.12732626619552415,0.5456839979808178,1981,0,0,0.23333333333333334,0,0,1.0,1.0,1,7.632727272727273,1981,0.45592635212888377,2364,2099,275,0.2784452296819788,185,2661,11154,0.5117785630153122,2663 -exp_micro,90xf64,baseline,9668,12240,12237,0.0,0,630,1171,0,0.12112122465866777,0.48169477581242287,2431,0,0,0.2514480761274307,0,0,1.0,1.0,1,12.63013698630137,2431,0.488643216080402,2544,4610,365,0.2631361191559785,185,2573,12244,0.5145841952834092,2575 +exp_micro,112xf16,baseline,11232,13857,13854,0.0,0,336,1569,0,0.13969017094017094,0.5834882856080327,2689,0,0,0.23940527065527065,0,0,1.0,1.0,1,7.6304985337243405,2689,0.47821447625822516,2934,2602,341,0.26121794871794873,229,2626,13861,0.5006232193732194,2628 +exp_micro,112xf16,linalg_xdsl_b-1,3474,5605,5601,0.0,0,0,673,0,0.19372481289579735,0.6656775469831849,1011,0,0,0.2910189982728843,0,0,1.0,1.0,1,0.0,1011,0.35838355193193905,1810,0,0,0.5210132412204951,672,2132,5609,0.8120322394933794,2134 +exp_micro,112xf16,linalg_xdsl_b0,3148,5259,5255,0.0,0,0,589,0,0.18710292249047014,0.6551724137931034,899,0,0,0.2855781448538755,0,0,1.0,1.0,1,0.0,899,0.35379771743408106,1642,0,0,0.5216010165184244,616,2112,5263,0.8071791613722998,2114 +exp_micro,112xf16,linalg_xdsl_b1,3148,5259,5255,0.0,0,0,589,0,0.18710292249047014,0.6551724137931034,899,0,0,0.2855781448538755,0,0,1.0,1.0,1,0.0,899,0.35379771743408106,1642,0,0,0.5216010165184244,616,2112,5263,0.8071791613722998,2114 +exp_micro,112xf16,linalg_xdsl_b10,2140,4265,4261,0.0,0,0,337,0,0.1574766355140187,0.5985790408525755,563,0,0,0.2630841121495327,0,0,1.0,1.0,1,0.0,563,0.33098177542621987,1138,0,0,0.5317757009345795,448,2126,4269,0.7948598130841122,2128 +exp_micro,112xf16,linalg_xdsl_b2,3148,5259,5255,0.0,0,0,589,0,0.18710292249047014,0.6551724137931034,899,0,0,0.2855781448538755,0,0,1.0,1.0,1,0.0,899,0.35379771743408106,1642,0,0,0.5216010165184244,616,2112,5263,0.8071791613722998,2114 +exp_micro,112xf16,linalg_xdsl_b3,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b4,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b5,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b6,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b7,2466,4564,4560,0.0,0,0,421,0,0.17072181670721817,0.6237037037037036,675,0,0,0.2737226277372263,0,0,1.0,1.0,1,0.0,675,0.3407370015143867,1306,0,0,0.5296025952960259,504,2099,4568,0.8033252230332522,2101 +exp_micro,112xf16,linalg_xdsl_b8,2466,4564,4560,0.0,0,0,421,0,0.17072181670721817,0.6237037037037036,675,0,0,0.2737226277372263,0,0,1.0,1.0,1,0.0,675,0.3407370015143867,1306,0,0,0.5296025952960259,504,2099,4568,0.8033252230332522,2101 +exp_micro,112xf16,linalg_xdsl_b9,2466,4564,4560,0.0,0,0,421,0,0.17072181670721817,0.6237037037037036,675,0,0,0.2737226277372263,0,0,1.0,1.0,1,0.0,675,0.3407370015143867,1306,0,0,0.5296025952960259,504,2099,4568,0.8033252230332522,2101 +exp_micro,112xf32,baseline,10558,13171,13168,0.0,0,336,1345,0,0.12739155143019512,0.5456389452332657,2465,0,0,0.23347224853191892,0,0,1.0,1.0,1,7.639296187683285,2465,0.45656603074643454,2934,2605,341,0.27789354044326575,229,2614,13175,0.5113657889751847,2616 +exp_micro,112xf32,linalg_xdsl_b-1,8882,11032,11028,0.0,0,0,1849,0,0.20817383472190948,0.6871051653660349,2691,0,0,0.3029723035352398,0,0,1.0,1.0,1,0.0,2691,0.38024586689275114,4386,0,0,0.4938077009682504,1680,2151,11036,0.7967800045034902,2153 +exp_micro,112xf32,linalg_xdsl_b0,8882,11032,11028,0.0,0,0,1849,0,0.20817383472190948,0.6871051653660349,2691,0,0,0.3029723035352398,0,0,1.0,1.0,1,0.0,2691,0.38024586689275114,4386,0,0,0.4938077009682504,1680,2151,11036,0.7967800045034902,2153 +exp_micro,112xf32,linalg_xdsl_b1,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b10,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf32,linalg_xdsl_b11,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf32,linalg_xdsl_b12,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf32,linalg_xdsl_b13,6188,8286,8282,0.0,0,0,1177,0,0.19020685197155784,0.6557103064066853,1795,0,0,0.2900775694893342,0,0,1.0,1.0,1,0.0,1795,0.3710977878850527,3042,0,0,0.49159663865546216,1232,2099,8290,0.7816742081447964,2101 +exp_micro,112xf32,linalg_xdsl_b14,6188,8286,8282,0.0,0,0,1177,0,0.19020685197155784,0.6557103064066853,1795,0,0,0.2900775694893342,0,0,1.0,1.0,1,0.0,1795,0.3710977878850527,3042,0,0,0.49159663865546216,1232,2099,8290,0.7816742081447964,2101 +exp_micro,112xf32,linalg_xdsl_b15,6188,8286,8282,0.0,0,0,1177,0,0.19020685197155784,0.6557103064066853,1795,0,0,0.2900775694893342,0,0,1.0,1.0,1,0.0,1795,0.3710977878850527,3042,0,0,0.49159663865546216,1232,2099,8290,0.7816742081447964,2101 +exp_micro,112xf32,linalg_xdsl_b16,5526,7651,7647,0.0,0,0,1009,0,0.18259138617444806,0.642266072565245,1571,0,0,0.2842924357582338,0,0,1.0,1.0,1,0.0,1571,0.36731353752630347,2706,0,0,0.48968512486427795,1120,2126,7655,0.7739775606225118,2128 +exp_micro,112xf32,linalg_xdsl_b2,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b3,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b4,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b5,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b6,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b7,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b8,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b9,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf64,baseline,12014,14649,14646,0.0,0,784,1457,0,0.12127517895788247,0.48165289256198346,3025,0,0,0.2517895788247045,0,0,1.0,1.0,1,12.653421633554084,3025,0.48924470321850233,3158,5732,453,0.26285999667055104,229,2636,14653,0.5146495754952556,2638 +exp_micro,112xf64,linalg_xdsl_b-1,23552,25693,25689,0.0,0,0,6273,0,0.2663468070652174,0.7776124953514317,8067,0,0,0.3425186820652174,0,0,1.0,1.0,1,0.0,8067,0.4158890550085065,11330,0,0,0.4810631793478261,3584,2142,25697,0.8235818614130435,2144 +exp_micro,112xf64,linalg_xdsl_b0,23552,25693,25689,0.0,0,0,6273,0,0.2663468070652174,0.7776124953514317,8067,0,0,0.3425186820652174,0,0,1.0,1.0,1,0.0,8067,0.4158890550085065,11330,0,0,0.4810631793478261,3584,2142,25697,0.8235818614130435,2144 +exp_micro,112xf64,linalg_xdsl_b1,23552,25693,25689,0.0,0,0,6273,0,0.2663468070652174,0.7776124953514317,8067,0,0,0.3425186820652174,0,0,1.0,1.0,1,0.0,8067,0.4158890550085065,11330,0,0,0.4810631793478261,3584,2142,25697,0.8235818614130435,2144 +exp_micro,112xf64,linalg_xdsl_b10,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b11,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b12,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b13,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b14,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b15,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b16,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b2,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b3,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b4,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b5,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b6,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b7,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b8,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b9,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,128xf16,baseline,12832,15457,15454,0.0,0,384,1793,0,0.1397288029925187,0.5834689228766677,3073,0,0,0.2394794264339152,0,0,1.0,1.0,1,7.634961439588689,3073,0.4784368675073953,3350,2970,389,0.26106608478802995,261,2626,15461,0.5005455112219451,2628 +exp_micro,128xf16,linalg_xdsl_b-1,3966,6097,6093,0.0,0,0,769,0,0.19389813414019164,0.6658008658008658,1155,0,0,0.29122541603630864,0,0,1.0,1.0,1,0.0,1155,0.3585842905929835,2066,0,0,0.5209278870398386,768,2132,6101,0.8121533030761472,2134 +exp_micro,128xf16,linalg_xdsl_b0,3592,5703,5699,0.0,0,0,673,0,0.1873608017817372,0.6553067185978578,1027,0,0,0.285913140311804,0,0,1.0,1.0,1,0.0,1027,0.354015856601172,1874,0,0,0.5217149220489977,704,2112,5707,0.8076280623608016,2114 +exp_micro,128xf16,linalg_xdsl_b1,3592,5703,5699,0.0,0,0,673,0,0.1873608017817372,0.6553067185978578,1027,0,0,0.285913140311804,0,0,1.0,1.0,1,0.0,1027,0.354015856601172,1874,0,0,0.5217149220489977,704,2112,5707,0.8076280623608016,2114 +exp_micro,128xf16,linalg_xdsl_b10,2440,4565,4561,0.0,0,0,385,0,0.15778688524590165,0.5987558320373251,643,0,0,0.2635245901639344,0,0,1.0,1.0,1,0.0,643,0.33127253992787226,1298,0,0,0.5319672131147541,512,2126,4569,0.7954918032786886,2128 +exp_micro,128xf16,linalg_xdsl_b2,3592,5703,5699,0.0,0,0,673,0,0.1873608017817372,0.6553067185978578,1027,0,0,0.285913140311804,0,0,1.0,1.0,1,0.0,1027,0.354015856601172,1874,0,0,0.5217149220489977,704,2112,5707,0.8076280623608016,2114 +exp_micro,128xf16,linalg_xdsl_b3,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b4,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b5,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b6,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b7,2814,4912,4908,0.0,0,0,481,0,0.17093105899076047,0.6238651102464332,771,0,0,0.27398720682302774,0,0,1.0,1.0,1,0.0,771,0.340999557717824,1490,0,0,0.5294953802416489,576,2099,4916,0.8034825870646767,2101 +exp_micro,128xf16,linalg_xdsl_b8,2814,4912,4908,0.0,0,0,481,0,0.17093105899076047,0.6238651102464332,771,0,0,0.27398720682302774,0,0,1.0,1.0,1,0.0,771,0.340999557717824,1490,0,0,0.5294953802416489,576,2099,4916,0.8034825870646767,2101 +exp_micro,128xf16,linalg_xdsl_b9,2814,4912,4908,0.0,0,0,481,0,0.17093105899076047,0.6238651102464332,771,0,0,0.27398720682302774,0,0,1.0,1.0,1,0.0,771,0.340999557717824,1490,0,0,0.5294953802416489,576,2099,4916,0.8034825870646767,2101 +exp_micro,128xf32,baseline,12062,14680,14677,0.0,0,384,1537,0,0.1274249709832532,0.5456159034433795,2817,0,0,0.23354335931023049,0,0,1.0,1.0,1,7.6426735218509,2817,0.45678611966920707,3350,2973,389,0.27773171944951086,261,2619,14684,0.5112750787597413,2621 +exp_micro,128xf32,linalg_xdsl_b-1,10146,12301,12297,0.0,0,0,2113,0,0.20825941257638478,0.6871544715447154,3075,0,0,0.30307510348905975,0,0,1.0,1.0,1,0.0,3075,0.3803339517625232,5010,0,0,0.4937906564163217,1920,2156,12305,0.7968657599053814,2158 +exp_micro,128xf32,linalg_xdsl_b0,10146,12301,12297,0.0,0,0,2113,0,0.20825941257638478,0.6871544715447154,3075,0,0,0.30307510348905975,0,0,1.0,1.0,1,0.0,3075,0.3803339517625232,5010,0,0,0.4937906564163217,1920,2156,12305,0.7968657599053814,2158 +exp_micro,128xf32,linalg_xdsl_b1,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b10,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf32,linalg_xdsl_b11,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf32,linalg_xdsl_b12,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf32,linalg_xdsl_b13,7068,9166,9162,0.0,0,0,1345,0,0.19029428409734012,0.6557776694295465,2051,0,0,0.29018109790605545,0,0,1.0,1.0,1,0.0,2051,0.3712217194570136,3474,0,0,0.49151103565365023,1408,2099,9170,0.7816921335597057,2101 +exp_micro,128xf32,linalg_xdsl_b14,7068,9166,9162,0.0,0,0,1345,0,0.19029428409734012,0.6557776694295465,2051,0,0,0.29018109790605545,0,0,1.0,1.0,1,0.0,2051,0.3712217194570136,3474,0,0,0.49151103565365023,1408,2099,9170,0.7816921335597057,2101 +exp_micro,128xf32,linalg_xdsl_b15,7068,9166,9162,0.0,0,0,1345,0,0.19029428409734012,0.6557776694295465,2051,0,0,0.29018109790605545,0,0,1.0,1.0,1,0.0,2051,0.3712217194570136,3474,0,0,0.49151103565365023,1408,2099,9170,0.7816921335597057,2101 +exp_micro,128xf32,linalg_xdsl_b16,6310,8440,8436,0.0,0,0,1153,0,0.18272583201267828,0.6423398328690808,1795,0,0,0.2844690966719493,0,0,1.0,1.0,1,0.0,1795,0.36745138178096215,3090,0,0,0.4896988906497623,1280,2131,8444,0.7741679873217115,2133 +exp_micro,128xf32,linalg_xdsl_b2,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b3,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b4,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b5,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b6,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b7,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b8,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b9,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf64,baseline,13726,16361,16358,0.0,0,896,1665,0,0.12130263733061343,0.4816314723748915,3457,0,0,0.25185778813929766,0,0,1.0,1.0,1,12.665377176015474,3457,0.4894520741894379,3606,6548,517,0.262713099227743,261,2636,16365,0.5145708873670407,2638 +exp_micro,128xf64,linalg_xdsl_b-1,26912,29053,29049,0.0,0,0,7169,0,0.26638674197384066,0.7776331489315544,9219,0,0,0.34256093935790727,0,0,1.0,1.0,1,0.0,9219,0.41592600947439656,12946,0,0,0.48104934601664684,4096,2142,29057,0.8236102853745542,2144 +exp_micro,128xf64,linalg_xdsl_b0,26912,29053,29049,0.0,0,0,7169,0,0.26638674197384066,0.7776331489315544,9219,0,0,0.34256093935790727,0,0,1.0,1.0,1,0.0,9219,0.41592600947439656,12946,0,0,0.48104934601664684,4096,2142,29057,0.8236102853745542,2144 +exp_micro,128xf64,linalg_xdsl_b1,26912,29053,29049,0.0,0,0,7169,0,0.26638674197384066,0.7776331489315544,9219,0,0,0.34256093935790727,0,0,1.0,1.0,1,0.0,9219,0.41592600947439656,12946,0,0,0.48104934601664684,4096,2142,29057,0.8236102853745542,2144 +exp_micro,128xf64,linalg_xdsl_b10,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b11,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b12,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b13,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b14,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b15,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b16,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b2,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b3,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b4,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b5,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b6,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b7,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b8,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b9,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,16xf16,baseline,1628,4248,4245,0.0,0,48,225,0,0.1382063882063882,0.5844155844155844,385,0,0,0.23648648648648649,0,0,1.0,1.0,1,7.686274509803922,385,0.5112881806108898,368,392,51,0.22604422604422605,35,2621,4252,0.46253071253071254,2623 +exp_micro,16xf16,linalg_xdsl_b-1,522,2648,2644,0.0,0,0,97,0,0.18582375478927204,0.6598639455782312,147,0,0,0.28160919540229884,0,0,1.0,1.0,1,0.0,147,0.3491686460807601,274,0,0,0.524904214559387,96,2127,2652,0.8065134099616857,2129 +exp_micro,16xf16,linalg_xdsl_b0,484,2590,2586,0.0,0,0,85,0,0.1756198347107438,0.648854961832061,131,0,0,0.2706611570247934,0,0,1.0,1.0,1,0.0,131,0.3438320209973753,250,0,0,0.5165289256198347,88,2107,2594,0.7871900826446281,2109 +exp_micro,16xf16,linalg_xdsl_b1,484,2590,2586,0.0,0,0,85,0,0.1756198347107438,0.648854961832061,131,0,0,0.2706611570247934,0,0,1.0,1.0,1,0.0,131,0.3438320209973753,250,0,0,0.5165289256198347,88,2107,2594,0.7871900826446281,2109 +exp_micro,16xf16,linalg_xdsl_b10,340,2460,2456,0.0,0,0,49,0,0.14411764705882352,0.5903614457831325,83,0,0,0.24411764705882352,0,0,1.0,1.0,1,0.0,83,0.31800766283524906,178,0,0,0.5235294117647059,64,2121,2464,0.7676470588235295,2123 +exp_micro,16xf16,linalg_xdsl_b2,484,2590,2586,0.0,0,0,85,0,0.1756198347107438,0.648854961832061,131,0,0,0.2706611570247934,0,0,1.0,1.0,1,0.0,131,0.3438320209973753,250,0,0,0.5165289256198347,88,2107,2594,0.7871900826446281,2109 +exp_micro,16xf16,linalg_xdsl_b3,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b4,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b5,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b6,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b7,378,2471,2467,0.0,0,0,61,0,0.16137566137566137,0.6161616161616161,99,0,0,0.2619047619047619,0,0,1.0,1.0,1,0.0,99,0.3289036544850498,202,0,0,0.5343915343915344,72,2094,2475,0.7962962962962963,2096 +exp_micro,16xf16,linalg_xdsl_b8,378,2471,2467,0.0,0,0,61,0,0.16137566137566137,0.6161616161616161,99,0,0,0.2619047619047619,0,0,1.0,1.0,1,0.0,99,0.3289036544850498,202,0,0,0.5343915343915344,72,2094,2475,0.7962962962962963,2096 +exp_micro,16xf16,linalg_xdsl_b9,378,2471,2467,0.0,0,0,61,0,0.16137566137566137,0.6161616161616161,99,0,0,0.2619047619047619,0,0,1.0,1.0,1,0.0,99,0.3289036544850498,202,0,0,0.5343915343915344,72,2094,2475,0.7962962962962963,2096 +exp_micro,16xf32,baseline,1535,4155,4152,0.0,0,48,193,0,0.1257328990228013,0.546742209631728,353,0,0,0.22996742671009773,0,0,1.0,1.0,1,7.745098039215686,353,0.4895977808599168,368,395,51,0.23973941368078175,35,2621,4159,0.4697068403908795,2623 +exp_micro,16xf32,linalg_xdsl_b-1,1298,3443,3439,0.0,0,0,265,0,0.2041602465331279,0.6847545219638242,387,0,0,0.2981510015408321,0,0,1.0,1.0,1,0.0,387,0.3760932944606414,642,0,0,0.4946070878274268,240,2146,3447,0.7927580893682589,2148 +exp_micro,16xf32,linalg_xdsl_b0,1298,3443,3439,0.0,0,0,265,0,0.2041602465331279,0.6847545219638242,387,0,0,0.2981510015408321,0,0,1.0,1.0,1,0.0,387,0.3760932944606414,642,0,0,0.4946070878274268,240,2146,3447,0.7927580893682589,2148 +exp_micro,16xf32,linalg_xdsl_b1,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b10,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf32,linalg_xdsl_b11,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf32,linalg_xdsl_b12,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf32,linalg_xdsl_b13,908,3001,2997,0.0,0,0,169,0,0.18612334801762115,0.6525096525096525,259,0,0,0.2852422907488987,0,0,1.0,1.0,1,0.0,259,0.36530324400564174,450,0,0,0.4955947136563877,176,2094,3005,0.7808370044052864,2096 +exp_micro,16xf32,linalg_xdsl_b14,908,3001,2997,0.0,0,0,169,0,0.18612334801762115,0.6525096525096525,259,0,0,0.2852422907488987,0,0,1.0,1.0,1,0.0,259,0.36530324400564174,450,0,0,0.4955947136563877,176,2094,3005,0.7808370044052864,2096 +exp_micro,16xf32,linalg_xdsl_b15,908,3001,2997,0.0,0,0,169,0,0.18612334801762115,0.6525096525096525,259,0,0,0.2852422907488987,0,0,1.0,1.0,1,0.0,259,0.36530324400564174,450,0,0,0.4955947136563877,176,2094,3005,0.7808370044052864,2096 +exp_micro,16xf32,linalg_xdsl_b16,822,2942,2938,0.0,0,0,145,0,0.17639902676399027,0.6387665198237885,227,0,0,0.2761557177615572,0,0,1.0,1.0,1,0.0,227,0.36089030206677264,402,0,0,0.48905109489051096,160,2121,2946,0.7652068126520681,2123 +exp_micro,16xf32,linalg_xdsl_b2,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b3,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b4,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b5,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b6,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b7,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b8,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b9,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf64,baseline,1750,4321,4318,0.0,0,112,209,0,0.11942857142857143,0.48267898383371827,433,0,0,0.24742857142857144,0,0,1.0,1.0,1,12.35820895522388,433,0.5198079231692677,400,828,67,0.22857142857142856,35,2572,4325,0.476,2574 +exp_micro,16xf64,linalg_xdsl_b-1,3392,5518,5514,0.0,0,0,897,0,0.2644457547169811,0.7766233766233767,1155,0,0,0.3405070754716981,0,0,1.0,1.0,1,0.0,1155,0.4141269272140552,1634,0,0,0.48172169811320753,512,2127,5522,0.8222287735849056,2129 +exp_micro,16xf64,linalg_xdsl_b0,3392,5518,5514,0.0,0,0,897,0,0.2644457547169811,0.7766233766233767,1155,0,0,0.3405070754716981,0,0,1.0,1.0,1,0.0,1155,0.4141269272140552,1634,0,0,0.48172169811320753,512,2127,5522,0.8222287735849056,2129 +exp_micro,16xf64,linalg_xdsl_b1,3392,5518,5514,0.0,0,0,897,0,0.2644457547169811,0.7766233766233767,1155,0,0,0.3405070754716981,0,0,1.0,1.0,1,0.0,1155,0.4141269272140552,1634,0,0,0.48172169811320753,512,2127,5522,0.8222287735849056,2129 +exp_micro,16xf64,linalg_xdsl_b10,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b11,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b12,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b13,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b14,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b15,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b16,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b2,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b3,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b4,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b5,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b6,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b7,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b8,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b9,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,32xf16,baseline,3229,5849,5846,0.0,0,96,449,0,0.13905233818519666,0.5838751625487646,769,0,0,0.2381542273149582,0,0,1.0,1.0,1,7.6767676767676765,769,0.5164539959704499,720,760,99,0.22297925054196346,67,2621,5853,0.46113347785692166,2623 +exp_micro,32xf16,linalg_xdsl_b-1,1014,3140,3136,0.0,0,0,193,0,0.1903353057199211,0.6632302405498282,291,0,0,0.2869822485207101,0,0,1.0,1.0,1,0.0,291,0.35444579780755175,530,0,0,0.5226824457593688,192,2127,3144,0.8096646942800789,2129 +exp_micro,32xf16,linalg_xdsl_b0,928,3034,3030,0.0,0,0,169,0,0.18211206896551724,0.6525096525096525,259,0,0,0.2790948275862069,0,0,1.0,1.0,1,0.0,259,0.349527665317139,482,0,0,0.5193965517241379,176,2107,3038,0.7984913793103448,2109 +exp_micro,32xf16,linalg_xdsl_b1,928,3034,3030,0.0,0,0,169,0,0.18211206896551724,0.6525096525096525,259,0,0,0.2790948275862069,0,0,1.0,1.0,1,0.0,259,0.349527665317139,482,0,0,0.5193965517241379,176,2107,3038,0.7984913793103448,2109 +exp_micro,32xf16,linalg_xdsl_b10,640,2760,2756,0.0,0,0,97,0,0.1515625,0.5950920245398773,163,0,0,0.2546875,0,0,1.0,1.0,1,0.0,163,0.3253493013972056,338,0,0,0.528125,128,2121,2764,0.7828124999999999,2123 +exp_micro,32xf16,linalg_xdsl_b2,928,3034,3030,0.0,0,0,169,0,0.18211206896551724,0.6525096525096525,259,0,0,0.2790948275862069,0,0,1.0,1.0,1,0.0,259,0.349527665317139,482,0,0,0.5193965517241379,176,2107,3038,0.7984913793103448,2109 +exp_micro,32xf16,linalg_xdsl_b3,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b4,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b5,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b6,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b7,726,2819,2815,0.0,0,0,121,0,0.16666666666666666,0.6205128205128205,195,0,0,0.26859504132231404,0,0,1.0,1.0,1,0.0,195,0.33562822719449226,386,0,0,0.5316804407713499,144,2094,2823,0.800275482093664,2096 +exp_micro,32xf16,linalg_xdsl_b8,726,2819,2815,0.0,0,0,121,0,0.16666666666666666,0.6205128205128205,195,0,0,0.26859504132231404,0,0,1.0,1.0,1,0.0,195,0.33562822719449226,386,0,0,0.5316804407713499,144,2094,2823,0.800275482093664,2096 +exp_micro,32xf16,linalg_xdsl_b9,726,2819,2815,0.0,0,0,121,0,0.16666666666666666,0.6205128205128205,195,0,0,0.26859504132231404,0,0,1.0,1.0,1,0.0,195,0.33562822719449226,386,0,0,0.5316804407713499,144,2094,2823,0.800275482093664,2096 +exp_micro,32xf32,baseline,3039,5659,5656,0.0,0,96,385,0,0.12668641000329056,0.5460992907801419,705,0,0,0.23198420533070088,0,0,1.0,1.0,1,7.707070707070707,705,0.49473684210526314,720,763,99,0.23692003948667326,67,2621,5663,0.46890424481737414,2623 +exp_micro,32xf32,linalg_xdsl_b-1,2562,4707,4703,0.0,0,0,529,0,0.2064793130366901,0.6861219195849546,771,0,0,0.3009367681498829,0,0,1.0,1.0,1,0.0,771,0.3784977908689249,1266,0,0,0.49414519906323184,480,2146,4711,0.7950819672131147,2148 +exp_micro,32xf32,linalg_xdsl_b0,2562,4707,4703,0.0,0,0,529,0,0.2064793130366901,0.6861219195849546,771,0,0,0.3009367681498829,0,0,1.0,1.0,1,0.0,771,0.3784977908689249,1266,0,0,0.49414519906323184,480,2146,4711,0.7950819672131147,2148 +exp_micro,32xf32,linalg_xdsl_b1,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b10,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf32,linalg_xdsl_b11,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf32,linalg_xdsl_b12,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf32,linalg_xdsl_b13,1788,3881,3877,0.0,0,0,337,0,0.1884787472035794,0.654368932038835,515,0,0,0.28803131991051456,0,0,1.0,1.0,1,0.0,515,0.3686471009305655,882,0,0,0.49328859060402686,352,2094,3885,0.7813199105145414,2096 +exp_micro,32xf32,linalg_xdsl_b14,1788,3881,3877,0.0,0,0,337,0,0.1884787472035794,0.654368932038835,515,0,0,0.28803131991051456,0,0,1.0,1.0,1,0.0,515,0.3686471009305655,882,0,0,0.49328859060402686,352,2094,3885,0.7813199105145414,2096 +exp_micro,32xf32,linalg_xdsl_b15,1788,3881,3877,0.0,0,0,337,0,0.1884787472035794,0.654368932038835,515,0,0,0.28803131991051456,0,0,1.0,1.0,1,0.0,515,0.3686471009305655,882,0,0,0.49328859060402686,352,2094,3885,0.7813199105145414,2096 +exp_micro,32xf32,linalg_xdsl_b16,1606,3726,3722,0.0,0,0,289,0,0.17995018679950187,0.6407982261640798,451,0,0,0.2808219178082192,0,0,1.0,1.0,1,0.0,451,0.36459175424413903,786,0,0,0.48941469489414696,320,2121,3730,0.7702366127023661,2123 +exp_micro,32xf32,linalg_xdsl_b2,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b3,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b4,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b5,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b6,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b7,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b8,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b9,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf64,baseline,3463,6039,6036,0.0,0,224,417,0,0.12041582442968525,0.4820809248554913,865,0,0,0.2497834247762056,0,0,1.0,1.0,1,12.549618320610687,865,0.5245603395997575,784,1644,131,0.22639330060641064,67,2577,6043,0.47617672538261624,2579 +exp_micro,32xf64,linalg_xdsl_b-1,6752,8883,8879,0.0,0,0,1793,0,0.2655509478672986,0.777199826614651,2307,0,0,0.3416765402843602,0,0,1.0,1.0,1,0.0,2307,0.41515206046427927,3250,0,0,0.4813388625592417,1024,2132,8887,0.8230154028436019,2134 +exp_micro,32xf64,linalg_xdsl_b0,6752,8883,8879,0.0,0,0,1793,0,0.2655509478672986,0.777199826614651,2307,0,0,0.3416765402843602,0,0,1.0,1.0,1,0.0,2307,0.41515206046427927,3250,0,0,0.4813388625592417,1024,2132,8887,0.8230154028436019,2134 +exp_micro,32xf64,linalg_xdsl_b1,6752,8883,8879,0.0,0,0,1793,0,0.2655509478672986,0.777199826614651,2307,0,0,0.3416765402843602,0,0,1.0,1.0,1,0.0,2307,0.41515206046427927,3250,0,0,0.4813388625592417,1024,2132,8887,0.8230154028436019,2134 +exp_micro,32xf64,linalg_xdsl_b10,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b11,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b12,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b13,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b14,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b15,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b16,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b2,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b3,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b4,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b5,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b6,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b7,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b8,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b9,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,48xf16,baseline,4832,7452,7449,0.0,0,144,673,0,0.13927980132450332,0.5836947094535994,1153,0,0,0.23861754966887416,0,0,1.0,1.0,1,7.583892617449664,1153,0.47585637639290135,1270,1130,149,0.2628311258278146,101,2621,7456,0.5014486754966887,2623 +exp_micro,48xf16,linalg_xdsl_b-1,1506,3632,3628,0.0,0,0,289,0,0.19189907038512616,0.664367816091954,435,0,0,0.28884462151394424,0,0,1.0,1.0,1,0.0,435,0.35626535626535627,786,0,0,0.5219123505976095,288,2127,3636,0.8107569721115537,2129 +exp_micro,48xf16,linalg_xdsl_b0,1372,3478,3474,0.0,0,0,253,0,0.18440233236151604,0.6537467700258398,387,0,0,0.2820699708454811,0,0,1.0,1.0,1,0.0,387,0.35149863760217986,714,0,0,0.5204081632653061,264,2107,3482,0.8024781341107872,2109 +exp_micro,48xf16,linalg_xdsl_b1,1372,3478,3474,0.0,0,0,253,0,0.18440233236151604,0.6537467700258398,387,0,0,0.2820699708454811,0,0,1.0,1.0,1,0.0,387,0.35149863760217986,714,0,0,0.5204081632653061,264,2107,3482,0.8024781341107872,2109 +exp_micro,48xf16,linalg_xdsl_b10,940,3060,3056,0.0,0,0,145,0,0.15425531914893617,0.5967078189300411,243,0,0,0.25851063829787235,0,0,1.0,1.0,1,0.0,243,0.32793522267206476,498,0,0,0.5297872340425532,192,2121,3064,0.7882978723404256,2123 +exp_micro,48xf16,linalg_xdsl_b2,1372,3478,3474,0.0,0,0,253,0,0.18440233236151604,0.6537467700258398,387,0,0,0.2820699708454811,0,0,1.0,1.0,1,0.0,387,0.35149863760217986,714,0,0,0.5204081632653061,264,2107,3482,0.8024781341107872,2109 +exp_micro,48xf16,linalg_xdsl_b3,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b4,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b5,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b6,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b7,1074,3167,3163,0.0,0,0,181,0,0.1685288640595903,0.6219931271477663,291,0,0,0.2709497206703911,0,0,1.0,1.0,1,0.0,291,0.33797909407665505,570,0,0,0.5307262569832403,216,2094,3171,0.8016759776536313,2096 +exp_micro,48xf16,linalg_xdsl_b8,1074,3167,3163,0.0,0,0,181,0,0.1685288640595903,0.6219931271477663,291,0,0,0.2709497206703911,0,0,1.0,1.0,1,0.0,291,0.33797909407665505,570,0,0,0.5307262569832403,216,2094,3171,0.8016759776536313,2096 +exp_micro,48xf16,linalg_xdsl_b9,1074,3167,3163,0.0,0,0,181,0,0.1685288640595903,0.6219931271477663,291,0,0,0.2709497206703911,0,0,1.0,1.0,1,0.0,291,0.33797909407665505,570,0,0,0.5307262569832403,216,2094,3171,0.8016759776536313,2096 +exp_micro,48xf32,baseline,4544,7169,7166,0.0,0,144,577,0,0.1269806338028169,0.5458845789971618,1057,0,0,0.2326144366197183,0,0,1.0,1.0,1,7.6938775510204085,1057,0.4964772193518084,1072,1131,147,0.23591549295774647,99,2626,7173,0.46852992957746475,2628 +exp_micro,48xf32,linalg_xdsl_b-1,3826,5976,5972,0.0,0,0,793,0,0.20726607422895976,0.6865800865800866,1155,0,0,0.30188186095138525,0,0,1.0,1.0,1,0.0,1155,0.3793103448275862,1890,0,0,0.4939884997386304,720,2151,5980,0.7958703606900157,2153 +exp_micro,48xf32,linalg_xdsl_b0,3826,5976,5972,0.0,0,0,793,0,0.20726607422895976,0.6865800865800866,1155,0,0,0.30188186095138525,0,0,1.0,1.0,1,0.0,1155,0.3793103448275862,1890,0,0,0.4939884997386304,720,2151,5980,0.7958703606900157,2153 +exp_micro,48xf32,linalg_xdsl_b1,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b10,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf32,linalg_xdsl_b11,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf32,linalg_xdsl_b12,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf32,linalg_xdsl_b13,2668,4761,4757,0.0,0,0,505,0,0.18928035982008995,0.6549935149156939,771,0,0,0.28898050974512746,0,0,1.0,1.0,1,0.0,771,0.3697841726618705,1314,0,0,0.49250374812593706,528,2094,4765,0.7814842578710646,2096 +exp_micro,48xf32,linalg_xdsl_b14,2668,4761,4757,0.0,0,0,505,0,0.18928035982008995,0.6549935149156939,771,0,0,0.28898050974512746,0,0,1.0,1.0,1,0.0,771,0.3697841726618705,1314,0,0,0.49250374812593706,528,2094,4765,0.7814842578710646,2096 +exp_micro,48xf32,linalg_xdsl_b15,2668,4761,4757,0.0,0,0,505,0,0.18928035982008995,0.6549935149156939,771,0,0,0.28898050974512746,0,0,1.0,1.0,1,0.0,771,0.3697841726618705,1314,0,0,0.49250374812593706,528,2094,4765,0.7814842578710646,2096 +exp_micro,48xf32,linalg_xdsl_b16,2390,4515,4511,0.0,0,0,433,0,0.1811715481171548,0.6414814814814814,675,0,0,0.2824267782426778,0,0,1.0,1.0,1,0.0,675,0.36585365853658536,1170,0,0,0.4895397489539749,480,2126,4519,0.7719665271966527,2128 +exp_micro,48xf32,linalg_xdsl_b2,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b3,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b4,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b5,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b6,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b7,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b8,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b9,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf64,baseline,5177,7754,7751,0.0,0,336,625,0,0.12072628935677034,0.4818812644564379,1297,0,0,0.2505311956731698,0,0,1.0,1.0,1,12.615384615384615,1297,0.5261663286004057,1168,2460,195,0.2256132895499324,99,2578,7758,0.47614448522310215,2580 +exp_micro,48xf64,linalg_xdsl_b-1,10112,12243,12239,0.0,0,0,2689,0,0.2659216772151899,0.7773923099161607,3459,0,0,0.34206882911392406,0,0,1.0,1.0,1,0.0,3459,0.41549549549549547,4866,0,0,0.48121044303797467,1536,2132,12247,0.8232792721518987,2134 +exp_micro,48xf64,linalg_xdsl_b0,10112,12243,12239,0.0,0,0,2689,0,0.2659216772151899,0.7773923099161607,3459,0,0,0.34206882911392406,0,0,1.0,1.0,1,0.0,3459,0.41549549549549547,4866,0,0,0.48121044303797467,1536,2132,12247,0.8232792721518987,2134 +exp_micro,48xf64,linalg_xdsl_b1,10112,12243,12239,0.0,0,0,2689,0,0.2659216772151899,0.7773923099161607,3459,0,0,0.34206882911392406,0,0,1.0,1.0,1,0.0,3459,0.41549549549549547,4866,0,0,0.48121044303797467,1536,2132,12247,0.8232792721518987,2134 +exp_micro,48xf64,linalg_xdsl_b10,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b11,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b12,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b13,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b14,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b15,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b16,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b2,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b3,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b4,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b5,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b6,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b7,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b8,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b9,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,64xf16,baseline,6432,9052,9049,0.0,0,192,897,0,0.1394589552238806,0.5836044242029929,1537,0,0,0.23896144278606965,0,0,1.0,1.0,1,7.604060913705584,1537,0.47688488985417316,1686,1498,197,0.2621268656716418,133,2621,9056,0.5010883084577115,2623 +exp_micro,64xf16,linalg_xdsl_b-1,1998,4124,4120,0.0,0,0,385,0,0.19269269269269268,0.6649395509499136,579,0,0,0.2897897897897898,0,0,1.0,1.0,1,0.0,579,0.3571869216533004,1042,0,0,0.5215215215215215,384,2127,4128,0.8113113113113113,2129 +exp_micro,64xf16,linalg_xdsl_b0,1816,3922,3918,0.0,0,0,337,0,0.1855726872246696,0.654368932038835,515,0,0,0.28359030837004406,0,0,1.0,1.0,1,0.0,515,0.35249828884325807,946,0,0,0.5209251101321586,352,2107,3926,0.8045154185022027,2109 +exp_micro,64xf16,linalg_xdsl_b1,1816,3922,3918,0.0,0,0,337,0,0.1855726872246696,0.654368932038835,515,0,0,0.28359030837004406,0,0,1.0,1.0,1,0.0,515,0.35249828884325807,946,0,0,0.5209251101321586,352,2107,3926,0.8045154185022027,2109 +exp_micro,64xf16,linalg_xdsl_b10,1240,3360,3356,0.0,0,0,193,0,0.15564516129032258,0.5975232198142415,323,0,0,0.26048387096774195,0,0,1.0,1.0,1,0.0,323,0.3292558613659531,658,0,0,0.5306451612903226,256,2121,3364,0.7911290322580645,2123 +exp_micro,64xf16,linalg_xdsl_b2,1816,3922,3918,0.0,0,0,337,0,0.1855726872246696,0.654368932038835,515,0,0,0.28359030837004406,0,0,1.0,1.0,1,0.0,515,0.35249828884325807,946,0,0,0.5209251101321586,352,2107,3926,0.8045154185022027,2109 +exp_micro,64xf16,linalg_xdsl_b3,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b4,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b5,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b6,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b7,1422,3515,3511,0.0,0,0,241,0,0.16947960618846694,0.6227390180878553,387,0,0,0.2721518987341772,0,0,1.0,1.0,1,0.0,387,0.33917616126205086,754,0,0,0.530239099859353,288,2094,3519,0.8023909985935302,2096 +exp_micro,64xf16,linalg_xdsl_b8,1422,3515,3511,0.0,0,0,241,0,0.16947960618846694,0.6227390180878553,387,0,0,0.2721518987341772,0,0,1.0,1.0,1,0.0,387,0.33917616126205086,754,0,0,0.530239099859353,288,2094,3519,0.8023909985935302,2096 +exp_micro,64xf16,linalg_xdsl_b9,1422,3515,3511,0.0,0,0,241,0,0.16947960618846694,0.6227390180878553,387,0,0,0.2721518987341772,0,0,1.0,1.0,1,0.0,387,0.33917616126205086,754,0,0,0.530239099859353,288,2094,3519,0.8023909985935302,2096 +exp_micro,64xf32,baseline,6046,8659,8656,0.0,0,192,769,0,0.12719153159113464,0.5457771469127041,1409,0,0,0.23304664240820377,0,0,1.0,1.0,1,7.619289340101523,1409,0.4552504038772213,1686,1501,197,0.2788620575587165,133,2614,8663,0.5119086999669202,2616 +exp_micro,64xf32,linalg_xdsl_b-1,5090,7240,7236,0.0,0,0,1057,0,0.20766208251473478,0.686809616634178,1539,0,0,0.3023575638506876,0,0,1.0,1.0,1,0.0,1539,0.37971872686898595,2514,0,0,0.49390962671905697,960,2151,7244,0.7962671905697446,2153 +exp_micro,64xf32,linalg_xdsl_b0,5090,7240,7236,0.0,0,0,1057,0,0.20766208251473478,0.686809616634178,1539,0,0,0.3023575638506876,0,0,1.0,1.0,1,0.0,1539,0.37971872686898595,2514,0,0,0.49390962671905697,960,2151,7244,0.7962671905697446,2153 +exp_micro,64xf32,linalg_xdsl_b1,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b10,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf32,linalg_xdsl_b11,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf32,linalg_xdsl_b12,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf32,linalg_xdsl_b13,3548,5646,5642,0.0,0,0,673,0,0.18968432919954903,0.6553067185978578,1027,0,0,0.2894588500563698,0,0,1.0,1.0,1,0.0,1027,0.3703570140641904,1746,0,0,0.49210822998872605,704,2099,5650,0.7815670800450958,2101 +exp_micro,64xf32,linalg_xdsl_b14,3548,5646,5642,0.0,0,0,673,0,0.18968432919954903,0.6553067185978578,1027,0,0,0.2894588500563698,0,0,1.0,1.0,1,0.0,1027,0.3703570140641904,1746,0,0,0.49210822998872605,704,2099,5650,0.7815670800450958,2101 +exp_micro,64xf32,linalg_xdsl_b15,3548,5646,5642,0.0,0,0,673,0,0.18968432919954903,0.6553067185978578,1027,0,0,0.2894588500563698,0,0,1.0,1.0,1,0.0,1027,0.3703570140641904,1746,0,0,0.49210822998872605,704,2099,5650,0.7815670800450958,2101 +exp_micro,64xf32,linalg_xdsl_b16,3174,5299,5295,0.0,0,0,577,0,0.1817895400126024,0.6418242491657397,899,0,0,0.28323881537492124,0,0,1.0,1.0,1,0.0,899,0.36649001222992256,1554,0,0,0.4896030245746692,640,2126,5303,0.7728418399495904,2128 +exp_micro,64xf32,linalg_xdsl_b2,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b3,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b4,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b5,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b6,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b7,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b8,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b9,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf64,baseline,6878,9508,9505,0.0,0,448,833,0,0.1211107880197732,0.4817813765182186,1729,0,0,0.2513812154696133,0,0,1.0,1.0,1,12.582375478927203,1729,0.4880045159469376,1814,3284,261,0.26373945914510033,133,2631,9512,0.5151206746147137,2633 +exp_micro,64xf64,linalg_xdsl_b-1,13472,15608,15604,0.0,0,0,3585,0,0.26610748218527314,0.7774886141834743,4611,0,0,0.34226543942992876,0,0,1.0,1.0,1,0.0,4611,0.41566753808708196,6482,0,0,0.481146080760095,2048,2137,15612,0.8234115201900238,2139 +exp_micro,64xf64,linalg_xdsl_b0,13472,15608,15604,0.0,0,0,3585,0,0.26610748218527314,0.7774886141834743,4611,0,0,0.34226543942992876,0,0,1.0,1.0,1,0.0,4611,0.41566753808708196,6482,0,0,0.481146080760095,2048,2137,15612,0.8234115201900238,2139 +exp_micro,64xf64,linalg_xdsl_b1,13472,15608,15604,0.0,0,0,3585,0,0.26610748218527314,0.7774886141834743,4611,0,0,0.34226543942992876,0,0,1.0,1.0,1,0.0,4611,0.41566753808708196,6482,0,0,0.481146080760095,2048,2137,15612,0.8234115201900238,2139 +exp_micro,64xf64,linalg_xdsl_b10,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b11,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b12,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b13,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b14,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b15,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b16,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b2,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b3,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b4,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b5,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b6,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b7,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b8,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b9,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,80xf16,baseline,8032,10657,10654,0.0,0,240,1121,0,0.13956673306772907,0.5835502342529932,1921,0,0,0.2391683266932271,0,0,1.0,1.0,1,7.616326530612245,1921,0.47750434998757146,2102,1866,245,0.261703187250996,165,2626,10661,0.5008715139442231,2628 +exp_micro,80xf16,linalg_xdsl_b-1,2490,4621,4617,0.0,0,0,481,0,0.1931726907630522,0.665283540802213,723,0,0,0.29036144578313255,0,0,1.0,1.0,1,0.0,723,0.3577436912419594,1298,0,0,0.521285140562249,480,2132,4625,0.8116465863453814,2134 +exp_micro,80xf16,linalg_xdsl_b0,2260,4371,4367,0.0,0,0,421,0,0.18628318584070797,0.6547433903576982,643,0,0,0.2845132743362832,0,0,1.0,1.0,1,0.0,643,0.3531026908292147,1178,0,0,0.5212389380530974,440,2112,4375,0.8057522123893806,2114 +exp_micro,80xf16,linalg_xdsl_b1,2260,4371,4367,0.0,0,0,421,0,0.18628318584070797,0.6547433903576982,643,0,0,0.2845132743362832,0,0,1.0,1.0,1,0.0,643,0.3531026908292147,1178,0,0,0.5212389380530974,440,2112,4375,0.8057522123893806,2114 +exp_micro,80xf16,linalg_xdsl_b10,1540,3665,3661,0.0,0,0,241,0,0.1564935064935065,0.598014888337469,403,0,0,0.2616883116883117,0,0,1.0,1.0,1,0.0,403,0.33005733005733007,818,0,0,0.5311688311688312,320,2126,3669,0.7928571428571429,2128 +exp_micro,80xf16,linalg_xdsl_b2,2260,4371,4367,0.0,0,0,421,0,0.18628318584070797,0.6547433903576982,643,0,0,0.2845132743362832,0,0,1.0,1.0,1,0.0,643,0.3531026908292147,1178,0,0,0.5212389380530974,440,2112,4375,0.8057522123893806,2114 +exp_micro,80xf16,linalg_xdsl_b3,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b4,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b5,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b6,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b7,1770,3863,3859,0.0,0,0,301,0,0.17005649717514124,0.6231884057971014,483,0,0,0.27288135593220336,0,0,1.0,1.0,1,0.0,483,0.3399014778325123,938,0,0,0.5299435028248588,360,2094,3867,0.8028248587570621,2096 +exp_micro,80xf16,linalg_xdsl_b8,1770,3863,3859,0.0,0,0,301,0,0.17005649717514124,0.6231884057971014,483,0,0,0.27288135593220336,0,0,1.0,1.0,1,0.0,483,0.3399014778325123,938,0,0,0.5299435028248588,360,2094,3867,0.8028248587570621,2096 +exp_micro,80xf16,linalg_xdsl_b9,1770,3863,3859,0.0,0,0,301,0,0.17005649717514124,0.6231884057971014,483,0,0,0.27288135593220336,0,0,1.0,1.0,1,0.0,483,0.3399014778325123,938,0,0,0.5299435028248588,360,2094,3867,0.8028248587570621,2096 +exp_micro,80xf32,baseline,7550,10163,10160,0.0,0,240,961,0,0.12728476821192053,0.5457126632595116,1761,0,0,0.2332450331125828,0,0,1.0,1.0,1,7.628571428571429,1761,0.45586331866425056,2102,1869,245,0.27841059602649004,165,2614,10167,0.5116556291390728,2616 +exp_micro,80xf32,linalg_xdsl_b-1,6354,8504,8500,0.0,0,0,1321,0,0.2079005350960025,0.6869474778991159,1923,0,0,0.30264400377714823,0,0,1.0,1.0,1,0.0,1923,0.3799644339063426,3138,0,0,0.493862134088763,1200,2151,8508,0.7965061378659113,2153 +exp_micro,80xf32,linalg_xdsl_b0,6354,8504,8500,0.0,0,0,1321,0,0.2079005350960025,0.6869474778991159,1923,0,0,0.30264400377714823,0,0,1.0,1.0,1,0.0,1923,0.3799644339063426,3138,0,0,0.493862134088763,1200,2151,8508,0.7965061378659113,2153 +exp_micro,80xf32,linalg_xdsl_b1,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b10,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf32,linalg_xdsl_b11,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf32,linalg_xdsl_b12,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf32,linalg_xdsl_b13,4428,6526,6522,0.0,0,0,841,0,0.18992773261065943,0.6554949337490257,1283,0,0,0.28974706413730805,0,0,1.0,1.0,1,0.0,1283,0.3707021092169893,2178,0,0,0.491869918699187,880,2099,6530,0.7816169828364951,2101 +exp_micro,80xf32,linalg_xdsl_b14,4428,6526,6522,0.0,0,0,841,0,0.18992773261065943,0.6554949337490257,1283,0,0,0.28974706413730805,0,0,1.0,1.0,1,0.0,1283,0.3707021092169893,2178,0,0,0.491869918699187,880,2099,6530,0.7816169828364951,2101 +exp_micro,80xf32,linalg_xdsl_b15,4428,6526,6522,0.0,0,0,841,0,0.18992773261065943,0.6554949337490257,1283,0,0,0.28974706413730805,0,0,1.0,1.0,1,0.0,1283,0.3707021092169893,2178,0,0,0.491869918699187,880,2099,6530,0.7816169828364951,2101 +exp_micro,80xf32,linalg_xdsl_b16,3958,6083,6079,0.0,0,0,721,0,0.18216270843860535,0.6420302760463046,1123,0,0,0.28372915613946437,0,0,1.0,1.0,1,0.0,1123,0.3668735707285201,1938,0,0,0.4896412329459323,800,2126,6087,0.7733703890853967,2128 +exp_micro,80xf32,linalg_xdsl_b2,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b3,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b4,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b5,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b6,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b7,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b8,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b9,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf64,baseline,8590,11220,11217,0.0,0,560,1041,0,0.12118742724097788,0.4817214252660805,2161,0,0,0.25157159487776487,0,0,1.0,1.0,1,12.615384615384615,2161,0.4885824101288718,2262,4100,325,0.26332945285215364,165,2631,11224,0.5149010477299185,2633 +exp_micro,80xf64,linalg_xdsl_b-1,16832,18968,18964,0.0,0,0,4481,0,0.2662191064638783,0.7775464167968072,5763,0,0,0.34238355513307983,0,0,1.0,1.0,1,0.0,5763,0.4157708679027487,8098,0,0,0.4811074144486692,2560,2137,18972,0.823490969581749,2139 +exp_micro,80xf64,linalg_xdsl_b0,16832,18968,18964,0.0,0,0,4481,0,0.2662191064638783,0.7775464167968072,5763,0,0,0.34238355513307983,0,0,1.0,1.0,1,0.0,5763,0.4157708679027487,8098,0,0,0.4811074144486692,2560,2137,18972,0.823490969581749,2139 +exp_micro,80xf64,linalg_xdsl_b1,16832,18968,18964,0.0,0,0,4481,0,0.2662191064638783,0.7775464167968072,5763,0,0,0.34238355513307983,0,0,1.0,1.0,1,0.0,5763,0.4157708679027487,8098,0,0,0.4811074144486692,2560,2137,18972,0.823490969581749,2139 +exp_micro,80xf64,linalg_xdsl_b10,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b11,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b12,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b13,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b14,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b15,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b16,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b2,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b3,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b4,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b5,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b6,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b7,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b8,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b9,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,96xf16,baseline,9632,12257,12254,0.0,0,288,1345,0,0.13963870431893688,0.5835140997830802,2305,0,0,0.2393064784053156,0,0,1.0,1.0,1,7.624573378839591,2305,0.4779183081069874,2518,2234,293,0.2614202657807309,197,2626,12261,0.5007267441860466,2628 +exp_micro,96xf16,linalg_xdsl_b-1,2982,5113,5109,0.0,0,0,577,0,0.19349429912810195,0.6655132641291811,867,0,0,0.29074446680080485,0,0,1.0,1.0,1,0.0,867,0.35811648079306074,1554,0,0,0.5211267605633803,576,2132,5117,0.811871227364185,2134 +exp_micro,96xf16,linalg_xdsl_b0,2704,4815,4811,0.0,0,0,505,0,0.1867603550295858,0.6549935149156939,771,0,0,0.28513313609467456,0,0,1.0,1.0,1,0.0,771,0.3535075653370014,1410,0,0,0.5214497041420119,528,2112,4819,0.8065828402366864,2114 +exp_micro,96xf16,linalg_xdsl_b1,2704,4815,4811,0.0,0,0,505,0,0.1867603550295858,0.6549935149156939,771,0,0,0.28513313609467456,0,0,1.0,1.0,1,0.0,771,0.3535075653370014,1410,0,0,0.5214497041420119,528,2112,4819,0.8065828402366864,2114 +exp_micro,96xf16,linalg_xdsl_b10,1840,3965,3961,0.0,0,0,289,0,0.15706521739130436,0.598343685300207,483,0,0,0.2625,0,0,1.0,1.0,1,0.0,483,0.33059548254620125,978,0,0,0.5315217391304348,384,2126,3969,0.7940217391304347,2128 +exp_micro,96xf16,linalg_xdsl_b2,2704,4815,4811,0.0,0,0,505,0,0.1867603550295858,0.6549935149156939,771,0,0,0.28513313609467456,0,0,1.0,1.0,1,0.0,771,0.3535075653370014,1410,0,0,0.5214497041420119,528,2112,4819,0.8065828402366864,2114 +exp_micro,96xf16,linalg_xdsl_b3,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b4,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b5,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b6,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b7,2118,4211,4207,0.0,0,0,361,0,0.1704438149197356,0.6234887737478411,579,0,0,0.273371104815864,0,0,1.0,1.0,1,0.0,579,0.3403880070546737,1122,0,0,0.5297450424929179,432,2094,4215,0.8031161473087819,2096 +exp_micro,96xf16,linalg_xdsl_b8,2118,4211,4207,0.0,0,0,361,0,0.1704438149197356,0.6234887737478411,579,0,0,0.273371104815864,0,0,1.0,1.0,1,0.0,579,0.3403880070546737,1122,0,0,0.5297450424929179,432,2094,4215,0.8031161473087819,2096 +exp_micro,96xf16,linalg_xdsl_b9,2118,4211,4207,0.0,0,0,361,0,0.1704438149197356,0.6234887737478411,579,0,0,0.273371104815864,0,0,1.0,1.0,1,0.0,579,0.3403880070546737,1122,0,0,0.5297450424929179,432,2094,4215,0.8031161473087819,2096 +exp_micro,96xf32,baseline,9054,11667,11664,0.0,0,288,1153,0,0.1273470289374862,0.5456696639848556,2113,0,0,0.23337751270156837,0,0,1.0,1.0,1,7.63481228668942,2113,0.4562729432088102,2518,2237,293,0.27810912303954055,197,2614,11671,0.511486635741109,2616 +exp_micro,96xf32,linalg_xdsl_b-1,7618,9768,9764,0.0,0,0,1585,0,0.20805985823050668,0.6870394451668834,2307,0,0,0.3028353898661066,0,0,1.0,1.0,1,0.0,2307,0.3801285219970341,3762,0,0,0.493830401680231,1440,2151,9772,0.7966657915463375,2153 +exp_micro,96xf32,linalg_xdsl_b0,7618,9768,9764,0.0,0,0,1585,0,0.20805985823050668,0.6870394451668834,2307,0,0,0.3028353898661066,0,0,1.0,1.0,1,0.0,2307,0.3801285219970341,3762,0,0,0.493830401680231,1440,2151,9772,0.7966657915463375,2153 +exp_micro,96xf32,linalg_xdsl_b1,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b10,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf32,linalg_xdsl_b11,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf32,linalg_xdsl_b12,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf32,linalg_xdsl_b13,5308,7406,7402,0.0,0,0,1009,0,0.1900904295403165,0.6556205328135153,1539,0,0,0.289939713639789,0,0,1.0,1.0,1,0.0,1539,0.37093275488069416,2610,0,0,0.4917106254709872,1056,2099,7410,0.7816503391107762,2101 +exp_micro,96xf32,linalg_xdsl_b14,5308,7406,7402,0.0,0,0,1009,0,0.1900904295403165,0.6556205328135153,1539,0,0,0.289939713639789,0,0,1.0,1.0,1,0.0,1539,0.37093275488069416,2610,0,0,0.4917106254709872,1056,2099,7410,0.7816503391107762,2101 +exp_micro,96xf32,linalg_xdsl_b15,5308,7406,7402,0.0,0,0,1009,0,0.1900904295403165,0.6556205328135153,1539,0,0,0.289939713639789,0,0,1.0,1.0,1,0.0,1539,0.37093275488069416,2610,0,0,0.4917106254709872,1056,2099,7410,0.7816503391107762,2101 +exp_micro,96xf32,linalg_xdsl_b16,4742,6867,6863,0.0,0,0,865,0,0.18241248418388867,0.6421677802524127,1347,0,0,0.28405735976381274,0,0,1.0,1.0,1,0.0,1347,0.3671300081766149,2322,0,0,0.48966680725432304,960,2126,6871,0.7737241670181358,2128 +exp_micro,96xf32,linalg_xdsl_b2,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b3,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b4,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b5,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b6,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b7,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b8,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b9,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf64,baseline,10302,12932,12929,0.0,0,672,1249,0,0.12123859444768006,0.48168145005784807,2593,0,0,0.25169869928169286,0,0,1.0,1.0,1,12.637532133676093,2593,0.48896850839147654,2710,4916,389,0.2630557173364395,197,2631,12936,0.5147544166181324,2633 +exp_micro,96xf64,linalg_xdsl_b-1,20192,22328,22324,0.0,0,0,5377,0,0.26629358161648176,0.777584960231381,6915,0,0,0.34246236133122027,0,0,1.0,1.0,1,0.0,6915,0.41583979794335196,9714,0,0,0.48108161648177494,3072,2137,22332,0.8235439778129952,2139 +exp_micro,96xf64,linalg_xdsl_b0,20192,22328,22324,0.0,0,0,5377,0,0.26629358161648176,0.777584960231381,6915,0,0,0.34246236133122027,0,0,1.0,1.0,1,0.0,6915,0.41583979794335196,9714,0,0,0.48108161648177494,3072,2137,22332,0.8235439778129952,2139 +exp_micro,96xf64,linalg_xdsl_b1,20192,22328,22324,0.0,0,0,5377,0,0.26629358161648176,0.777584960231381,6915,0,0,0.34246236133122027,0,0,1.0,1.0,1,0.0,6915,0.41583979794335196,9714,0,0,0.48108161648177494,3072,2137,22332,0.8235439778129952,2139 +exp_micro,96xf64,linalg_xdsl_b10,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b11,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b12,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b13,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b14,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b15,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b16,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b2,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b3,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b4,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b5,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b6,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b7,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b8,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b9,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 From 2fa6bbdfb490d8f489d52ef3e7574b21e14704a3 Mon Sep 17 00:00:00 2001 From: Mia Sophie Zerdick Date: Thu, 14 May 2026 15:07:56 +0100 Subject: [PATCH 09/33] run tests again --- results/kernels.all.csv | 1353 ++++++++++++++++++++++------------- results/pivoted.all.csv | 965 ++++++++++++------------- results/pivoted_fpu.all.csv | 513 ++++++------- results/pivoted_ipc.all.csv | 419 +++++------ 4 files changed, 1823 insertions(+), 1427 deletions(-) diff --git a/results/kernels.all.csv b/results/kernels.all.csv index 9e8a9de7..02532040 100644 --- a/results/kernels.all.csv +++ b/results/kernels.all.csv @@ -1,13 +1,13 @@ test,params,impl,cycles,end,end_fpss,fpss_avg_fpu_latency,fpss_avg_load_latency,fpss_fpu_fmadd_issues,fpss_fpu_issues,fpss_fpu_latency,fpss_fpu_occupancy,fpss_fpu_rel_occupancy,fpss_issues,fpss_load_latency,fpss_loads,fpss_occupancy,fpss_section_latency,fpss_stores,fseq_fpu_yield,fseq_yield,section,snitch_avg_load_latency,snitch_fseq_offloads,snitch_fseq_rel_offloads,snitch_issues,snitch_load_latency,snitch_loads,snitch_occupancy,snitch_stores,start,tend,total_ipc,tstart conv2d_d1_s1_3x3,12x12xf64,baseline,7373,9521,9518,0.0,0,1152,1297,0,0.1759121117591211,0.32159682618398217,4033,0,0,0.5469957954699579,0,0,1.0,1.0,1,0.0,4033,0.861936311177602,646,0,0,0.08761698087616981,0,2149,9525,0.6346127763461278,2151 conv2d_d1_s1_3x3,12x12xf64,linalg,6726,8817,8814,0.0,0,1296,1297,0,0.1928337793636634,0.44878892733564013,2890,0,0,0.42967588462682127,0,0,1.0,1.0,1,3.75,2890,0.7157008420009906,1148,15,4,0.17068093963722866,304,2092,8821,0.6003568242640499,2094 -conv2d_d1_s1_3x3,12x12xf64,linalg_xdsl,2482,4611,4608,0.0,0,1296,1586,0,0.6390008058017728,0.9850931677018634,1610,0,0,0.6486704270749396,0,0,3.259109311740891,3.2591093117408905,1,0.0,494,0.3877551020408163,780,0,0,0.314262691377921,0,2130,4615,0.9629331184528607,2132 +conv2d_d1_s1_3x3,12x12xf64,linalg_xdsl,2449,4550,4547,0.0,0,1296,1586,0,0.6476112699060841,0.9850931677018634,1610,0,0,0.657411188240098,0,0,3.3402489626556013,3.340248962655602,1,0.0,482,0.3931484502446982,744,0,0,0.3037974683544304,0,2102,4554,0.9612086565945284,2104 conv2d_d1_s1_3x3,12x16xf64,baseline,9817,11989,11986,0.0,0,1536,1729,0,0.17612305184883364,0.3215547703180212,5377,0,0,0.5477233370683509,0,0,1.0,1.0,1,0.0,5377,0.8651649235720033,838,0,0,0.08536212692268513,0,2173,11993,0.6330854639910359,2175 conv2d_d1_s1_3x3,12x16xf64,linalg,8934,11077,11074,0.0,0,1728,1729,0,0.19353033355719723,0.4490909090909091,3850,0,0,0.43093798970226105,0,0,1.0,1.0,1,3.75,3850,0.7217847769028871,1484,15,4,0.16610700693978062,400,2144,11081,0.5970449966420417,2146 conv2d_d1_s1_3x3,12x16xf64,linalg_xdsl,3034,5140,5137,0.0,0,1728,2114,0,0.6967699406723797,0.9887745556594949,2138,0,0,0.7046802900461437,0,0,3.2892307692307687,3.289230769230769,1,0.0,650,0.4433833560709413,816,0,0,0.26895187870797627,0,2107,5144,0.9736321687541201,2109 conv2d_d1_s1_3x3,12x20xf64,baseline,12265,14426,14423,0.0,0,1920,2161,0,0.17619241744802283,0.32152953429549175,6721,0,0,0.5479820627802691,0,0,1.0,1.0,1,0.0,6721,0.867113920784415,1030,0,0,0.08397880146759071,0,2162,14430,0.6319608642478598,2164 conv2d_d1_s1_3x3,12x20xf64,linalg,11149,13318,13315,0.0,0,2160,2161,0,0.19382904296349449,0.44927234927234927,4810,0,0,0.43142882769755136,0,0,1.0,1.0,1,3.75,4810,0.7254901960784313,1820,15,4,0.1632433402098843,496,2170,13322,0.5946721679074356,2172 -conv2d_d1_s1_3x3,12x20xf64,linalg_xdsl,3578,5707,5704,0.0,0,2160,2642,0,0.7384013415315819,0.9909977494373593,2666,0,0,0.7451089994410285,0,0,3.307692307692308,3.3076923076923075,1,0.0,806,0.48612786489746684,852,0,0,0.23812185578535494,0,2130,5711,0.9832308552263834,2132 +conv2d_d1_s1_3x3,12x20xf64,linalg_xdsl,3554,5677,5674,0.0,0,2160,2642,0,0.7433877321328081,0.9909977494373593,2666,0,0,0.7501406865503658,0,0,3.3576826196473553,3.3576826196473553,1,0.0,794,0.493167701863354,816,0,0,0.22960045019696118,0,2124,5681,0.979741136747327,2126 conv2d_d1_s1_3x3,12x4xf64,baseline,2445,4559,4556,0.0,0,384,433,0,0.17709611451942742,0.32193308550185873,1345,0,0,0.5501022494887525,0,0,1.0,1.0,1,0.0,1345,0.9593437945791726,57,0,0,0.023312883435582823,0,2115,4563,0.5734151329243353,2117 conv2d_d1_s1_3x3,12x4xf64,linalg,2084,4150,4147,0.0,0,432,433,0,0.20777351247600767,0.5742705570291777,754,0,0,0.3618042226487524,0,0,1.0,1.0,1,3.75,754,0.748015873015873,254,15,4,0.1218809980806142,112,2067,4154,0.4836852207293666,2069 conv2d_d1_s1_3x3,12x4xf64,linalg_xdsl,628,2732,2729,0.0,0,432,530,0,0.8439490445859873,0.9962406015037594,532,0,0,0.8471337579617835,0,0,3.325,3.325,1,0.0,160,0.6477732793522267,87,0,0,0.13853503184713375,0,2105,2736,0.9856687898089173,2107 @@ -16,13 +16,13 @@ conv2d_d1_s1_3x3,12x8xf64,linalg,4518,6594,6591,0.0,0,864,865,0,0.19145639663567 conv2d_d1_s1_3x3,12x8xf64,linalg_xdsl,1930,4044,4041,0.0,0,864,1058,0,0.5481865284974093,0.977818853974122,1082,0,0,0.5606217616580311,0,0,3.201183431952663,3.201183431952663,1,0.0,338,0.3123844731977819,744,0,0,0.3854922279792746,0,2115,4048,0.9461139896373058,2117 conv2d_d1_s1_3x3,16x12xf64,baseline,9817,11989,11986,0.0,0,1536,1729,0,0.17612305184883364,0.3215547703180212,5377,0,0,0.5477233370683509,0,0,1.0,1.0,1,0.0,5377,0.8623897353648757,858,0,0,0.08739940918814301,0,2173,11993,0.6351227462564939,2175 conv2d_d1_s1_3x3,16x12xf64,linalg,8934,11077,11074,0.0,0,1728,1729,0,0.19353033355719723,0.4490909090909091,3850,0,0,0.43093798970226105,0,0,1.0,1.0,1,3.75,3850,0.7185516983949235,1508,15,4,0.16879337362883368,400,2144,11081,0.5997313633310948,2146 -conv2d_d1_s1_3x3,16x12xf64,linalg_xdsl,3298,5404,5401,0.0,0,1728,2114,0,0.6409945421467557,0.9850885368126747,2146,0,0,0.6506973923590055,0,0,3.2613981762917934,3.2613981762917934,1,0.0,658,0.3884297520661157,1036,0,0,0.31412977562158884,0,2107,5408,0.9648271679805943,2109 +conv2d_d1_s1_3x3,16x12xf64,linalg_xdsl,3257,5411,5408,0.0,0,1728,2114,0,0.6490635554190973,0.9850885368126747,2146,0,0,0.6588885477433221,0,0,3.3426791277258565,3.3426791277258565,1,0.0,642,0.39386503067484663,988,0,0,0.30334663801043904,0,2155,5415,0.9622351857537611,2157 conv2d_d1_s1_3x3,16x16xf64,baseline,13081,15256,15253,0.0,0,2048,2305,0,0.17620976989526796,0.32152322499651276,7169,0,0,0.5480467854139591,0,0,1.0,1.0,1,0.0,7169,0.8655076663044791,1114,0,0,0.08516168488647657,0,2176,15260,0.6332084703004357,2178 conv2d_d1_s1_3x3,16x16xf64,linalg,11885,14060,14057,0.0,0,2304,2305,0,0.19394194362641987,0.449317738791423,5130,0,0,0.4316365166175852,0,0,1.0,1.0,1,3.75,5130,0.7238605898123325,1957,15,4,0.1646613378207825,528,2176,14064,0.5962978544383677,2178 conv2d_d1_s1_3x3,16x16xf64,linalg_xdsl,4026,6149,6146,0.0,0,2304,2818,0,0.6999503229011426,0.9887719298245614,2850,0,0,0.7078986587183308,0,0,3.2909930715935336,3.2909930715935336,1,0.0,866,0.4441025641025641,1084,0,0,0.26924987580725285,0,2124,6153,0.9771485345255837,2126 conv2d_d1_s1_3x3,16x20xf64,baseline,16345,18535,18532,0.0,0,2560,2881,0,0.17626185377791373,0.32150429639549155,8961,0,0,0.5482410523095748,0,0,1.0,1.0,1,0.0,8961,0.8673894105120511,1370,0,0,0.0838176812480881,0,2191,18539,0.6320587335576628,2193 conv2d_d1_s1_3x3,16x20xf64,linalg,14829,17019,17016,0.0,0,2880,2881,0,0.194281475487221,0.44945397815912635,6410,0,0,0.43226110998718725,0,0,1.0,1.0,1,3.75,6410,0.7271695972773681,2405,15,4,0.16218221053341425,656,2191,17023,0.5944433205206014,2193 -conv2d_d1_s1_3x3,16x20xf64,linalg_xdsl,4762,6900,6897,0.0,0,2880,3522,0,0.739605207895842,0.9909960607765897,3554,0,0,0.7463250734985301,0,0,3.3091247672253257,3.3091247672253257,1,0.0,1074,0.48685403445149594,1132,0,0,0.2377152456950861,0,2139,6904,0.9840403191936161,2141 +conv2d_d1_s1_3x3,16x20xf64,linalg_xdsl,4730,6897,6894,0.0,0,2880,3522,0,0.7446088794926005,0.9909960607765897,3554,0,0,0.7513742071881607,0,0,3.3591682419659734,3.3591682419659734,1,0.0,1058,0.4939309056956116,1084,0,0,0.22917547568710359,0,2168,6901,0.9805496828752643,2170 conv2d_d1_s1_3x3,16x4xf64,baseline,3258,5374,5371,0.0,0,512,577,0,0.1771025168815224,0.3218070273284997,1793,0,0,0.5503376304481277,0,0,1.0,1.0,1,0.0,1793,0.9603642206748795,74,0,0,0.022713321055862493,0,2117,5378,0.5730509515039902,2119 conv2d_d1_s1_3x3,16x4xf64,linalg,2748,4819,4816,0.0,0,576,577,0,0.20997088791848617,0.5758483033932136,1002,0,0,0.3646288209606987,0,0,1.0,1.0,1,3.75,1002,0.759090909090909,318,15,4,0.11572052401746726,144,2072,4823,0.48034934497816595,2074 conv2d_d1_s1_3x3,16x4xf64,linalg_xdsl,812,2921,2918,0.0,0,576,706,0,0.8694581280788177,0.9971751412429378,708,0,0,0.8719211822660099,0,0,3.339622641509434,3.339622641509434,1,0.0,212,0.6816720257234726,99,0,0,0.12192118226600986,0,2110,2925,0.9938423645320198,2112 @@ -31,13 +31,13 @@ conv2d_d1_s1_3x3,16x8xf64,linalg,5990,8076,8073,0.0,0,1152,1153,0,0.192487479131 conv2d_d1_s1_3x3,16x8xf64,linalg_xdsl,2562,4686,4683,0.0,0,1152,1410,0,0.550351288056206,0.9778085991678225,1442,0,0,0.5628415300546448,0,0,3.2044444444444444,3.2044444444444444,1,0.0,450,0.3129346314325452,988,0,0,0.38563622170179546,0,2125,4690,0.9484777517564402,2127 conv2d_d1_s1_3x3,20x12xf64,baseline,12265,14426,14423,0.0,0,1920,2161,0,0.17619241744802283,0.32152953429549175,6721,0,0,0.5479820627802691,0,0,1.0,1.0,1,0.0,6721,0.8626620459504557,1070,0,0,0.08724011414594374,0,2162,14430,0.6352221769262127,2164 conv2d_d1_s1_3x3,20x12xf64,linalg,11149,13318,13315,0.0,0,2160,2161,0,0.19382904296349449,0.44927234927234927,4810,0,0,0.43142882769755136,0,0,1.0,1.0,1,3.75,4810,0.7202755315962863,1868,15,4,0.16754865907256256,496,2170,13322,0.5989774867701139,2172 -conv2d_d1_s1_3x3,20x12xf64,linalg_xdsl,4106,6235,6232,0.0,0,2160,2642,0,0.6434486117876279,0.9850857568978374,2682,0,0,0.6531904529956162,0,0,3.2627737226277373,3.2627737226277373,1,0.0,822,0.3888363292336802,1292,0,0,0.3146614710180224,0,2130,6239,0.9678519240136385,2132 +conv2d_d1_s1_3x3,20x12xf64,linalg_xdsl,4066,6245,6242,0.0,0,2160,2642,0,0.6497786522380719,0.9850857568978374,2682,0,0,0.6596163305459911,0,0,3.344139650872818,3.344139650872818,1,0.0,802,0.3942969518190757,1232,0,0,0.30300049188391537,0,2180,6249,0.9626168224299065,2182 conv2d_d1_s1_3x3,20x16xf64,baseline,16345,18535,18532,0.0,0,2560,2881,0,0.17626185377791373,0.32150429639549155,8961,0,0,0.5482410523095748,0,0,1.0,1.0,1,0.0,8961,0.8657134576369433,1390,0,0,0.08504129703273172,0,2191,18539,0.6332823493423065,2193 conv2d_d1_s1_3x3,20x16xf64,linalg,14829,17019,17016,0.0,0,2880,2881,0,0.194281475487221,0.44945397815912635,6410,0,0,0.43226110998718725,0,0,1.0,1.0,1,3.75,6410,0.7251951578232831,2429,15,4,0.16380066086721964,656,2191,17023,0.5960617708544069,2193 conv2d_d1_s1_3x3,20x16xf64,linalg_xdsl,5026,7164,7161,0.0,0,2880,3522,0,0.7007560684440908,0.9887703537338574,3562,0,0,0.7087146836450458,0,0,3.292051756007394,3.292051756007394,1,0.0,1082,0.4445357436318817,1352,0,0,0.26900119379228016,0,2139,7168,0.9777158774373259,2141 conv2d_d1_s1_3x3,20x20xf64,baseline,20425,22635,22632,0.0,0,3200,3601,0,0.17630354957160344,0.32148915275421835,11201,0,0,0.5483965728274174,0,0,1.0,1.0,1,0.0,11201,0.867554798234064,1710,0,0,0.08372093023255814,0,2211,22639,0.6321175030599755,2213 conv2d_d1_s1_3x3,20x20xf64,linalg,18509,20724,20721,0.0,0,3600,3601,0,0.1945540007563888,0.4495630461922597,8010,0,0,0.43276243989410557,0,0,1.0,1.0,1,3.75,8010,0.7282480225475043,2989,15,4,0.16148900534874927,816,2216,20728,0.5942514452428549,2218 -conv2d_d1_s1_3x3,20x20xf64,linalg_xdsl,5946,8104,8101,0.0,0,3600,4402,0,0.7403296333669694,0.9909950472760019,4442,0,0,0.7470568449377732,0,0,3.3099850968703426,3.3099850968703426,1,0.0,1342,0.48729121278140886,1412,0,0,0.23747056844937772,0,2159,8108,0.984527413387151,2161 +conv2d_d1_s1_3x3,20x20xf64,linalg_xdsl,5906,8093,8090,0.0,0,3600,4402,0,0.7453437182526245,0.9909950472760019,4442,0,0,0.7521164917033525,0,0,3.3600605143721634,3.3600605143721634,1,0.0,1322,0.4943904263275991,1352,0,0,0.22891974263460887,0,2188,8097,0.9810362343379614,2190 conv2d_d1_s1_3x3,20x4xf64,baseline,4061,6185,6182,0.0,0,640,721,0,0.17754247722235902,0.32173136992414103,2241,0,0,0.5518345235163753,0,0,1.0,1.0,1,0.0,2241,0.9618025751072962,89,0,0,0.021915784289583847,0,2125,6189,0.5737503078059591,2127 conv2d_d1_s1_3x3,20x4xf64,linalg,3412,5488,5485,0.0,0,720,721,0,0.21131301289566237,0.5768,1250,0,0,0.36635404454865184,0,0,1.0,1.0,1,3.75,1250,0.7659313725490197,382,15,4,0.111957796014068,176,2077,5492,0.4783118405627198,2079 conv2d_d1_s1_3x3,20x4xf64,linalg_xdsl,996,3110,3107,0.0,0,720,882,0,0.8855421686746988,0.997737556561086,884,0,0,0.8875502008032129,0,0,3.348484848484848,3.3484848484848486,1,0.0,264,0.704,111,0,0,0.11144578313253012,0,2115,3114,0.998995983935743,2117 @@ -46,13 +46,13 @@ conv2d_d1_s1_3x3,20x8xf64,linalg,7462,9558,9555,0.0,0,1440,1441,0,0.193111766282 conv2d_d1_s1_3x3,20x8xf64,linalg_xdsl,3194,5328,5325,0.0,0,1440,1762,0,0.5516593613024421,0.9778024417314095,1802,0,0,0.5641828428303068,0,0,3.206405693950178,3.206405693950178,1,0.0,562,0.3132664437012263,1232,0,0,0.3857232310582342,0,2135,5332,0.949906073888541,2137 conv2d_d1_s1_3x3,4x12xf64,baseline,2479,4569,4566,0.0,0,384,433,0,0.17466720451795079,0.32193308550185873,1345,0,0,0.5425574828559904,0,0,1.0,1.0,1,0.0,1345,0.8632862644415917,213,0,0,0.08592174263816055,0,2091,4573,0.6284792254941509,2093 conv2d_d1_s1_3x3,4x12xf64,linalg,2303,4367,4364,0.0,0,432,434,0,0.1884498480243161,0.45255474452554745,959,0,0,0.41641337386018235,0,0,1.0,1.0,1,3.75,959,0.6949275362318841,421,15,4,0.18280503690838038,112,2065,4371,0.5992184107685627,2067 -conv2d_d1_s1_3x3,4x12xf64,linalg_xdsl,850,2954,2951,0.0,0,432,530,0,0.6235294117647059,0.9851301115241635,538,0,0,0.6329411764705882,0,0,3.240963855421687,3.2409638554216866,1,0.0,166,0.3824884792626728,268,0,0,0.31529411764705884,0,2105,2958,0.9482352941176471,2107 +conv2d_d1_s1_3x3,4x12xf64,linalg_xdsl,833,2909,2906,0.0,0,432,530,0,0.6362545018007203,0.9851301115241635,538,0,0,0.6458583433373349,0,0,3.3209876543209877,3.3209876543209877,1,0.0,162,0.3875598086124402,256,0,0,0.30732292917166865,0,2077,2913,0.9531812725090036,2079 conv2d_d1_s1_3x3,4x16xf64,baseline,3295,5390,5387,0.0,0,512,577,0,0.17511380880121397,0.3218070273284997,1793,0,0,0.5441578148710167,0,0,1.0,1.0,1,0.0,1793,0.866183574879227,277,0,0,0.08406676783004552,0,2096,5394,0.6282245827010622,2098 conv2d_d1_s1_3x3,4x16xf64,linalg,3035,5104,5101,0.0,0,576,578,0,0.19044481054365733,0.4533333333333333,1275,0,0,0.4200988467874794,0,0,1.0,1.0,1,3.75,1275,0.7036423841059603,537,15,4,0.17693574958813837,144,2070,5108,0.5970345963756177,2072 conv2d_d1_s1_3x3,4x16xf64,linalg_xdsl,1034,3143,3140,0.0,0,576,706,0,0.6827852998065764,0.988795518207283,714,0,0,0.690522243713733,0,0,3.275229357798165,3.2752293577981653,1,0.0,218,0.43775100401606426,280,0,0,0.27079303675048355,0,2110,3147,0.9613152804642167,2112 conv2d_d1_s1_3x3,4x20xf64,baseline,4111,6211,6208,0.0,0,640,721,0,0.17538311846266116,0.32173136992414103,2241,0,0,0.5451228411578691,0,0,1.0,1.0,1,0.0,2241,0.8679318357862122,341,0,0,0.08294818778885917,0,2101,6215,0.6280710289467283,2103 conv2d_d1_s1_3x3,4x20xf64,linalg,3767,5836,5833,0.0,0,720,722,0,0.1916644544730555,0.4538026398491515,1591,0,0,0.42235200424741176,0,0,1.0,1.0,1,3.75,1591,0.7090017825311943,653,15,4,0.17334749137244493,176,2070,5840,0.5956994956198567,2072 -conv2d_d1_s1_3x3,4x20xf64,linalg_xdsl,1218,3332,3329,0.0,0,720,882,0,0.7241379310344828,0.9910112359550561,890,0,0,0.7307060755336617,0,0,3.2962962962962963,3.2962962962962963,1,0.0,270,0.4804270462633452,292,0,0,0.23973727422003285,0,2115,3336,0.9704433497536946,2117 +conv2d_d1_s1_3x3,4x20xf64,linalg_xdsl,1202,3284,3281,0.0,0,720,882,0,0.7337770382695508,0.9910112359550561,890,0,0,0.740432612312812,0,0,3.3458646616541357,3.345864661654135,1,0.0,266,0.48717948717948717,280,0,0,0.23294509151414308,0,2083,3288,0.9733777038269551,2085 conv2d_d1_s1_3x3,4x4xf64,baseline,825,2929,2926,0.0,0,128,145,0,0.17575757575757575,0.32293986636971045,449,0,0,0.5442424242424242,0,0,1.0,1.0,1,0.0,449,0.9452631578947368,26,0,0,0.03151515151515152,0,2105,2933,0.5757575757575757,2107 conv2d_d1_s1_3x3,4x4xf64,linalg,752,2832,2829,0.0,0,144,145,0,0.19281914893617022,0.562015503875969,258,0,0,0.34308510638297873,0,0,1.0,1.0,1,3.75,258,0.671875,126,15,4,0.1675531914893617,48,2081,2836,0.5106382978723405,2083 conv2d_d1_s1_3x3,4x4xf64,linalg_xdsl,248,2325,2322,0.0,0,144,178,0,0.717741935483871,0.9888888888888889,180,0,0,0.7258064516129032,0,0,3.214285714285714,3.2142857142857144,1,0.0,56,0.47058823529411764,63,0,0,0.2540322580645161,0,2078,2329,0.9798387096774194,2080 @@ -61,13 +61,13 @@ conv2d_d1_s1_3x3,4x8xf64,linalg,1436,3548,3545,0.0,0,287,289,0,0.201253481894150 conv2d_d1_s1_3x3,4x8xf64,linalg_xdsl,666,2770,2767,0.0,0,288,354,0,0.5315315315315315,0.9779005524861878,362,0,0,0.5435435435435435,0,0,3.175438596491228,3.175438596491228,1,0.0,114,0.3081081081081081,256,0,0,0.3843843843843844,0,2105,2774,0.9279279279279279,2107 conv2d_d1_s1_3x3,8x12xf64,baseline,4925,7058,7055,0.0,0,768,865,0,0.17563451776649747,0.32168092227593903,2689,0,0,0.545989847715736,0,0,1.0,1.0,1,0.0,2689,0.8610310598783222,434,0,0,0.08812182741116752,0,2134,7062,0.6341116751269035,2136 conv2d_d1_s1_3x3,8x12xf64,linalg,4518,6594,6591,0.0,0,864,865,0,0.1914563966356795,0.4481865284974093,1930,0,0,0.4271801682160248,0,0,1.0,1.0,1,3.75,1930,0.7100809418690214,788,15,4,0.17441345728198318,208,2077,6598,0.601593625498008,2079 -conv2d_d1_s1_3x3,8x12xf64,linalg_xdsl,1666,3780,3777,0.0,0,864,1058,0,0.6350540216086434,0.9851024208566108,1074,0,0,0.6446578631452581,0,0,3.2545454545454544,3.2545454545454544,1,0.0,330,0.3864168618266979,524,0,0,0.31452581032412963,0,2115,3784,0.9591836734693877,2117 +conv2d_d1_s1_3x3,8x12xf64,linalg_xdsl,1641,3727,3724,0.0,0,864,1058,0,0.6447288238878732,0.9851024208566108,1074,0,0,0.6544789762340036,0,0,3.3354037267080745,3.3354037267080745,1,0.0,322,0.39172749391727496,500,0,0,0.30469226081657524,0,2087,3731,0.9591712370505789,2089 conv2d_d1_s1_3x3,8x16xf64,baseline,6557,8700,8697,0.0,0,1024,1153,0,0.17584261095012962,0.32161785216178523,3585,0,0,0.5467439377764222,0,0,1.0,1.0,1,0.0,3585,0.8644803472389679,562,0,0,0.08570992832087845,0,2144,8704,0.6324538660973006,2146 conv2d_d1_s1_3x3,8x16xf64,linalg,5990,8076,8073,0.0,0,1152,1153,0,0.1924874791318865,0.44863813229571986,2570,0,0,0.4290484140233723,0,0,1.0,1.0,1,3.75,2570,0.7174762702400893,1012,15,4,0.16894824707846412,272,2087,8080,0.5979966611018364,2089 conv2d_d1_s1_3x3,8x16xf64,linalg_xdsl,2034,4158,4155,0.0,0,1152,1410,0,0.6932153392330384,0.9887798036465638,1426,0,0,0.7010816125860374,0,0,3.2857142857142856,3.2857142857142856,1,0.0,434,0.4419551934826884,548,0,0,0.2694198623402163,0,2125,4162,0.9705014749262537,2127 conv2d_d1_s1_3x3,8x20xf64,baseline,8189,10342,10339,0.0,0,1280,1441,0,0.17596776163145683,0.32158000446328944,4481,0,0,0.5471974600073269,0,0,1.0,1.0,1,0.0,4481,0.8665635273641462,690,0,0,0.08425937232873366,0,2154,10346,0.6314568323360606,2156 conv2d_d1_s1_3x3,8x20xf64,linalg,7462,9558,9555,0.0,0,1440,1441,0,0.193111766282498,0.4489096573208723,3210,0,0,0.43017957652103994,0,0,1.0,1.0,1,3.75,3210,0.7219973009446694,1236,15,4,0.16563923880997053,336,2097,9562,0.5958188153310104,2099 -conv2d_d1_s1_3x3,8x20xf64,linalg_xdsl,2402,4536,4533,0.0,0,1440,1762,0,0.7335553705245629,0.9910011248593926,1778,0,0,0.7402164862614488,0,0,3.3048327137546467,3.3048327137546467,1,0.0,538,0.4846846846846847,572,0,0,0.23813488759367193,0,2135,4540,0.9783513738551207,2137 +conv2d_d1_s1_3x3,8x20xf64,linalg_xdsl,2378,4480,4477,0.0,0,1440,1762,0,0.7409587888982339,0.9910011248593926,1778,0,0,0.7476871320437343,0,0,3.3547169811320754,3.3547169811320754,1,0.0,530,0.49165120593692024,548,0,0,0.2304457527333894,0,2103,4484,0.9781328847771237,2105 conv2d_d1_s1_3x3,8x4xf64,baseline,1642,3753,3750,0.0,0,256,289,0,0.17600487210718635,0.3221850613154961,897,0,0,0.546285018270402,0,0,1.0,1.0,1,0.0,897,0.9552715654952076,42,0,0,0.025578562728380026,0,2112,3757,0.571863580998782,2114 conv2d_d1_s1_3x3,8x4xf64,linalg,1420,3486,3483,0.0,0,288,289,0,0.2035211267605634,0.5711462450592886,506,0,0,0.3563380281690141,0,0,1.0,1.0,1,3.75,506,0.7270114942528736,190,15,4,0.13380281690140844,80,2067,3490,0.49014084507042255,2069 conv2d_d1_s1_3x3,8x4xf64,linalg_xdsl,444,2548,2545,0.0,0,288,354,0,0.7972972972972973,0.9943820224719101,356,0,0,0.8018018018018018,0,0,3.2962962962962963,3.2962962962962963,1,0.0,108,0.5901639344262295,75,0,0,0.16891891891891891,0,2105,2552,0.9707207207207207,2107 @@ -93,27 +93,414 @@ exp_macro,384xf64,snrt,6582,12497,12493,0.0,0,1152,3851,0,0.5850805226374962,0.9 exp_macro,448xf64,snrt,7523,14078,14075,0.0,0,1344,4492,0,0.5971022198590987,0.9920494699646644,4528,0,0,0.6018875448624219,0,0,13.436201780415429,13.43620178041543,1,4.593147751605995,337,0.055318450426789234,5755,6435,1401,0.764987372059019,942,6556,14082,1.366874916921441,6558 exp_macro,512xf64,snrt,8453,15649,15646,0.0,0,1536,5133,0,0.6072400331243346,0.9926513246954167,5171,0,0,0.6117354785283331,0,0,13.572178477690288,13.572178477690288,1,4.613947696139477,381,0.0554504438946296,6490,7410,1606,0.7677747545250208,1078,7197,15653,1.3795102330533537,7199 exp_macro,64xf64,snrt,1897,4593,4590,0.0,0,192,646,0,0.34053769109119664,0.9656203288490284,669,0,0,0.3526620980495519,0,0,9.422535211267606,9.422535211267606,1,4.342592592592593,71,0.06484018264840183,1024,938,216,0.5397996837111229,174,2697,4597,0.8924617817606748,2699 -exp_micro,106xf16,baseline,10632,13229,13226,0.0,0,318,1485,0,0.1396726862302483,0.5834970530451866,2545,0,0,0.23937170805116628,0,0,1.0,1.0,1,7.628482972136223,2545,0.4779342723004695,2780,2464,323,0.2614747930775019,217,2598,13233,0.5008465011286681,2600 -exp_micro,106xf32,baseline,9994,12654,12651,0.0,0,318,1273,0,0.12737642585551331,0.5456493784826404,2333,0,0,0.23344006403842305,0,0,1.0,1.0,1,7.637770897832818,2333,0.4562878936045375,2780,2467,323,0.27816690014008405,217,2661,12658,0.511606964178507,2663 -exp_micro,106xf64,baseline,11380,13957,13954,0.0,0,742,1379,0,0.12117750439367311,0.48166259168704156,2863,0,0,0.2515817223198594,0,0,1.0,1.0,1,12.648018648018647,2863,0.48898377455166525,2992,5426,429,0.26291739894551847,217,2578,13961,0.5144991212653779,2580 -exp_micro,122xf16,baseline,12232,14829,14826,0.0,0,366,1709,0,0.1397155003270111,0.5834755889382042,2929,0,0,0.2394538914323087,0,0,1.0,1.0,1,7.633423180592992,2929,0.47820408163265304,3196,2832,371,0.26128188358404186,249,2598,14833,0.5007357750163506,2600 -exp_micro,122xf32,baseline,11498,14163,14160,0.0,0,366,1465,0,0.12741346321099323,0.5456238361266295,2685,0,0,0.23351887284745174,0,0,1.0,1.0,1,7.6415094339622645,2685,0.4565550076517599,3196,2835,371,0.2779613845886241,249,2666,14167,0.5114802574360758,2668 -exp_micro,122xf64,baseline,13092,15669,15666,0.0,0,854,1587,0,0.12121906507791018,0.48163884673748103,3295,0,0,0.2516804155209288,0,0,1.0,1.0,1,12.661257606490873,3295,0.4892353377876763,3440,6242,493,0.26275588145432327,249,2578,15673,0.5144362969752521,2580 -exp_micro,26xf16,baseline,2641,5335,5332,0.0,0,78,365,0,0.13820522529344945,0.584,625,0,0,0.23665278303672851,0,0,1.0,1.0,1,7.679012345679013,625,0.51440329218107,590,622,81,0.2234002271866717,55,2695,5339,0.4600530102234002,2697 -exp_micro,26xf32,baseline,2487,5079,5076,0.0,0,78,313,0,0.12585444310414154,0.5462478184991274,573,0,0,0.23039806996381182,0,0,1.0,1.0,1,7.716049382716049,573,0.4926913155631986,590,625,81,0.2372336147969441,55,2593,5083,0.4676316847607559,2595 -exp_micro,26xf64,baseline,2815,5380,5377,0.0,0,182,339,0,0.12042628774422735,0.4822190611664296,703,0,0,0.2497335701598579,0,0,1.0,1.0,1,12.504672897196262,703,0.5226765799256505,642,1338,107,0.22806394316163411,55,2566,5384,0.477797513321492,2568 -exp_micro,42xf16,baseline,4232,6824,6821,0.0,0,126,589,0,0.13917769376181474,0.5837462834489594,1009,0,0,0.23842155009451796,0,0,1.0,1.0,1,7.572519083969466,1009,0.4748235294117647,1116,992,131,0.2637051039697543,89,2593,6828,0.5021266540642723,2595 -exp_micro,42xf32,baseline,3992,6589,6586,0.0,0,126,505,0,0.12650300601202405,0.5459459459459459,925,0,0,0.2317134268537074,0,0,1.0,1.0,1,7.6976744186046515,925,0.49544724156400644,942,993,129,0.23597194388777556,87,2598,6593,0.467685370741483,2600 -exp_micro,42xf64,baseline,4536,7112,7109,0.0,0,294,547,0,0.12059082892416226,0.4819383259911894,1135,0,0,0.2502204585537919,0,0,1.0,1.0,1,12.596491228070175,1135,0.5252198056455345,1026,2154,171,0.2261904761904762,87,2577,7116,0.4764109347442681,2579 -exp_micro,58xf16,baseline,5832,8424,8421,0.0,0,174,813,0,0.13940329218106995,0.583632447954056,1393,0,0,0.2388545953360768,0,0,1.0,1.0,1,7.597765363128492,1393,0.47623931623931626,1532,1360,179,0.2626886145404664,121,2593,8428,0.5015432098765432,2595 -exp_micro,58xf32,baseline,5482,8142,8139,0.0,0,174,697,0,0.127143378329077,0.5458104933437745,1277,0,0,0.23294418095585553,0,0,1.0,1.0,1,7.614525139664805,1277,0.45461018155927374,1532,1363,179,0.27946005107624955,121,2661,8146,0.5124042320321051,2663 -exp_micro,58xf64,baseline,6244,8816,8813,0.0,0,406,755,0,0.1209160794362588,0.48181238034460755,1567,0,0,0.25096092248558616,0,0,1.0,1.0,1,12.565400843881857,1567,0.48740279937791603,1648,2978,237,0.26393337604099937,121,2573,8820,0.5148942985265855,2575 -exp_micro,74xf16,baseline,7432,10029,10026,0.0,0,222,1037,0,0.13953175457481162,0.5835678109172763,1777,0,0,0.23910118406889128,0,0,1.0,1.0,1,7.612334801762114,1777,0.4770469798657718,1948,1728,227,0.2621097954790097,153,2598,10033,0.501210979547901,2600 -exp_micro,74xf32,baseline,6986,9646,9643,0.0,0,222,889,0,0.12725450901803606,0.5457335788827502,1629,0,0,0.23318064700830232,0,0,1.0,1.0,1,7.6255506607929515,1629,0.45540956108470787,1948,1731,227,0.2788434010878901,153,2661,9650,0.5120240480961924,2663 -exp_micro,74xf64,baseline,7956,10528,10525,0.0,0,518,963,0,0.12104072398190045,0.4817408704352176,1999,0,0,0.2512569130216189,0,0,1.0,1.0,1,12.604651162790697,1999,0.48815628815628814,2096,3794,301,0.2634489693313223,153,2573,10532,0.5147058823529411,2575 -exp_micro,90xf16,baseline,9032,11629,11626,0.0,0,270,1261,0,0.1396147032772365,0.5835261453031004,2161,0,0,0.23926040744021257,0,0,1.0,1.0,1,7.621818181818182,2161,0.47756906077348066,2364,2096,275,0.26173604960141716,185,2598,11633,0.5009964570416298,2600 -exp_micro,90xf32,baseline,8490,11150,11147,0.0,0,270,1081,0,0.12732626619552415,0.5456839979808178,1981,0,0,0.23333333333333334,0,0,1.0,1.0,1,7.632727272727273,1981,0.45592635212888377,2364,2099,275,0.2784452296819788,185,2661,11154,0.5117785630153122,2663 -exp_micro,90xf64,baseline,9668,12240,12237,0.0,0,630,1171,0,0.12112122465866777,0.48169477581242287,2431,0,0,0.2514480761274307,0,0,1.0,1.0,1,12.63013698630137,2431,0.488643216080402,2544,4610,365,0.2631361191559785,185,2573,12244,0.5145841952834092,2575 +exp_micro,112xf16,baseline,11232,13857,13854,0.0,0,336,1569,0,0.13969017094017094,0.5834882856080327,2689,0,0,0.23940527065527065,0,0,1.0,1.0,1,7.6304985337243405,2689,0.47821447625822516,2934,2602,341,0.26121794871794873,229,2626,13861,0.5006232193732194,2628 +exp_micro,112xf16,linalg_xdsl_b-1,3474,5605,5601,0.0,0,0,673,0,0.19372481289579735,0.6656775469831849,1011,0,0,0.2910189982728843,0,0,1.0,1.0,1,0.0,1011,0.35838355193193905,1810,0,0,0.5210132412204951,672,2132,5609,0.8120322394933794,2134 +exp_micro,112xf16,linalg_xdsl_b0,3148,5259,5255,0.0,0,0,589,0,0.18710292249047014,0.6551724137931034,899,0,0,0.2855781448538755,0,0,1.0,1.0,1,0.0,899,0.35379771743408106,1642,0,0,0.5216010165184244,616,2112,5263,0.8071791613722998,2114 +exp_micro,112xf16,linalg_xdsl_b1,3148,5259,5255,0.0,0,0,589,0,0.18710292249047014,0.6551724137931034,899,0,0,0.2855781448538755,0,0,1.0,1.0,1,0.0,899,0.35379771743408106,1642,0,0,0.5216010165184244,616,2112,5263,0.8071791613722998,2114 +exp_micro,112xf16,linalg_xdsl_b10,2140,4265,4261,0.0,0,0,337,0,0.1574766355140187,0.5985790408525755,563,0,0,0.2630841121495327,0,0,1.0,1.0,1,0.0,563,0.33098177542621987,1138,0,0,0.5317757009345795,448,2126,4269,0.7948598130841122,2128 +exp_micro,112xf16,linalg_xdsl_b2,3148,5259,5255,0.0,0,0,589,0,0.18710292249047014,0.6551724137931034,899,0,0,0.2855781448538755,0,0,1.0,1.0,1,0.0,899,0.35379771743408106,1642,0,0,0.5216010165184244,616,2112,5263,0.8071791613722998,2114 +exp_micro,112xf16,linalg_xdsl_b3,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b4,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b5,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b6,2804,4952,4948,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0.0,787,0.34807607253427686,1474,0,0,0.5256776034236804,560,2149,4956,0.8063480741797432,2151 +exp_micro,112xf16,linalg_xdsl_b7,2466,4564,4560,0.0,0,0,421,0,0.17072181670721817,0.6237037037037036,675,0,0,0.2737226277372263,0,0,1.0,1.0,1,0.0,675,0.3407370015143867,1306,0,0,0.5296025952960259,504,2099,4568,0.8033252230332522,2101 +exp_micro,112xf16,linalg_xdsl_b8,2466,4564,4560,0.0,0,0,421,0,0.17072181670721817,0.6237037037037036,675,0,0,0.2737226277372263,0,0,1.0,1.0,1,0.0,675,0.3407370015143867,1306,0,0,0.5296025952960259,504,2099,4568,0.8033252230332522,2101 +exp_micro,112xf16,linalg_xdsl_b9,2466,4564,4560,0.0,0,0,421,0,0.17072181670721817,0.6237037037037036,675,0,0,0.2737226277372263,0,0,1.0,1.0,1,0.0,675,0.3407370015143867,1306,0,0,0.5296025952960259,504,2099,4568,0.8033252230332522,2101 +exp_micro,112xf32,baseline,10558,13171,13168,0.0,0,336,1345,0,0.12739155143019512,0.5456389452332657,2465,0,0,0.23347224853191892,0,0,1.0,1.0,1,7.639296187683285,2465,0.45656603074643454,2934,2605,341,0.27789354044326575,229,2614,13175,0.5113657889751847,2616 +exp_micro,112xf32,linalg_xdsl_b-1,8882,11032,11028,0.0,0,0,1849,0,0.20817383472190948,0.6871051653660349,2691,0,0,0.3029723035352398,0,0,1.0,1.0,1,0.0,2691,0.38024586689275114,4386,0,0,0.4938077009682504,1680,2151,11036,0.7967800045034902,2153 +exp_micro,112xf32,linalg_xdsl_b0,8882,11032,11028,0.0,0,0,1849,0,0.20817383472190948,0.6871051653660349,2691,0,0,0.3029723035352398,0,0,1.0,1.0,1,0.0,2691,0.38024586689275114,4386,0,0,0.4938077009682504,1680,2151,11036,0.7967800045034902,2153 +exp_micro,112xf32,linalg_xdsl_b1,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b10,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf32,linalg_xdsl_b11,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf32,linalg_xdsl_b12,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf32,linalg_xdsl_b13,6188,8286,8282,0.0,0,0,1177,0,0.19020685197155784,0.6557103064066853,1795,0,0,0.2900775694893342,0,0,1.0,1.0,1,0.0,1795,0.3710977878850527,3042,0,0,0.49159663865546216,1232,2099,8290,0.7816742081447964,2101 +exp_micro,112xf32,linalg_xdsl_b14,6188,8286,8282,0.0,0,0,1177,0,0.19020685197155784,0.6557103064066853,1795,0,0,0.2900775694893342,0,0,1.0,1.0,1,0.0,1795,0.3710977878850527,3042,0,0,0.49159663865546216,1232,2099,8290,0.7816742081447964,2101 +exp_micro,112xf32,linalg_xdsl_b15,6188,8286,8282,0.0,0,0,1177,0,0.19020685197155784,0.6557103064066853,1795,0,0,0.2900775694893342,0,0,1.0,1.0,1,0.0,1795,0.3710977878850527,3042,0,0,0.49159663865546216,1232,2099,8290,0.7816742081447964,2101 +exp_micro,112xf32,linalg_xdsl_b16,5526,7651,7647,0.0,0,0,1009,0,0.18259138617444806,0.642266072565245,1571,0,0,0.2842924357582338,0,0,1.0,1.0,1,0.0,1571,0.36731353752630347,2706,0,0,0.48968512486427795,1120,2126,7655,0.7739775606225118,2128 +exp_micro,112xf32,linalg_xdsl_b2,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b3,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b4,8204,10335,10331,0.0,0,0,1681,0,0.20490004875670403,0.6813944061613295,2467,0,0,0.3007069722086787,0,0,1.0,1.0,1,0.0,2467,0.3785484118459414,4050,0,0,0.49366162847391515,1568,2132,10339,0.7943686006825939,2134 +exp_micro,112xf32,linalg_xdsl_b5,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b6,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b7,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b8,7542,9653,9649,0.0,0,0,1513,0,0.20060991779368867,0.6745430227374053,2243,0,0,0.29740121983558737,0,0,1.0,1.0,1,0.0,2243,0.37653181131442,3714,0,0,0.492442322991249,1456,2112,9657,0.7898435428268364,2114 +exp_micro,112xf32,linalg_xdsl_b9,6862,9010,9006,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0.0,2019,0.37409672040022235,3378,0,0,0.49227630428446517,1344,2149,9014,0.7865053920139902,2151 +exp_micro,112xf64,baseline,12014,14649,14646,0.0,0,784,1457,0,0.12127517895788247,0.48165289256198346,3025,0,0,0.2517895788247045,0,0,1.0,1.0,1,12.653421633554084,3025,0.48924470321850233,3158,5732,453,0.26285999667055104,229,2636,14653,0.5146495754952556,2638 +exp_micro,112xf64,linalg_xdsl_b-1,23552,25693,25689,0.0,0,0,6273,0,0.2663468070652174,0.7776124953514317,8067,0,0,0.3425186820652174,0,0,1.0,1.0,1,0.0,8067,0.4158890550085065,11330,0,0,0.4810631793478261,3584,2142,25697,0.8235818614130435,2144 +exp_micro,112xf64,linalg_xdsl_b0,23552,25693,25689,0.0,0,0,6273,0,0.2663468070652174,0.7776124953514317,8067,0,0,0.3425186820652174,0,0,1.0,1.0,1,0.0,8067,0.4158890550085065,11330,0,0,0.4810631793478261,3584,2142,25697,0.8235818614130435,2144 +exp_micro,112xf64,linalg_xdsl_b1,23552,25693,25689,0.0,0,0,6273,0,0.2663468070652174,0.7776124953514317,8067,0,0,0.3425186820652174,0,0,1.0,1.0,1,0.0,8067,0.4158890550085065,11330,0,0,0.4810631793478261,3584,2142,25697,0.8235818614130435,2144 +exp_micro,112xf64,linalg_xdsl_b10,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b11,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b12,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b13,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b14,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b15,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b16,19299,21394,21390,0.0,0,0,5265,0,0.2728120628011814,0.7831325301204819,6723,0,0,0.3483600186538163,0,0,1.0,1.0,1,0.0,6723,0.4312656360254025,8866,0,0,0.45940204155655734,2912,2096,21398,0.8077620602103737,2098 +exp_micro,112xf64,linalg_xdsl_b2,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b3,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b4,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b5,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b6,22203,24339,24335,0.0,0,0,5937,0,0.26739629779759494,0.7792361202257514,7619,0,0,0.34315182632977526,0,0,1.0,1.0,1,0.0,7619,0.4168627236417355,10658,0,0,0.4800252218168716,3360,2137,24343,0.8231770481466468,2139 +exp_micro,112xf64,linalg_xdsl_b7,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b8,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,112xf64,linalg_xdsl_b9,20857,22971,22967,0.0,0,0,5601,0,0.26854293522558376,0.7810626133035838,7171,0,0,0.34381742340700966,0,0,1.0,1.0,1,0.0,7171,0.4179635134347497,9986,0,0,0.47878410126096754,3136,2115,22975,0.8226015246679772,2117 +exp_micro,128xf16,baseline,12832,15457,15454,0.0,0,384,1793,0,0.1397288029925187,0.5834689228766677,3073,0,0,0.2394794264339152,0,0,1.0,1.0,1,7.634961439588689,3073,0.4784368675073953,3350,2970,389,0.26106608478802995,261,2626,15461,0.5005455112219451,2628 +exp_micro,128xf16,linalg_xdsl_b-1,3966,6097,6093,0.0,0,0,769,0,0.19389813414019164,0.6658008658008658,1155,0,0,0.29122541603630864,0,0,1.0,1.0,1,0.0,1155,0.3585842905929835,2066,0,0,0.5209278870398386,768,2132,6101,0.8121533030761472,2134 +exp_micro,128xf16,linalg_xdsl_b0,3592,5703,5699,0.0,0,0,673,0,0.1873608017817372,0.6553067185978578,1027,0,0,0.285913140311804,0,0,1.0,1.0,1,0.0,1027,0.354015856601172,1874,0,0,0.5217149220489977,704,2112,5707,0.8076280623608016,2114 +exp_micro,128xf16,linalg_xdsl_b1,3592,5703,5699,0.0,0,0,673,0,0.1873608017817372,0.6553067185978578,1027,0,0,0.285913140311804,0,0,1.0,1.0,1,0.0,1027,0.354015856601172,1874,0,0,0.5217149220489977,704,2112,5707,0.8076280623608016,2114 +exp_micro,128xf16,linalg_xdsl_b10,2440,4565,4561,0.0,0,0,385,0,0.15778688524590165,0.5987558320373251,643,0,0,0.2635245901639344,0,0,1.0,1.0,1,0.0,643,0.33127253992787226,1298,0,0,0.5319672131147541,512,2126,4569,0.7954918032786886,2128 +exp_micro,128xf16,linalg_xdsl_b2,3592,5703,5699,0.0,0,0,673,0,0.1873608017817372,0.6553067185978578,1027,0,0,0.285913140311804,0,0,1.0,1.0,1,0.0,1027,0.354015856601172,1874,0,0,0.5217149220489977,704,2112,5707,0.8076280623608016,2114 +exp_micro,128xf16,linalg_xdsl_b3,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b4,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b5,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b6,3200,5348,5344,0.0,0,0,577,0,0.1803125,0.6418242491657397,899,0,0,0.2809375,0,0,1.0,1.0,1,0.0,899,0.34831460674157305,1682,0,0,0.525625,640,2149,5352,0.8065625000000001,2151 +exp_micro,128xf16,linalg_xdsl_b7,2814,4912,4908,0.0,0,0,481,0,0.17093105899076047,0.6238651102464332,771,0,0,0.27398720682302774,0,0,1.0,1.0,1,0.0,771,0.340999557717824,1490,0,0,0.5294953802416489,576,2099,4916,0.8034825870646767,2101 +exp_micro,128xf16,linalg_xdsl_b8,2814,4912,4908,0.0,0,0,481,0,0.17093105899076047,0.6238651102464332,771,0,0,0.27398720682302774,0,0,1.0,1.0,1,0.0,771,0.340999557717824,1490,0,0,0.5294953802416489,576,2099,4916,0.8034825870646767,2101 +exp_micro,128xf16,linalg_xdsl_b9,2814,4912,4908,0.0,0,0,481,0,0.17093105899076047,0.6238651102464332,771,0,0,0.27398720682302774,0,0,1.0,1.0,1,0.0,771,0.340999557717824,1490,0,0,0.5294953802416489,576,2099,4916,0.8034825870646767,2101 +exp_micro,128xf32,baseline,12062,14680,14677,0.0,0,384,1537,0,0.1274249709832532,0.5456159034433795,2817,0,0,0.23354335931023049,0,0,1.0,1.0,1,7.6426735218509,2817,0.45678611966920707,3350,2973,389,0.27773171944951086,261,2619,14684,0.5112750787597413,2621 +exp_micro,128xf32,linalg_xdsl_b-1,10146,12301,12297,0.0,0,0,2113,0,0.20825941257638478,0.6871544715447154,3075,0,0,0.30307510348905975,0,0,1.0,1.0,1,0.0,3075,0.3803339517625232,5010,0,0,0.4937906564163217,1920,2156,12305,0.7968657599053814,2158 +exp_micro,128xf32,linalg_xdsl_b0,10146,12301,12297,0.0,0,0,2113,0,0.20825941257638478,0.6871544715447154,3075,0,0,0.30307510348905975,0,0,1.0,1.0,1,0.0,3075,0.3803339517625232,5010,0,0,0.4937906564163217,1920,2156,12305,0.7968657599053814,2158 +exp_micro,128xf32,linalg_xdsl_b1,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b10,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf32,linalg_xdsl_b11,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf32,linalg_xdsl_b12,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf32,linalg_xdsl_b13,7068,9166,9162,0.0,0,0,1345,0,0.19029428409734012,0.6557776694295465,2051,0,0,0.29018109790605545,0,0,1.0,1.0,1,0.0,2051,0.3712217194570136,3474,0,0,0.49151103565365023,1408,2099,9170,0.7816921335597057,2101 +exp_micro,128xf32,linalg_xdsl_b14,7068,9166,9162,0.0,0,0,1345,0,0.19029428409734012,0.6557776694295465,2051,0,0,0.29018109790605545,0,0,1.0,1.0,1,0.0,2051,0.3712217194570136,3474,0,0,0.49151103565365023,1408,2099,9170,0.7816921335597057,2101 +exp_micro,128xf32,linalg_xdsl_b15,7068,9166,9162,0.0,0,0,1345,0,0.19029428409734012,0.6557776694295465,2051,0,0,0.29018109790605545,0,0,1.0,1.0,1,0.0,2051,0.3712217194570136,3474,0,0,0.49151103565365023,1408,2099,9170,0.7816921335597057,2101 +exp_micro,128xf32,linalg_xdsl_b16,6310,8440,8436,0.0,0,0,1153,0,0.18272583201267828,0.6423398328690808,1795,0,0,0.2844690966719493,0,0,1.0,1.0,1,0.0,1795,0.36745138178096215,3090,0,0,0.4896988906497623,1280,2131,8444,0.7741679873217115,2133 +exp_micro,128xf32,linalg_xdsl_b2,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b3,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b4,9372,11508,11504,0.0,0,0,1921,0,0.2049722577891592,0.6814473217452998,2819,0,0,0.3007895860008536,0,0,1.0,1.0,1,0.0,2819,0.3786433848220282,4626,0,0,0.49359795134443024,1792,2137,11512,0.7943875373452838,2139 +exp_micro,128xf32,linalg_xdsl_b5,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b6,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b7,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b8,8614,10730,10726,0.0,0,0,1729,0,0.2007197585326213,0.6746000780335544,2563,0,0,0.2975388901787787,0,0,1.0,1.0,1,0.0,2563,0.3766348273328435,4242,0,0,0.4924541444160669,1664,2117,10734,0.7899930345948456,2119 +exp_micro,128xf32,linalg_xdsl_b9,7838,9991,9987,0.0,0,0,1537,0,0.19609594284256188,0.6662332032943217,2307,0,0,0.2943352896146976,0,0,1.0,1.0,1,0.0,2307,0.37420924574209247,3858,0,0,0.4922174023985711,1536,2154,9995,0.7865526920132687,2156 +exp_micro,128xf64,baseline,13726,16361,16358,0.0,0,896,1665,0,0.12130263733061343,0.4816314723748915,3457,0,0,0.25185778813929766,0,0,1.0,1.0,1,12.665377176015474,3457,0.4894520741894379,3606,6548,517,0.262713099227743,261,2636,16365,0.5145708873670407,2638 +exp_micro,128xf64,linalg_xdsl_b-1,26912,29053,29049,0.0,0,0,7169,0,0.26638674197384066,0.7776331489315544,9219,0,0,0.34256093935790727,0,0,1.0,1.0,1,0.0,9219,0.41592600947439656,12946,0,0,0.48104934601664684,4096,2142,29057,0.8236102853745542,2144 +exp_micro,128xf64,linalg_xdsl_b0,26912,29053,29049,0.0,0,0,7169,0,0.26638674197384066,0.7776331489315544,9219,0,0,0.34256093935790727,0,0,1.0,1.0,1,0.0,9219,0.41592600947439656,12946,0,0,0.48104934601664684,4096,2142,29057,0.8236102853745542,2144 +exp_micro,128xf64,linalg_xdsl_b1,26912,29053,29049,0.0,0,0,7169,0,0.26638674197384066,0.7776331489315544,9219,0,0,0.34256093935790727,0,0,1.0,1.0,1,0.0,9219,0.41592600947439656,12946,0,0,0.48104934601664684,4096,2142,29057,0.8236102853745542,2144 +exp_micro,128xf64,linalg_xdsl_b10,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b11,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b12,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b13,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b14,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b15,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b16,22051,24146,24142,0.0,0,0,6017,0,0.27286744365334903,0.7831576207210725,7683,0,0,0.3484195728084894,0,0,1.0,1.0,1,0.0,7683,0.43131420872396564,10130,0,0,0.4593895968436806,3328,2096,24150,0.80780916965217,2098 +exp_micro,128xf64,linalg_xdsl_b2,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b3,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b4,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b5,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b6,25371,27507,27503,0.0,0,0,6785,0,0.2674313192227346,0.7792580682209717,8707,0,0,0.34318710338575537,0,0,1.0,1.0,1,0.0,8707,0.41690208283457025,12178,0,0,0.47999684679358323,3840,2137,27511,0.8231839501793385,2139 +exp_micro,128xf64,linalg_xdsl_b7,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b8,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,128xf64,linalg_xdsl_b9,23833,25947,25943,0.0,0,0,6401,0,0.2685771828976629,0.7810860280658939,8195,0,0,0.3438509629505308,0,0,1.0,1.0,1,0.0,8195,0.41800561081356796,11410,0,0,0.4787479545168464,3584,2115,25951,0.8225989174673771,2117 +exp_micro,16xf16,baseline,1628,4248,4245,0.0,0,48,225,0,0.1382063882063882,0.5844155844155844,385,0,0,0.23648648648648649,0,0,1.0,1.0,1,7.686274509803922,385,0.5112881806108898,368,392,51,0.22604422604422605,35,2621,4252,0.46253071253071254,2623 +exp_micro,16xf16,linalg_xdsl_b-1,522,2648,2644,0.0,0,0,97,0,0.18582375478927204,0.6598639455782312,147,0,0,0.28160919540229884,0,0,1.0,1.0,1,0.0,147,0.3491686460807601,274,0,0,0.524904214559387,96,2127,2652,0.8065134099616857,2129 +exp_micro,16xf16,linalg_xdsl_b0,484,2590,2586,0.0,0,0,85,0,0.1756198347107438,0.648854961832061,131,0,0,0.2706611570247934,0,0,1.0,1.0,1,0.0,131,0.3438320209973753,250,0,0,0.5165289256198347,88,2107,2594,0.7871900826446281,2109 +exp_micro,16xf16,linalg_xdsl_b1,484,2590,2586,0.0,0,0,85,0,0.1756198347107438,0.648854961832061,131,0,0,0.2706611570247934,0,0,1.0,1.0,1,0.0,131,0.3438320209973753,250,0,0,0.5165289256198347,88,2107,2594,0.7871900826446281,2109 +exp_micro,16xf16,linalg_xdsl_b10,340,2460,2456,0.0,0,0,49,0,0.14411764705882352,0.5903614457831325,83,0,0,0.24411764705882352,0,0,1.0,1.0,1,0.0,83,0.31800766283524906,178,0,0,0.5235294117647059,64,2121,2464,0.7676470588235295,2123 +exp_micro,16xf16,linalg_xdsl_b2,484,2590,2586,0.0,0,0,85,0,0.1756198347107438,0.648854961832061,131,0,0,0.2706611570247934,0,0,1.0,1.0,1,0.0,131,0.3438320209973753,250,0,0,0.5165289256198347,88,2107,2594,0.7871900826446281,2109 +exp_micro,16xf16,linalg_xdsl_b3,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b4,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b5,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b6,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf16,linalg_xdsl_b7,378,2471,2467,0.0,0,0,61,0,0.16137566137566137,0.6161616161616161,99,0,0,0.2619047619047619,0,0,1.0,1.0,1,0.0,99,0.3289036544850498,202,0,0,0.5343915343915344,72,2094,2475,0.7962962962962963,2096 +exp_micro,16xf16,linalg_xdsl_b8,378,2471,2467,0.0,0,0,61,0,0.16137566137566137,0.6161616161616161,99,0,0,0.2619047619047619,0,0,1.0,1.0,1,0.0,99,0.3289036544850498,202,0,0,0.5343915343915344,72,2094,2475,0.7962962962962963,2096 +exp_micro,16xf16,linalg_xdsl_b9,378,2471,2467,0.0,0,0,61,0,0.16137566137566137,0.6161616161616161,99,0,0,0.2619047619047619,0,0,1.0,1.0,1,0.0,99,0.3289036544850498,202,0,0,0.5343915343915344,72,2094,2475,0.7962962962962963,2096 +exp_micro,16xf32,baseline,1535,4155,4152,0.0,0,48,193,0,0.1257328990228013,0.546742209631728,353,0,0,0.22996742671009773,0,0,1.0,1.0,1,7.745098039215686,353,0.4895977808599168,368,395,51,0.23973941368078175,35,2621,4159,0.4697068403908795,2623 +exp_micro,16xf32,linalg_xdsl_b-1,1298,3443,3439,0.0,0,0,265,0,0.2041602465331279,0.6847545219638242,387,0,0,0.2981510015408321,0,0,1.0,1.0,1,0.0,387,0.3760932944606414,642,0,0,0.4946070878274268,240,2146,3447,0.7927580893682589,2148 +exp_micro,16xf32,linalg_xdsl_b0,1298,3443,3439,0.0,0,0,265,0,0.2041602465331279,0.6847545219638242,387,0,0,0.2981510015408321,0,0,1.0,1.0,1,0.0,387,0.3760932944606414,642,0,0,0.4946070878274268,240,2146,3447,0.7927580893682589,2148 +exp_micro,16xf32,linalg_xdsl_b1,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b10,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf32,linalg_xdsl_b11,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf32,linalg_xdsl_b12,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf32,linalg_xdsl_b13,908,3001,2997,0.0,0,0,169,0,0.18612334801762115,0.6525096525096525,259,0,0,0.2852422907488987,0,0,1.0,1.0,1,0.0,259,0.36530324400564174,450,0,0,0.4955947136563877,176,2094,3005,0.7808370044052864,2096 +exp_micro,16xf32,linalg_xdsl_b14,908,3001,2997,0.0,0,0,169,0,0.18612334801762115,0.6525096525096525,259,0,0,0.2852422907488987,0,0,1.0,1.0,1,0.0,259,0.36530324400564174,450,0,0,0.4955947136563877,176,2094,3005,0.7808370044052864,2096 +exp_micro,16xf32,linalg_xdsl_b15,908,3001,2997,0.0,0,0,169,0,0.18612334801762115,0.6525096525096525,259,0,0,0.2852422907488987,0,0,1.0,1.0,1,0.0,259,0.36530324400564174,450,0,0,0.4955947136563877,176,2094,3005,0.7808370044052864,2096 +exp_micro,16xf32,linalg_xdsl_b16,822,2942,2938,0.0,0,0,145,0,0.17639902676399027,0.6387665198237885,227,0,0,0.2761557177615572,0,0,1.0,1.0,1,0.0,227,0.36089030206677264,402,0,0,0.48905109489051096,160,2121,2946,0.7652068126520681,2123 +exp_micro,16xf32,linalg_xdsl_b2,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b3,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b4,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf32,linalg_xdsl_b5,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b6,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b7,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b8,1110,3216,3212,0.0,0,0,217,0,0.1954954954954955,0.6718266253869969,323,0,0,0.290990990990991,0,0,1.0,1.0,1,0.0,323,0.3716915995397008,546,0,0,0.4918918918918919,208,2107,3220,0.7828828828828829,2109 +exp_micro,16xf32,linalg_xdsl_b9,1006,3149,3145,0.0,0,0,193,0,0.1918489065606362,0.6632302405498282,291,0,0,0.28926441351888665,0,0,1.0,1.0,1,0.0,291,0.3688212927756654,498,0,0,0.49502982107355864,192,2144,3153,0.7842942345924453,2146 +exp_micro,16xf64,baseline,1750,4321,4318,0.0,0,112,209,0,0.11942857142857143,0.48267898383371827,433,0,0,0.24742857142857144,0,0,1.0,1.0,1,12.35820895522388,433,0.5198079231692677,400,828,67,0.22857142857142856,35,2572,4325,0.476,2574 +exp_micro,16xf64,linalg_xdsl_b-1,3392,5518,5514,0.0,0,0,897,0,0.2644457547169811,0.7766233766233767,1155,0,0,0.3405070754716981,0,0,1.0,1.0,1,0.0,1155,0.4141269272140552,1634,0,0,0.48172169811320753,512,2127,5522,0.8222287735849056,2129 +exp_micro,16xf64,linalg_xdsl_b0,3392,5518,5514,0.0,0,0,897,0,0.2644457547169811,0.7766233766233767,1155,0,0,0.3405070754716981,0,0,1.0,1.0,1,0.0,1155,0.4141269272140552,1634,0,0,0.48172169811320753,512,2127,5522,0.8222287735849056,2129 +exp_micro,16xf64,linalg_xdsl_b1,3392,5518,5514,0.0,0,0,897,0,0.2644457547169811,0.7766233766233767,1155,0,0,0.3405070754716981,0,0,1.0,1.0,1,0.0,1155,0.4141269272140552,1634,0,0,0.48172169811320753,512,2127,5522,0.8222287735849056,2129 +exp_micro,16xf64,linalg_xdsl_b10,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b11,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b12,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b13,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b14,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b15,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b16,2787,4867,4863,0.0,0,0,753,0,0.27018299246501615,0.7819314641744548,963,0,0,0.3455328310010764,0,0,1.0,1.0,1,0.0,963,0.4289532293986637,1282,0,0,0.4599928238249013,416,2081,4871,0.8055256548259777,2083 +exp_micro,16xf64,linalg_xdsl_b2,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b3,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b4,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b5,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b6,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,16xf64,linalg_xdsl_b7,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b8,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,16xf64,linalg_xdsl_b9,3001,5100,5096,0.0,0,0,801,0,0.2669110296567811,0.7799415774099319,1027,0,0,0.34221926024658444,0,0,1.0,1.0,1,0.0,1027,0.4159578776832726,1442,0,0,0.4805064978340553,448,2100,5104,0.8227257580806397,2102 +exp_micro,32xf16,baseline,3229,5849,5846,0.0,0,96,449,0,0.13905233818519666,0.5838751625487646,769,0,0,0.2381542273149582,0,0,1.0,1.0,1,7.6767676767676765,769,0.5164539959704499,720,760,99,0.22297925054196346,67,2621,5853,0.46113347785692166,2623 +exp_micro,32xf16,linalg_xdsl_b-1,1014,3140,3136,0.0,0,0,193,0,0.1903353057199211,0.6632302405498282,291,0,0,0.2869822485207101,0,0,1.0,1.0,1,0.0,291,0.35444579780755175,530,0,0,0.5226824457593688,192,2127,3144,0.8096646942800789,2129 +exp_micro,32xf16,linalg_xdsl_b0,928,3034,3030,0.0,0,0,169,0,0.18211206896551724,0.6525096525096525,259,0,0,0.2790948275862069,0,0,1.0,1.0,1,0.0,259,0.349527665317139,482,0,0,0.5193965517241379,176,2107,3038,0.7984913793103448,2109 +exp_micro,32xf16,linalg_xdsl_b1,928,3034,3030,0.0,0,0,169,0,0.18211206896551724,0.6525096525096525,259,0,0,0.2790948275862069,0,0,1.0,1.0,1,0.0,259,0.349527665317139,482,0,0,0.5193965517241379,176,2107,3038,0.7984913793103448,2109 +exp_micro,32xf16,linalg_xdsl_b10,640,2760,2756,0.0,0,0,97,0,0.1515625,0.5950920245398773,163,0,0,0.2546875,0,0,1.0,1.0,1,0.0,163,0.3253493013972056,338,0,0,0.528125,128,2121,2764,0.7828124999999999,2123 +exp_micro,32xf16,linalg_xdsl_b2,928,3034,3030,0.0,0,0,169,0,0.18211206896551724,0.6525096525096525,259,0,0,0.2790948275862069,0,0,1.0,1.0,1,0.0,259,0.349527665317139,482,0,0,0.5193965517241379,176,2107,3038,0.7984913793103448,2109 +exp_micro,32xf16,linalg_xdsl_b3,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b4,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b5,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b6,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf16,linalg_xdsl_b7,726,2819,2815,0.0,0,0,121,0,0.16666666666666666,0.6205128205128205,195,0,0,0.26859504132231404,0,0,1.0,1.0,1,0.0,195,0.33562822719449226,386,0,0,0.5316804407713499,144,2094,2823,0.800275482093664,2096 +exp_micro,32xf16,linalg_xdsl_b8,726,2819,2815,0.0,0,0,121,0,0.16666666666666666,0.6205128205128205,195,0,0,0.26859504132231404,0,0,1.0,1.0,1,0.0,195,0.33562822719449226,386,0,0,0.5316804407713499,144,2094,2823,0.800275482093664,2096 +exp_micro,32xf16,linalg_xdsl_b9,726,2819,2815,0.0,0,0,121,0,0.16666666666666666,0.6205128205128205,195,0,0,0.26859504132231404,0,0,1.0,1.0,1,0.0,195,0.33562822719449226,386,0,0,0.5316804407713499,144,2094,2823,0.800275482093664,2096 +exp_micro,32xf32,baseline,3039,5659,5656,0.0,0,96,385,0,0.12668641000329056,0.5460992907801419,705,0,0,0.23198420533070088,0,0,1.0,1.0,1,7.707070707070707,705,0.49473684210526314,720,763,99,0.23692003948667326,67,2621,5663,0.46890424481737414,2623 +exp_micro,32xf32,linalg_xdsl_b-1,2562,4707,4703,0.0,0,0,529,0,0.2064793130366901,0.6861219195849546,771,0,0,0.3009367681498829,0,0,1.0,1.0,1,0.0,771,0.3784977908689249,1266,0,0,0.49414519906323184,480,2146,4711,0.7950819672131147,2148 +exp_micro,32xf32,linalg_xdsl_b0,2562,4707,4703,0.0,0,0,529,0,0.2064793130366901,0.6861219195849546,771,0,0,0.3009367681498829,0,0,1.0,1.0,1,0.0,771,0.3784977908689249,1266,0,0,0.49414519906323184,480,2146,4711,0.7950819672131147,2148 +exp_micro,32xf32,linalg_xdsl_b1,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b10,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf32,linalg_xdsl_b11,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf32,linalg_xdsl_b12,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf32,linalg_xdsl_b13,1788,3881,3877,0.0,0,0,337,0,0.1884787472035794,0.654368932038835,515,0,0,0.28803131991051456,0,0,1.0,1.0,1,0.0,515,0.3686471009305655,882,0,0,0.49328859060402686,352,2094,3885,0.7813199105145414,2096 +exp_micro,32xf32,linalg_xdsl_b14,1788,3881,3877,0.0,0,0,337,0,0.1884787472035794,0.654368932038835,515,0,0,0.28803131991051456,0,0,1.0,1.0,1,0.0,515,0.3686471009305655,882,0,0,0.49328859060402686,352,2094,3885,0.7813199105145414,2096 +exp_micro,32xf32,linalg_xdsl_b15,1788,3881,3877,0.0,0,0,337,0,0.1884787472035794,0.654368932038835,515,0,0,0.28803131991051456,0,0,1.0,1.0,1,0.0,515,0.3686471009305655,882,0,0,0.49328859060402686,352,2094,3885,0.7813199105145414,2096 +exp_micro,32xf32,linalg_xdsl_b16,1606,3726,3722,0.0,0,0,289,0,0.17995018679950187,0.6407982261640798,451,0,0,0.2808219178082192,0,0,1.0,1.0,1,0.0,451,0.36459175424413903,786,0,0,0.48941469489414696,320,2121,3730,0.7702366127023661,2123 +exp_micro,32xf32,linalg_xdsl_b2,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b3,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b4,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf32,linalg_xdsl_b5,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b6,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b7,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b8,2182,4288,4284,0.0,0,0,433,0,0.19844179651695693,0.6734059097978227,643,0,0,0.2946837763519707,0,0,1.0,1.0,1,0.0,643,0.37449039021549213,1074,0,0,0.4922089825847846,416,2107,4292,0.7868927589367554,2109 +exp_micro,32xf32,linalg_xdsl_b9,1982,4125,4121,0.0,0,0,385,0,0.19424823410696265,0.6649395509499136,579,0,0,0.2921291624621594,0,0,1.0,1.0,1,0.0,579,0.371868978805395,978,0,0,0.4934409687184662,384,2144,4129,0.7855701311806256,2146 +exp_micro,32xf64,baseline,3463,6039,6036,0.0,0,224,417,0,0.12041582442968525,0.4820809248554913,865,0,0,0.2497834247762056,0,0,1.0,1.0,1,12.549618320610687,865,0.5245603395997575,784,1644,131,0.22639330060641064,67,2577,6043,0.47617672538261624,2579 +exp_micro,32xf64,linalg_xdsl_b-1,6752,8883,8879,0.0,0,0,1793,0,0.2655509478672986,0.777199826614651,2307,0,0,0.3416765402843602,0,0,1.0,1.0,1,0.0,2307,0.41515206046427927,3250,0,0,0.4813388625592417,1024,2132,8887,0.8230154028436019,2134 +exp_micro,32xf64,linalg_xdsl_b0,6752,8883,8879,0.0,0,0,1793,0,0.2655509478672986,0.777199826614651,2307,0,0,0.3416765402843602,0,0,1.0,1.0,1,0.0,2307,0.41515206046427927,3250,0,0,0.4813388625592417,1024,2132,8887,0.8230154028436019,2134 +exp_micro,32xf64,linalg_xdsl_b1,6752,8883,8879,0.0,0,0,1793,0,0.2655509478672986,0.777199826614651,2307,0,0,0.3416765402843602,0,0,1.0,1.0,1,0.0,2307,0.41515206046427927,3250,0,0,0.4813388625592417,1024,2132,8887,0.8230154028436019,2134 +exp_micro,32xf64,linalg_xdsl_b10,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b11,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b12,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b13,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b14,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b15,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b16,5539,7624,7620,0.0,0,0,1505,0,0.2717096948907745,0.7826313052522101,1923,0,0,0.34717458024914244,0,0,1.0,1.0,1,0.0,1923,0.43029760572835085,2546,0,0,0.4596497562736956,832,2086,7628,0.806824336522838,2088 +exp_micro,32xf64,linalg_xdsl_b2,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b3,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b4,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b5,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b6,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,32xf64,linalg_xdsl_b7,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b8,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,32xf64,linalg_xdsl_b9,5977,8081,8077,0.0,0,0,1601,0,0.267860130500251,0.7805948317893711,2051,0,0,0.34314873682449387,0,0,1.0,1.0,1,0.0,2051,0.41712426276184666,2866,0,0,0.47950476827840055,896,2105,8085,0.8226535051028945,2107 +exp_micro,48xf16,baseline,4832,7452,7449,0.0,0,144,673,0,0.13927980132450332,0.5836947094535994,1153,0,0,0.23861754966887416,0,0,1.0,1.0,1,7.583892617449664,1153,0.47585637639290135,1270,1130,149,0.2628311258278146,101,2621,7456,0.5014486754966887,2623 +exp_micro,48xf16,linalg_xdsl_b-1,1506,3632,3628,0.0,0,0,289,0,0.19189907038512616,0.664367816091954,435,0,0,0.28884462151394424,0,0,1.0,1.0,1,0.0,435,0.35626535626535627,786,0,0,0.5219123505976095,288,2127,3636,0.8107569721115537,2129 +exp_micro,48xf16,linalg_xdsl_b0,1372,3478,3474,0.0,0,0,253,0,0.18440233236151604,0.6537467700258398,387,0,0,0.2820699708454811,0,0,1.0,1.0,1,0.0,387,0.35149863760217986,714,0,0,0.5204081632653061,264,2107,3482,0.8024781341107872,2109 +exp_micro,48xf16,linalg_xdsl_b1,1372,3478,3474,0.0,0,0,253,0,0.18440233236151604,0.6537467700258398,387,0,0,0.2820699708454811,0,0,1.0,1.0,1,0.0,387,0.35149863760217986,714,0,0,0.5204081632653061,264,2107,3482,0.8024781341107872,2109 +exp_micro,48xf16,linalg_xdsl_b10,940,3060,3056,0.0,0,0,145,0,0.15425531914893617,0.5967078189300411,243,0,0,0.25851063829787235,0,0,1.0,1.0,1,0.0,243,0.32793522267206476,498,0,0,0.5297872340425532,192,2121,3064,0.7882978723404256,2123 +exp_micro,48xf16,linalg_xdsl_b2,1372,3478,3474,0.0,0,0,253,0,0.18440233236151604,0.6537467700258398,387,0,0,0.2820699708454811,0,0,1.0,1.0,1,0.0,387,0.35149863760217986,714,0,0,0.5204081632653061,264,2107,3482,0.8024781341107872,2109 +exp_micro,48xf16,linalg_xdsl_b3,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b4,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b5,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b6,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf16,linalg_xdsl_b7,1074,3167,3163,0.0,0,0,181,0,0.1685288640595903,0.6219931271477663,291,0,0,0.2709497206703911,0,0,1.0,1.0,1,0.0,291,0.33797909407665505,570,0,0,0.5307262569832403,216,2094,3171,0.8016759776536313,2096 +exp_micro,48xf16,linalg_xdsl_b8,1074,3167,3163,0.0,0,0,181,0,0.1685288640595903,0.6219931271477663,291,0,0,0.2709497206703911,0,0,1.0,1.0,1,0.0,291,0.33797909407665505,570,0,0,0.5307262569832403,216,2094,3171,0.8016759776536313,2096 +exp_micro,48xf16,linalg_xdsl_b9,1074,3167,3163,0.0,0,0,181,0,0.1685288640595903,0.6219931271477663,291,0,0,0.2709497206703911,0,0,1.0,1.0,1,0.0,291,0.33797909407665505,570,0,0,0.5307262569832403,216,2094,3171,0.8016759776536313,2096 +exp_micro,48xf32,baseline,4544,7169,7166,0.0,0,144,577,0,0.1269806338028169,0.5458845789971618,1057,0,0,0.2326144366197183,0,0,1.0,1.0,1,7.6938775510204085,1057,0.4964772193518084,1072,1131,147,0.23591549295774647,99,2626,7173,0.46852992957746475,2628 +exp_micro,48xf32,linalg_xdsl_b-1,3826,5976,5972,0.0,0,0,793,0,0.20726607422895976,0.6865800865800866,1155,0,0,0.30188186095138525,0,0,1.0,1.0,1,0.0,1155,0.3793103448275862,1890,0,0,0.4939884997386304,720,2151,5980,0.7958703606900157,2153 +exp_micro,48xf32,linalg_xdsl_b0,3826,5976,5972,0.0,0,0,793,0,0.20726607422895976,0.6865800865800866,1155,0,0,0.30188186095138525,0,0,1.0,1.0,1,0.0,1155,0.3793103448275862,1890,0,0,0.4939884997386304,720,2151,5980,0.7958703606900157,2153 +exp_micro,48xf32,linalg_xdsl_b1,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b10,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf32,linalg_xdsl_b11,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf32,linalg_xdsl_b12,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf32,linalg_xdsl_b13,2668,4761,4757,0.0,0,0,505,0,0.18928035982008995,0.6549935149156939,771,0,0,0.28898050974512746,0,0,1.0,1.0,1,0.0,771,0.3697841726618705,1314,0,0,0.49250374812593706,528,2094,4765,0.7814842578710646,2096 +exp_micro,48xf32,linalg_xdsl_b14,2668,4761,4757,0.0,0,0,505,0,0.18928035982008995,0.6549935149156939,771,0,0,0.28898050974512746,0,0,1.0,1.0,1,0.0,771,0.3697841726618705,1314,0,0,0.49250374812593706,528,2094,4765,0.7814842578710646,2096 +exp_micro,48xf32,linalg_xdsl_b15,2668,4761,4757,0.0,0,0,505,0,0.18928035982008995,0.6549935149156939,771,0,0,0.28898050974512746,0,0,1.0,1.0,1,0.0,771,0.3697841726618705,1314,0,0,0.49250374812593706,528,2094,4765,0.7814842578710646,2096 +exp_micro,48xf32,linalg_xdsl_b16,2390,4515,4511,0.0,0,0,433,0,0.1811715481171548,0.6414814814814814,675,0,0,0.2824267782426778,0,0,1.0,1.0,1,0.0,675,0.36585365853658536,1170,0,0,0.4895397489539749,480,2126,4519,0.7719665271966527,2128 +exp_micro,48xf32,linalg_xdsl_b2,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b3,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b4,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf32,linalg_xdsl_b5,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b6,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b7,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b8,3254,5365,5361,0.0,0,0,649,0,0.19944683466502766,0.6739356178608515,963,0,0,0.29594345421020285,0,0,1.0,1.0,1,0.0,963,0.37543859649122807,1602,0,0,0.49231714812538413,624,2112,5369,0.7882606023355869,2114 +exp_micro,48xf32,linalg_xdsl_b9,2958,5106,5102,0.0,0,0,577,0,0.19506423258958755,0.6655132641291811,867,0,0,0.29310344827586204,0,0,1.0,1.0,1,0.0,867,0.37290322580645163,1458,0,0,0.49290060851926976,576,2149,5110,0.7860040567951319,2151 +exp_micro,48xf64,baseline,5177,7754,7751,0.0,0,336,625,0,0.12072628935677034,0.4818812644564379,1297,0,0,0.2505311956731698,0,0,1.0,1.0,1,12.615384615384615,1297,0.5261663286004057,1168,2460,195,0.2256132895499324,99,2578,7758,0.47614448522310215,2580 +exp_micro,48xf64,linalg_xdsl_b-1,10112,12243,12239,0.0,0,0,2689,0,0.2659216772151899,0.7773923099161607,3459,0,0,0.34206882911392406,0,0,1.0,1.0,1,0.0,3459,0.41549549549549547,4866,0,0,0.48121044303797467,1536,2132,12247,0.8232792721518987,2134 +exp_micro,48xf64,linalg_xdsl_b0,10112,12243,12239,0.0,0,0,2689,0,0.2659216772151899,0.7773923099161607,3459,0,0,0.34206882911392406,0,0,1.0,1.0,1,0.0,3459,0.41549549549549547,4866,0,0,0.48121044303797467,1536,2132,12247,0.8232792721518987,2134 +exp_micro,48xf64,linalg_xdsl_b1,10112,12243,12239,0.0,0,0,2689,0,0.2659216772151899,0.7773923099161607,3459,0,0,0.34206882911392406,0,0,1.0,1.0,1,0.0,3459,0.41549549549549547,4866,0,0,0.48121044303797467,1536,2132,12247,0.8232792721518987,2134 +exp_micro,48xf64,linalg_xdsl_b10,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b11,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b12,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b13,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b14,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b15,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b16,8291,10376,10372,0.0,0,0,2257,0,0.2722228922928477,0.7828650711064863,2883,0,0,0.34772645036786876,0,0,1.0,1.0,1,0.0,2883,0.43074854325414613,3810,0,0,0.45953443492944157,1248,2086,10380,0.8072608852973103,2088 +exp_micro,48xf64,linalg_xdsl_b2,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b3,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b4,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b5,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b6,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,48xf64,linalg_xdsl_b7,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b8,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,48xf64,linalg_xdsl_b9,8953,11057,11053,0.0,0,0,2401,0,0.26817826426896013,0.7808130081300813,3075,0,0,0.34346029263933875,0,0,1.0,1.0,1,0.0,3075,0.4175152749490835,4290,0,0,0.47916899363341897,1344,2105,11061,0.8226292862727578,2107 +exp_micro,64xf16,baseline,6432,9052,9049,0.0,0,192,897,0,0.1394589552238806,0.5836044242029929,1537,0,0,0.23896144278606965,0,0,1.0,1.0,1,7.604060913705584,1537,0.47688488985417316,1686,1498,197,0.2621268656716418,133,2621,9056,0.5010883084577115,2623 +exp_micro,64xf16,linalg_xdsl_b-1,1998,4124,4120,0.0,0,0,385,0,0.19269269269269268,0.6649395509499136,579,0,0,0.2897897897897898,0,0,1.0,1.0,1,0.0,579,0.3571869216533004,1042,0,0,0.5215215215215215,384,2127,4128,0.8113113113113113,2129 +exp_micro,64xf16,linalg_xdsl_b0,1816,3922,3918,0.0,0,0,337,0,0.1855726872246696,0.654368932038835,515,0,0,0.28359030837004406,0,0,1.0,1.0,1,0.0,515,0.35249828884325807,946,0,0,0.5209251101321586,352,2107,3926,0.8045154185022027,2109 +exp_micro,64xf16,linalg_xdsl_b1,1816,3922,3918,0.0,0,0,337,0,0.1855726872246696,0.654368932038835,515,0,0,0.28359030837004406,0,0,1.0,1.0,1,0.0,515,0.35249828884325807,946,0,0,0.5209251101321586,352,2107,3926,0.8045154185022027,2109 +exp_micro,64xf16,linalg_xdsl_b10,1240,3360,3356,0.0,0,0,193,0,0.15564516129032258,0.5975232198142415,323,0,0,0.26048387096774195,0,0,1.0,1.0,1,0.0,323,0.3292558613659531,658,0,0,0.5306451612903226,256,2121,3364,0.7911290322580645,2123 +exp_micro,64xf16,linalg_xdsl_b2,1816,3922,3918,0.0,0,0,337,0,0.1855726872246696,0.654368932038835,515,0,0,0.28359030837004406,0,0,1.0,1.0,1,0.0,515,0.35249828884325807,946,0,0,0.5209251101321586,352,2107,3926,0.8045154185022027,2109 +exp_micro,64xf16,linalg_xdsl_b3,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b4,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b5,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b6,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf16,linalg_xdsl_b7,1422,3515,3511,0.0,0,0,241,0,0.16947960618846694,0.6227390180878553,387,0,0,0.2721518987341772,0,0,1.0,1.0,1,0.0,387,0.33917616126205086,754,0,0,0.530239099859353,288,2094,3519,0.8023909985935302,2096 +exp_micro,64xf16,linalg_xdsl_b8,1422,3515,3511,0.0,0,0,241,0,0.16947960618846694,0.6227390180878553,387,0,0,0.2721518987341772,0,0,1.0,1.0,1,0.0,387,0.33917616126205086,754,0,0,0.530239099859353,288,2094,3519,0.8023909985935302,2096 +exp_micro,64xf16,linalg_xdsl_b9,1422,3515,3511,0.0,0,0,241,0,0.16947960618846694,0.6227390180878553,387,0,0,0.2721518987341772,0,0,1.0,1.0,1,0.0,387,0.33917616126205086,754,0,0,0.530239099859353,288,2094,3519,0.8023909985935302,2096 +exp_micro,64xf32,baseline,6046,8659,8656,0.0,0,192,769,0,0.12719153159113464,0.5457771469127041,1409,0,0,0.23304664240820377,0,0,1.0,1.0,1,7.619289340101523,1409,0.4552504038772213,1686,1501,197,0.2788620575587165,133,2614,8663,0.5119086999669202,2616 +exp_micro,64xf32,linalg_xdsl_b-1,5090,7240,7236,0.0,0,0,1057,0,0.20766208251473478,0.686809616634178,1539,0,0,0.3023575638506876,0,0,1.0,1.0,1,0.0,1539,0.37971872686898595,2514,0,0,0.49390962671905697,960,2151,7244,0.7962671905697446,2153 +exp_micro,64xf32,linalg_xdsl_b0,5090,7240,7236,0.0,0,0,1057,0,0.20766208251473478,0.686809616634178,1539,0,0,0.3023575638506876,0,0,1.0,1.0,1,0.0,1539,0.37971872686898595,2514,0,0,0.49390962671905697,960,2151,7244,0.7962671905697446,2153 +exp_micro,64xf32,linalg_xdsl_b1,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b10,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf32,linalg_xdsl_b11,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf32,linalg_xdsl_b12,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf32,linalg_xdsl_b13,3548,5646,5642,0.0,0,0,673,0,0.18968432919954903,0.6553067185978578,1027,0,0,0.2894588500563698,0,0,1.0,1.0,1,0.0,1027,0.3703570140641904,1746,0,0,0.49210822998872605,704,2099,5650,0.7815670800450958,2101 +exp_micro,64xf32,linalg_xdsl_b14,3548,5646,5642,0.0,0,0,673,0,0.18968432919954903,0.6553067185978578,1027,0,0,0.2894588500563698,0,0,1.0,1.0,1,0.0,1027,0.3703570140641904,1746,0,0,0.49210822998872605,704,2099,5650,0.7815670800450958,2101 +exp_micro,64xf32,linalg_xdsl_b15,3548,5646,5642,0.0,0,0,673,0,0.18968432919954903,0.6553067185978578,1027,0,0,0.2894588500563698,0,0,1.0,1.0,1,0.0,1027,0.3703570140641904,1746,0,0,0.49210822998872605,704,2099,5650,0.7815670800450958,2101 +exp_micro,64xf32,linalg_xdsl_b16,3174,5299,5295,0.0,0,0,577,0,0.1817895400126024,0.6418242491657397,899,0,0,0.28323881537492124,0,0,1.0,1.0,1,0.0,899,0.36649001222992256,1554,0,0,0.4896030245746692,640,2126,5303,0.7728418399495904,2128 +exp_micro,64xf32,linalg_xdsl_b2,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b3,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b4,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf32,linalg_xdsl_b5,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b6,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b7,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b8,4326,6437,6433,0.0,0,0,865,0,0.19995376791493297,0.6742010911925176,1283,0,0,0.2965788257050393,0,0,1.0,1.0,1,0.0,1283,0.3759156167594492,2130,0,0,0.492371705963939,832,2112,6441,0.7889505316689782,2114 +exp_micro,64xf32,linalg_xdsl_b9,3934,6082,6078,0.0,0,0,769,0,0.1954753431621759,0.6658008658008658,1155,0,0,0.29359430604982206,0,0,1.0,1.0,1,0.0,1155,0.3734238603297769,1938,0,0,0.4926283680732079,768,2149,6086,0.78622267412303,2151 +exp_micro,64xf64,baseline,6878,9508,9505,0.0,0,448,833,0,0.1211107880197732,0.4817813765182186,1729,0,0,0.2513812154696133,0,0,1.0,1.0,1,12.582375478927203,1729,0.4880045159469376,1814,3284,261,0.26373945914510033,133,2631,9512,0.5151206746147137,2633 +exp_micro,64xf64,linalg_xdsl_b-1,13472,15608,15604,0.0,0,0,3585,0,0.26610748218527314,0.7774886141834743,4611,0,0,0.34226543942992876,0,0,1.0,1.0,1,0.0,4611,0.41566753808708196,6482,0,0,0.481146080760095,2048,2137,15612,0.8234115201900238,2139 +exp_micro,64xf64,linalg_xdsl_b0,13472,15608,15604,0.0,0,0,3585,0,0.26610748218527314,0.7774886141834743,4611,0,0,0.34226543942992876,0,0,1.0,1.0,1,0.0,4611,0.41566753808708196,6482,0,0,0.481146080760095,2048,2137,15612,0.8234115201900238,2139 +exp_micro,64xf64,linalg_xdsl_b1,13472,15608,15604,0.0,0,0,3585,0,0.26610748218527314,0.7774886141834743,4611,0,0,0.34226543942992876,0,0,1.0,1.0,1,0.0,4611,0.41566753808708196,6482,0,0,0.481146080760095,2048,2137,15612,0.8234115201900238,2139 +exp_micro,64xf64,linalg_xdsl_b10,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b11,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b12,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b13,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b14,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b15,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b16,11043,13133,13129,0.0,0,0,3009,0,0.27248030426514536,0.7829820452771272,3843,0,0,0.3480032599837001,0,0,1.0,1.0,1,0.0,3843,0.430974543007738,5074,0,0,0.45947659150593134,1664,2091,13137,0.8074798514896314,2093 +exp_micro,64xf64,linalg_xdsl_b2,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b3,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b4,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b5,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b6,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 +exp_micro,64xf64,linalg_xdsl_b7,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b8,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,64xf64,linalg_xdsl_b9,11929,14038,14034,0.0,0,0,3201,0,0.26833766451504737,0.7809221761405221,4099,0,0,0.3436163970156761,0,0,1.0,1.0,1,0.0,4099,0.41771119942932844,5714,0,0,0.4790007544639115,1792,2110,14042,0.8226171514795876,2112 +exp_micro,80xf16,baseline,8032,10657,10654,0.0,0,240,1121,0,0.13956673306772907,0.5835502342529932,1921,0,0,0.2391683266932271,0,0,1.0,1.0,1,7.616326530612245,1921,0.47750434998757146,2102,1866,245,0.261703187250996,165,2626,10661,0.5008715139442231,2628 +exp_micro,80xf16,linalg_xdsl_b-1,2490,4621,4617,0.0,0,0,481,0,0.1931726907630522,0.665283540802213,723,0,0,0.29036144578313255,0,0,1.0,1.0,1,0.0,723,0.3577436912419594,1298,0,0,0.521285140562249,480,2132,4625,0.8116465863453814,2134 +exp_micro,80xf16,linalg_xdsl_b0,2260,4371,4367,0.0,0,0,421,0,0.18628318584070797,0.6547433903576982,643,0,0,0.2845132743362832,0,0,1.0,1.0,1,0.0,643,0.3531026908292147,1178,0,0,0.5212389380530974,440,2112,4375,0.8057522123893806,2114 +exp_micro,80xf16,linalg_xdsl_b1,2260,4371,4367,0.0,0,0,421,0,0.18628318584070797,0.6547433903576982,643,0,0,0.2845132743362832,0,0,1.0,1.0,1,0.0,643,0.3531026908292147,1178,0,0,0.5212389380530974,440,2112,4375,0.8057522123893806,2114 +exp_micro,80xf16,linalg_xdsl_b10,1540,3665,3661,0.0,0,0,241,0,0.1564935064935065,0.598014888337469,403,0,0,0.2616883116883117,0,0,1.0,1.0,1,0.0,403,0.33005733005733007,818,0,0,0.5311688311688312,320,2126,3669,0.7928571428571429,2128 +exp_micro,80xf16,linalg_xdsl_b2,2260,4371,4367,0.0,0,0,421,0,0.18628318584070797,0.6547433903576982,643,0,0,0.2845132743362832,0,0,1.0,1.0,1,0.0,643,0.3531026908292147,1178,0,0,0.5212389380530974,440,2112,4375,0.8057522123893806,2114 +exp_micro,80xf16,linalg_xdsl_b3,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b4,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b5,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b6,2012,4160,4156,0.0,0,0,361,0,0.1794234592445328,0.6412078152753108,563,0,0,0.2798210735586481,0,0,1.0,1.0,1,0.0,563,0.3473164713140037,1058,0,0,0.525844930417495,400,2149,4164,0.8056660039761432,2151 +exp_micro,80xf16,linalg_xdsl_b7,1770,3863,3859,0.0,0,0,301,0,0.17005649717514124,0.6231884057971014,483,0,0,0.27288135593220336,0,0,1.0,1.0,1,0.0,483,0.3399014778325123,938,0,0,0.5299435028248588,360,2094,3867,0.8028248587570621,2096 +exp_micro,80xf16,linalg_xdsl_b8,1770,3863,3859,0.0,0,0,301,0,0.17005649717514124,0.6231884057971014,483,0,0,0.27288135593220336,0,0,1.0,1.0,1,0.0,483,0.3399014778325123,938,0,0,0.5299435028248588,360,2094,3867,0.8028248587570621,2096 +exp_micro,80xf16,linalg_xdsl_b9,1770,3863,3859,0.0,0,0,301,0,0.17005649717514124,0.6231884057971014,483,0,0,0.27288135593220336,0,0,1.0,1.0,1,0.0,483,0.3399014778325123,938,0,0,0.5299435028248588,360,2094,3867,0.8028248587570621,2096 +exp_micro,80xf32,baseline,7550,10163,10160,0.0,0,240,961,0,0.12728476821192053,0.5457126632595116,1761,0,0,0.2332450331125828,0,0,1.0,1.0,1,7.628571428571429,1761,0.45586331866425056,2102,1869,245,0.27841059602649004,165,2614,10167,0.5116556291390728,2616 +exp_micro,80xf32,linalg_xdsl_b-1,6354,8504,8500,0.0,0,0,1321,0,0.2079005350960025,0.6869474778991159,1923,0,0,0.30264400377714823,0,0,1.0,1.0,1,0.0,1923,0.3799644339063426,3138,0,0,0.493862134088763,1200,2151,8508,0.7965061378659113,2153 +exp_micro,80xf32,linalg_xdsl_b0,6354,8504,8500,0.0,0,0,1321,0,0.2079005350960025,0.6869474778991159,1923,0,0,0.30264400377714823,0,0,1.0,1.0,1,0.0,1923,0.3799644339063426,3138,0,0,0.493862134088763,1200,2151,8508,0.7965061378659113,2153 +exp_micro,80xf32,linalg_xdsl_b1,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b10,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf32,linalg_xdsl_b11,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf32,linalg_xdsl_b12,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf32,linalg_xdsl_b13,4428,6526,6522,0.0,0,0,841,0,0.18992773261065943,0.6554949337490257,1283,0,0,0.28974706413730805,0,0,1.0,1.0,1,0.0,1283,0.3707021092169893,2178,0,0,0.491869918699187,880,2099,6530,0.7816169828364951,2101 +exp_micro,80xf32,linalg_xdsl_b14,4428,6526,6522,0.0,0,0,841,0,0.18992773261065943,0.6554949337490257,1283,0,0,0.28974706413730805,0,0,1.0,1.0,1,0.0,1283,0.3707021092169893,2178,0,0,0.491869918699187,880,2099,6530,0.7816169828364951,2101 +exp_micro,80xf32,linalg_xdsl_b15,4428,6526,6522,0.0,0,0,841,0,0.18992773261065943,0.6554949337490257,1283,0,0,0.28974706413730805,0,0,1.0,1.0,1,0.0,1283,0.3707021092169893,2178,0,0,0.491869918699187,880,2099,6530,0.7816169828364951,2101 +exp_micro,80xf32,linalg_xdsl_b16,3958,6083,6079,0.0,0,0,721,0,0.18216270843860535,0.6420302760463046,1123,0,0,0.28372915613946437,0,0,1.0,1.0,1,0.0,1123,0.3668735707285201,1938,0,0,0.4896412329459323,800,2126,6087,0.7733703890853967,2128 +exp_micro,80xf32,linalg_xdsl_b2,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b3,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b4,5868,7999,7995,0.0,0,0,1201,0,0.20466939331970008,0.6812251843448667,1763,0,0,0.3004430811179277,0,0,1.0,1.0,1,0.0,1763,0.3782450118000429,2898,0,0,0.4938650306748466,1120,2132,8003,0.7943081117927744,2134 +exp_micro,80xf32,linalg_xdsl_b5,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b6,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b7,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b8,5398,7509,7505,0.0,0,0,1081,0,0.200259355316784,0.6743605739238927,1603,0,0,0.2969618377176732,0,0,1.0,1.0,1,0.0,1603,0.3762027693029805,2658,0,0,0.49240459429418304,1040,2112,7513,0.7893664320118563,2114 +exp_micro,80xf32,linalg_xdsl_b9,4910,7058,7054,0.0,0,0,961,0,0.19572301425661914,0.665973665973666,1443,0,0,0.2938900203665988,0,0,1.0,1.0,1,0.0,1443,0.37373737373737376,2418,0,0,0.4924643584521385,960,2149,7062,0.7863543788187373,2151 +exp_micro,80xf64,baseline,8590,11220,11217,0.0,0,560,1041,0,0.12118742724097788,0.4817214252660805,2161,0,0,0.25157159487776487,0,0,1.0,1.0,1,12.615384615384615,2161,0.4885824101288718,2262,4100,325,0.26332945285215364,165,2631,11224,0.5149010477299185,2633 +exp_micro,80xf64,linalg_xdsl_b-1,16832,18968,18964,0.0,0,0,4481,0,0.2662191064638783,0.7775464167968072,5763,0,0,0.34238355513307983,0,0,1.0,1.0,1,0.0,5763,0.4157708679027487,8098,0,0,0.4811074144486692,2560,2137,18972,0.823490969581749,2139 +exp_micro,80xf64,linalg_xdsl_b0,16832,18968,18964,0.0,0,0,4481,0,0.2662191064638783,0.7775464167968072,5763,0,0,0.34238355513307983,0,0,1.0,1.0,1,0.0,5763,0.4157708679027487,8098,0,0,0.4811074144486692,2560,2137,18972,0.823490969581749,2139 +exp_micro,80xf64,linalg_xdsl_b1,16832,18968,18964,0.0,0,0,4481,0,0.2662191064638783,0.7775464167968072,5763,0,0,0.34238355513307983,0,0,1.0,1.0,1,0.0,5763,0.4157708679027487,8098,0,0,0.4811074144486692,2560,2137,18972,0.823490969581749,2139 +exp_micro,80xf64,linalg_xdsl_b10,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b11,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b12,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b13,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b14,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b15,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b16,13795,15885,15881,0.0,0,0,3761,0,0.2726350126857557,0.7830522590047887,4803,0,0,0.348169626676332,0,0,1.0,1.0,1,0.0,4803,0.4311103132573378,6338,0,0,0.45944182674882206,2080,2091,15889,0.8076114534251541,2093 +exp_micro,80xf64,linalg_xdsl_b2,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b3,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b4,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b5,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b6,15867,17998,17994,0.0,0,0,4241,0,0.26728430074998427,0.7791659011574499,5443,0,0,0.3430390117854667,0,0,1.0,1.0,1,0.0,5443,0.4167368501646122,7618,0,0,0.4801159639503372,2400,2132,18002,0.8231549757358039,2134 +exp_micro,80xf64,linalg_xdsl_b7,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b8,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,80xf64,linalg_xdsl_b9,14905,17014,17010,0.0,0,0,4001,0,0.26843341160684336,0.7809877025180558,5123,0,0,0.343710164374371,0,0,1.0,1.0,1,0.0,5123,0.41782888834515947,7138,0,0,0.47889969808788996,2240,2110,17018,0.822609862462261,2112 +exp_micro,96xf16,baseline,9632,12257,12254,0.0,0,288,1345,0,0.13963870431893688,0.5835140997830802,2305,0,0,0.2393064784053156,0,0,1.0,1.0,1,7.624573378839591,2305,0.4779183081069874,2518,2234,293,0.2614202657807309,197,2626,12261,0.5007267441860466,2628 +exp_micro,96xf16,linalg_xdsl_b-1,2982,5113,5109,0.0,0,0,577,0,0.19349429912810195,0.6655132641291811,867,0,0,0.29074446680080485,0,0,1.0,1.0,1,0.0,867,0.35811648079306074,1554,0,0,0.5211267605633803,576,2132,5117,0.811871227364185,2134 +exp_micro,96xf16,linalg_xdsl_b0,2704,4815,4811,0.0,0,0,505,0,0.1867603550295858,0.6549935149156939,771,0,0,0.28513313609467456,0,0,1.0,1.0,1,0.0,771,0.3535075653370014,1410,0,0,0.5214497041420119,528,2112,4819,0.8065828402366864,2114 +exp_micro,96xf16,linalg_xdsl_b1,2704,4815,4811,0.0,0,0,505,0,0.1867603550295858,0.6549935149156939,771,0,0,0.28513313609467456,0,0,1.0,1.0,1,0.0,771,0.3535075653370014,1410,0,0,0.5214497041420119,528,2112,4819,0.8065828402366864,2114 +exp_micro,96xf16,linalg_xdsl_b10,1840,3965,3961,0.0,0,0,289,0,0.15706521739130436,0.598343685300207,483,0,0,0.2625,0,0,1.0,1.0,1,0.0,483,0.33059548254620125,978,0,0,0.5315217391304348,384,2126,3969,0.7940217391304347,2128 +exp_micro,96xf16,linalg_xdsl_b2,2704,4815,4811,0.0,0,0,505,0,0.1867603550295858,0.6549935149156939,771,0,0,0.28513313609467456,0,0,1.0,1.0,1,0.0,771,0.3535075653370014,1410,0,0,0.5214497041420119,528,2112,4819,0.8065828402366864,2114 +exp_micro,96xf16,linalg_xdsl_b3,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b4,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b5,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b6,2408,4556,4552,0.0,0,0,433,0,0.1798172757475083,0.6414814814814814,675,0,0,0.2803156146179402,0,0,1.0,1.0,1,0.0,675,0.34775888717156106,1266,0,0,0.5257475083056479,480,2149,4560,0.8060631229235881,2151 +exp_micro,96xf16,linalg_xdsl_b7,2118,4211,4207,0.0,0,0,361,0,0.1704438149197356,0.6234887737478411,579,0,0,0.273371104815864,0,0,1.0,1.0,1,0.0,579,0.3403880070546737,1122,0,0,0.5297450424929179,432,2094,4215,0.8031161473087819,2096 +exp_micro,96xf16,linalg_xdsl_b8,2118,4211,4207,0.0,0,0,361,0,0.1704438149197356,0.6234887737478411,579,0,0,0.273371104815864,0,0,1.0,1.0,1,0.0,579,0.3403880070546737,1122,0,0,0.5297450424929179,432,2094,4215,0.8031161473087819,2096 +exp_micro,96xf16,linalg_xdsl_b9,2118,4211,4207,0.0,0,0,361,0,0.1704438149197356,0.6234887737478411,579,0,0,0.273371104815864,0,0,1.0,1.0,1,0.0,579,0.3403880070546737,1122,0,0,0.5297450424929179,432,2094,4215,0.8031161473087819,2096 +exp_micro,96xf32,baseline,9054,11667,11664,0.0,0,288,1153,0,0.1273470289374862,0.5456696639848556,2113,0,0,0.23337751270156837,0,0,1.0,1.0,1,7.63481228668942,2113,0.4562729432088102,2518,2237,293,0.27810912303954055,197,2614,11671,0.511486635741109,2616 +exp_micro,96xf32,linalg_xdsl_b-1,7618,9768,9764,0.0,0,0,1585,0,0.20805985823050668,0.6870394451668834,2307,0,0,0.3028353898661066,0,0,1.0,1.0,1,0.0,2307,0.3801285219970341,3762,0,0,0.493830401680231,1440,2151,9772,0.7966657915463375,2153 +exp_micro,96xf32,linalg_xdsl_b0,7618,9768,9764,0.0,0,0,1585,0,0.20805985823050668,0.6870394451668834,2307,0,0,0.3028353898661066,0,0,1.0,1.0,1,0.0,2307,0.3801285219970341,3762,0,0,0.493830401680231,1440,2151,9772,0.7966657915463375,2153 +exp_micro,96xf32,linalg_xdsl_b1,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b10,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf32,linalg_xdsl_b11,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf32,linalg_xdsl_b12,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf32,linalg_xdsl_b13,5308,7406,7402,0.0,0,0,1009,0,0.1900904295403165,0.6556205328135153,1539,0,0,0.289939713639789,0,0,1.0,1.0,1,0.0,1539,0.37093275488069416,2610,0,0,0.4917106254709872,1056,2099,7410,0.7816503391107762,2101 +exp_micro,96xf32,linalg_xdsl_b14,5308,7406,7402,0.0,0,0,1009,0,0.1900904295403165,0.6556205328135153,1539,0,0,0.289939713639789,0,0,1.0,1.0,1,0.0,1539,0.37093275488069416,2610,0,0,0.4917106254709872,1056,2099,7410,0.7816503391107762,2101 +exp_micro,96xf32,linalg_xdsl_b15,5308,7406,7402,0.0,0,0,1009,0,0.1900904295403165,0.6556205328135153,1539,0,0,0.289939713639789,0,0,1.0,1.0,1,0.0,1539,0.37093275488069416,2610,0,0,0.4917106254709872,1056,2099,7410,0.7816503391107762,2101 +exp_micro,96xf32,linalg_xdsl_b16,4742,6867,6863,0.0,0,0,865,0,0.18241248418388867,0.6421677802524127,1347,0,0,0.28405735976381274,0,0,1.0,1.0,1,0.0,1347,0.3671300081766149,2322,0,0,0.48966680725432304,960,2126,6871,0.7737241670181358,2128 +exp_micro,96xf32,linalg_xdsl_b2,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b3,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b4,7036,9167,9163,0.0,0,0,1441,0,0.2048038658328596,0.6813238770685579,2115,0,0,0.30059693007390564,0,0,1.0,1.0,1,0.0,2115,0.3784219001610306,3474,0,0,0.4937464468447982,1344,2132,9171,0.7943433769187038,2134 +exp_micro,96xf32,linalg_xdsl_b5,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b6,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b7,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b8,6470,8581,8577,0.0,0,0,1297,0,0.20046367851622876,0.6744669786791472,1923,0,0,0.2972179289026275,0,0,1.0,1.0,1,0.0,1923,0.3763945977686436,3186,0,0,0.49242658423493046,1248,2112,8585,0.789644513137558,2114 +exp_micro,96xf32,linalg_xdsl_b9,5886,8034,8030,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0.0,1731,0.37394685677252104,2898,0,0,0.4923547400611621,1152,2149,8038,0.7864424057084607,2151 +exp_micro,96xf64,baseline,10302,12932,12929,0.0,0,672,1249,0,0.12123859444768006,0.48168145005784807,2593,0,0,0.25169869928169286,0,0,1.0,1.0,1,12.637532133676093,2593,0.48896850839147654,2710,4916,389,0.2630557173364395,197,2631,12936,0.5147544166181324,2633 +exp_micro,96xf64,linalg_xdsl_b-1,20192,22328,22324,0.0,0,0,5377,0,0.26629358161648176,0.777584960231381,6915,0,0,0.34246236133122027,0,0,1.0,1.0,1,0.0,6915,0.41583979794335196,9714,0,0,0.48108161648177494,3072,2137,22332,0.8235439778129952,2139 +exp_micro,96xf64,linalg_xdsl_b0,20192,22328,22324,0.0,0,0,5377,0,0.26629358161648176,0.777584960231381,6915,0,0,0.34246236133122027,0,0,1.0,1.0,1,0.0,6915,0.41583979794335196,9714,0,0,0.48108161648177494,3072,2137,22332,0.8235439778129952,2139 +exp_micro,96xf64,linalg_xdsl_b1,20192,22328,22324,0.0,0,0,5377,0,0.26629358161648176,0.777584960231381,6915,0,0,0.34246236133122027,0,0,1.0,1.0,1,0.0,6915,0.41583979794335196,9714,0,0,0.48108161648177494,3072,2137,22332,0.8235439778129952,2139 +exp_micro,96xf64,linalg_xdsl_b10,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b11,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b12,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b13,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b14,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b15,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b16,16547,18637,18633,0.0,0,0,4513,0,0.27273826071191154,0.7830990803401007,5763,0,0,0.34828065510364414,0,0,1.0,1.0,1,0.0,5763,0.43120089786756455,7602,0,0,0.4594186257327612,2496,2091,18641,0.8076992808364054,2093 +exp_micro,96xf64,linalg_xdsl_b2,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b3,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b4,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b5,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b6,19035,21166,21162,0.0,0,0,5089,0,0.26734961912266875,0.7792068595927116,6531,0,0,0.34310480693459416,0,0,1.0,1.0,1,0.0,6531,0.41681026230135937,9138,0,0,0.48006304176516945,2880,2132,21170,0.8231678486997636,2134 +exp_micro,96xf64,linalg_xdsl_b7,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b8,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 +exp_micro,96xf64,linalg_xdsl_b9,17881,19990,19986,0.0,0,0,4801,0,0.2684972876237347,0.7810313974296405,6147,0,0,0.3437727196465522,0,0,1.0,1.0,1,0.0,6147,0.41790740363043033,8562,0,0,0.4788322800738214,2688,2110,19994,0.8226049997203736,2112 fill,12x12xf64,baseline,201,2239,2236,0.0,0,0,1,0,0.004975124378109453,0.006896551724137931,145,0,0,0.7213930348258707,0,0,1.0,1.0,1,0.0,145,0.7671957671957672,44,0,0,0.21890547263681592,0,2039,2243,0.9402985074626866,2041 fill,12x12xf64,linalg,201,2239,2236,0.0,0,0,1,0,0.004975124378109453,0.006896551724137931,145,0,0,0.7213930348258707,0,0,1.0,1.0,1,0.0,145,0.7671957671957672,44,0,0,0.21890547263681592,0,2039,2243,0.9402985074626866,2041 fill,12x12xf64,linalg_xdsl,175,2200,2197,0.0,0,0,146,0,0.8342857142857143,0.9864864864864865,148,0,0,0.8457142857142858,0,0,24.666666666666664,24.666666666666668,1,0.0,6,0.3,14,0,0,0.08,0,2026,2204,0.9257142857142857,2028 @@ -190,65 +577,65 @@ fill,8x8xf64,baseline,75,2091,2088,0.0,0,0,1,0,0.013333333333333334,0.0153846153 fill,8x8xf64,linalg,75,2091,2088,0.0,0,0,1,0,0.013333333333333334,0.015384615384615385,65,0,0,0.8666666666666667,0,0,1.0,1.0,1,0.0,65,0.9154929577464789,6,0,0,0.08,0,2017,2095,0.9466666666666667,2019 fill,8x8xf64,linalg_xdsl,95,2120,2117,0.0,0,0,66,0,0.6947368421052632,0.9705882352941176,68,0,0,0.7157894736842105,0,0,11.333333333333334,11.333333333333334,1,0.0,6,0.3,14,0,0,0.14736842105263157,0,2026,2124,0.8631578947368421,2028 matmul,1x12x12xf64,baseline,821,2922,2919,0.0,0,132,145,0,0.17661388550548113,0.3258426966292135,445,0,0,0.5420219244823387,0,0,1.0,1.0,1,0.0,445,0.8864541832669323,57,0,0,0.06942752740560293,0,2102,2926,0.6114494518879416,2104 -matmul,1x12x12xf64,linalg_xdsl,228,2337,2334,0.0,0,144,170,0,0.7456140350877193,0.9883720930232558,172,0,0,0.7543859649122807,0,0,4.0,4.0,1,0.0,43,0.45263157894736844,52,0,0,0.22807017543859648,0,2110,2341,0.9824561403508771,2112 +matmul,1x12x12xf64,linalg_xdsl,224,2317,2314,0.0,0,144,170,0,0.7589285714285714,0.9883720930232558,172,0,0,0.7678571428571429,0,0,4.095238095238095,4.095238095238095,1,0.0,42,0.46153846153846156,49,0,0,0.21875,0,2094,2321,0.9866071428571429,2096 matmul,1x12x16xf64,baseline,1087,3181,3178,0.0,0,176,193,0,0.17755289788408463,0.3254637436762226,593,0,0,0.5455381784728611,0,0,1.0,1.0,1,0.0,593,0.8903903903903904,73,0,0,0.0671573137074517,0,2095,3185,0.6126954921803128,2097 matmul,1x12x16xf64,linalg_xdsl,286,2410,2407,0.0,0,192,226,0,0.7902097902097902,0.9912280701754386,228,0,0,0.7972027972027972,0,0,4.071428571428571,4.071428571428571,1,0.0,56,0.5045045045045045,55,0,0,0.19230769230769232,0,2125,2414,0.9895104895104895,2127 matmul,1x12x20xf64,baseline,1355,3463,3460,0.0,0,220,241,0,0.17785977859778598,0.3252361673414305,741,0,0,0.5468634686346864,0,0,1.0,1.0,1,0.0,741,0.8927710843373494,89,0,0,0.06568265682656826,0,2109,3467,0.6125461254612546,2111 -matmul,1x12x20xf64,linalg_xdsl,344,2460,2457,0.0,0,240,282,0,0.8197674418604651,0.9929577464788732,284,0,0,0.8255813953488372,0,0,4.115942028985508,4.115942028985507,1,0.0,69,0.5433070866141733,58,0,0,0.1686046511627907,0,2117,2464,0.9941860465116279,2119 +matmul,1x12x20xf64,linalg_xdsl,342,2454,2451,0.0,0,240,282,0,0.8245614035087719,0.9929577464788732,284,0,0,0.8304093567251462,0,0,4.176470588235294,4.176470588235294,1,0.0,68,0.5528455284552846,55,0,0,0.1608187134502924,0,2113,2458,0.9912280701754386,2115 matmul,1x12x24xf64,baseline,1639,3768,3765,0.0,0,264,289,0,0.17632702867602196,0.3250843644544432,889,0,0,0.5424039048200122,0,0,1.0,1.0,1,0.0,889,0.893467336683417,106,0,0,0.06467358145210494,0,2130,3772,0.6070774862721171,2132 -matmul,1x12x24xf64,linalg_xdsl,414,2565,2562,0.0,0,288,338,0,0.8164251207729468,0.9941176470588236,340,0,0,0.821256038647343,0,0,4.146341463414634,4.146341463414634,1,0.0,82,0.5655172413793104,63,0,0,0.15217391304347827,0,2152,2569,0.9734299516908212,2154 +matmul,1x12x24xf64,linalg_xdsl,414,2534,2531,0.0,0,288,338,0,0.8164251207729468,0.9941176470588236,340,0,0,0.821256038647343,0,0,4.249999999999999,4.25,1,0.0,80,0.583941605839416,57,0,0,0.13768115942028986,0,2121,2538,0.9589371980676329,2123 matmul,1x12x28xf64,baseline,1900,4034,4031,0.0,0,308,337,0,0.1773684210526316,0.32497589199614274,1037,0,0,0.5457894736842105,0,0,1.0,1.0,1,0.0,1037,0.8947368421052632,122,0,0,0.06421052631578947,0,2135,4038,0.61,2137 -matmul,1x12x28xf64,linalg_xdsl,484,2657,2654,0.0,0,336,394,0,0.8140495867768595,0.9949494949494949,396,0,0,0.8181818181818182,0,0,4.168421052631579,4.168421052631579,1,0.0,95,0.5900621118012422,66,0,0,0.13636363636363635,0,2174,2661,0.9545454545454546,2176 +matmul,1x12x28xf64,linalg_xdsl,476,2599,2596,0.0,0,336,394,0,0.8277310924369747,0.9949494949494949,396,0,0,0.8319327731092437,0,0,4.304347826086957,4.304347826086956,1,0.0,92,0.6174496644295302,57,0,0,0.11974789915966387,0,2124,2603,0.9516806722689076,2126 matmul,1x12x32xf64,baseline,2171,4306,4303,0.0,0,352,385,0,0.1773376324274528,0.32489451476793246,1185,0,0,0.5458314140948871,0,0,1.0,1.0,1,0.0,1185,0.8963691376701967,137,0,0,0.06310456011054813,0,2136,4310,0.6089359742054352,2138 matmul,1x12x32xf64,linalg_xdsl,524,2679,2676,0.0,0,384,450,0,0.8587786259541985,0.995575221238938,452,0,0,0.8625954198473282,0,0,4.185185185185185,4.185185185185185,1,0.0,108,0.6136363636363636,68,0,0,0.1297709923664122,0,2156,2683,0.9923664122137404,2158 matmul,1x12x36xf64,baseline,2439,4579,4576,0.0,0,396,433,0,0.1775317753177532,0.32483120780195046,1333,0,0,0.5465354653546536,0,0,1.0,1.0,1,0.0,1333,0.8970390309555855,153,0,0,0.06273062730627306,0,2141,4583,0.6092660926609267,2143 -matmul,1x12x36xf64,linalg_xdsl,582,2742,2739,0.0,0,432,506,0,0.8694158075601375,0.9960629921259843,508,0,0,0.872852233676976,0,0,4.198347107438017,4.198347107438017,1,0.0,121,0.6302083333333334,71,0,0,0.12199312714776632,0,2161,2746,0.9948453608247423,2163 +matmul,1x12x36xf64,linalg_xdsl,585,2702,2699,0.0,0,432,506,0,0.864957264957265,0.9960629921259843,508,0,0,0.8683760683760684,0,0,4.305084745762712,4.305084745762712,1,0.0,118,0.6555555555555556,62,0,0,0.10598290598290598,0,2118,2706,0.9743589743589743,2120 matmul,1x12x40xf64,baseline,2708,4858,4855,0.0,0,440,481,0,0.1776218611521418,0.32478055367994596,1481,0,0,0.5468980797636632,0,0,1.0,1.0,1,0.0,1481,0.8975757575757576,169,0,0,0.06240768094534712,0,2151,4862,0.6093057607090103,2153 -matmul,1x12x40xf64,linalg_xdsl,640,2810,2807,0.0,0,480,562,0,0.878125,0.9964539007092199,564,0,0,0.88125,0,0,4.208955223880596,4.208955223880597,1,0.0,134,0.6442307692307693,74,0,0,0.115625,0,2171,2814,0.996875,2173 +matmul,1x12x40xf64,linalg_xdsl,642,2792,2789,0.0,0,480,562,0,0.8753894080996885,0.9964539007092199,564,0,0,0.8785046728971962,0,0,4.2727272727272725,4.2727272727272725,1,0.0,132,0.66,68,0,0,0.1059190031152648,0,2151,2796,0.9844236760124611,2153 matmul,1x12x44xf64,baseline,2980,5146,5143,0.0,0,484,529,0,0.17751677852348993,0.3247391037446286,1629,0,0,0.5466442953020134,0,0,1.0,1.0,1,0.0,1629,0.8762775685852608,230,0,0,0.07718120805369127,0,2167,5150,0.6238255033557047,2169 matmul,1x12x44xf64,linalg_xdsl,698,2872,2869,0.0,0,528,618,0,0.8853868194842407,0.9967741935483871,620,0,0,0.8882521489971347,0,0,4.217687074829931,4.217687074829932,1,0.0,147,0.65625,77,0,0,0.11031518624641834,0,2175,2876,0.998567335243553,2177 matmul,1x12x48xf64,baseline,3248,5424,5421,0.0,0,528,577,0,0.17764778325123154,0.32470455824423183,1777,0,0,0.5471059113300493,0,0,1.0,1.0,1,0.0,1777,0.876665022200296,250,0,0,0.0769704433497537,0,2177,5428,0.6240763546798029,2179 -matmul,1x12x48xf64,linalg_xdsl,756,2940,2937,0.0,0,576,674,0,0.8915343915343915,0.9970414201183432,676,0,0,0.8941798941798942,0,0,4.2250000000000005,4.225,1,0.0,160,0.6666666666666666,80,0,0,0.10582010582010581,0,2185,2944,1.0,2187 +matmul,1x12x48xf64,linalg_xdsl,757,2894,2891,0.0,0,576,674,0,0.8903566710700133,0.9970414201183432,676,0,0,0.892998678996037,0,0,4.333333333333333,4.333333333333333,1,0.0,156,0.6964285714285714,68,0,0,0.08982826948480846,0,2138,2898,0.9828269484808455,2140 matmul,1x12x4xf64,baseline,286,2353,2350,0.0,0,44,49,0,0.17132867132867133,0.3288590604026846,149,0,0,0.5209790209790209,0,0,1.0,1.0,1,0.0,149,0.9612903225806452,6,0,0,0.02097902097902098,0,2068,2357,0.5419580419580419,2070 matmul,1x12x4xf64,linalg_xdsl,97,2191,2188,0.0,0,48,57,0,0.5876288659793815,0.9661016949152542,59,0,0,0.6082474226804123,0,0,3.6875,3.6875,1,0.0,16,0.34782608695652173,30,0,0,0.30927835051546393,0,2095,2195,0.9175257731958762,2097 matmul,1x12x52xf64,baseline,3516,5697,5694,0.0,0,572,625,0,0.17775881683731512,0.3246753246753247,1925,0,0,0.5474971558589306,0,0,1.0,1.0,1,0.0,1925,0.876993166287016,270,0,0,0.07679180887372014,0,2182,5701,0.6242889647326507,2184 matmul,1x12x52xf64,linalg_xdsl,814,3003,3000,0.0,0,624,730,0,0.8968058968058968,0.9972677595628415,732,0,0,0.8992628992628993,0,0,4.231213872832369,4.23121387283237,1,0.0,173,0.67578125,83,0,0,0.10196560196560196,0,2190,3007,1.0012285012285012,2192 matmul,1x12x56xf64,baseline,3784,5970,5967,0.0,0,616,673,0,0.17785412262156447,0.3246502653159672,2073,0,0,0.5478329809725159,0,0,1.0,1.0,1,0.0,2073,0.8772746508675413,290,0,0,0.07663847780126849,0,2187,5974,0.6244714587737844,2189 -matmul,1x12x56xf64,linalg_xdsl,872,3066,3063,0.0,0,672,786,0,0.9013761467889908,0.9974619289340102,788,0,0,0.9036697247706422,0,0,4.236559139784946,4.236559139784946,1,0.0,186,0.6838235294117647,86,0,0,0.09862385321100918,0,2195,3070,1.0022935779816513,2197 +matmul,1x12x56xf64,linalg_xdsl,861,3035,3032,0.0,0,672,786,0,0.9128919860627178,0.9974619289340102,788,0,0,0.9152148664343787,0,0,4.377777777777777,4.377777777777778,1,0.0,180,0.7258064516129032,68,0,0,0.07897793263646923,0,2175,3039,0.9941927990708479,2177 matmul,1x12x60xf64,baseline,4052,6243,6240,0.0,0,660,721,0,0.17793682132280356,0.32462854570013505,2221,0,0,0.5481243830207305,0,0,1.0,1.0,1,0.0,2221,0.8775187672856578,310,0,0,0.07650542941757157,0,2192,6247,0.6246298124383021,2194 -matmul,1x12x60xf64,linalg_xdsl,930,3129,3126,0.0,0,720,842,0,0.9053763440860215,0.9976303317535545,844,0,0,0.9075268817204301,0,0,4.241206030150754,4.241206030150754,1,0.0,199,0.6909722222222222,89,0,0,0.0956989247311828,0,2200,3133,1.0032258064516129,2202 +matmul,1x12x60xf64,linalg_xdsl,929,3086,3083,0.0,0,720,842,0,0.9063509149623251,0.9976303317535545,844,0,0,0.9085037674919269,0,0,4.350515463917525,4.350515463917525,1,0.0,194,0.7238805970149254,74,0,0,0.07965554359526372,0,2158,3090,0.9881593110871906,2160 matmul,1x12x64xf64,baseline,4320,6521,6518,0.0,0,704,769,0,0.17800925925925926,0.32460953989024904,2369,0,0,0.5483796296296296,0,0,1.0,1.0,1,0.0,2369,0.877732493516117,330,0,0,0.0763888888888889,0,2202,6525,0.6247685185185186,2204 matmul,1x12x64xf64,linalg_xdsl,988,3197,3194,0.0,0,768,898,0,0.9089068825910931,0.9977777777777778,900,0,0,0.9109311740890689,0,0,4.245283018867924,4.245283018867925,1,0.0,212,0.6973684210526315,92,0,0,0.0931174089068826,0,2210,3201,1.0040485829959516,2212 matmul,1x12x8xf64,baseline,551,2630,2627,0.0,0,88,97,0,0.17604355716878403,0.3265993265993266,297,0,0,0.5390199637023594,0,0,1.0,1.0,1,0.0,297,0.878698224852071,41,0,0,0.07441016333938294,0,2080,2634,0.6134301270417424,2082 matmul,1x12x8xf64,linalg_xdsl,170,2279,2276,0.0,0,96,114,0,0.6705882352941176,0.9827586206896551,116,0,0,0.6823529411764706,0,0,3.8666666666666667,3.8666666666666667,1,0.0,30,0.379746835443038,49,0,0,0.28823529411764703,0,2110,2283,0.9705882352941176,2112 matmul,1x16x12xf64,baseline,1073,3184,3181,0.0,0,180,193,0,0.1798695246971109,0.32767402376910015,589,0,0,0.548928238583411,0,0,1.0,1.0,1,0.0,589,0.9117647058823529,57,0,0,0.05312208760484623,0,2112,3188,0.6020503261882573,2114 -matmul,1x16x12xf64,linalg_xdsl,276,2387,2384,0.0,0,192,218,0,0.7898550724637681,0.990909090909091,220,0,0,0.7971014492753623,0,0,5.116279069767442,5.116279069767442,1,0.0,43,0.45263157894736844,52,0,0,0.18840579710144928,0,2112,2391,0.9855072463768115,2114 +matmul,1x16x12xf64,linalg_xdsl,272,2365,2362,0.0,0,192,218,0,0.8014705882352942,0.990909090909091,220,0,0,0.8088235294117647,0,0,5.238095238095238,5.238095238095238,1,0.0,42,0.46153846153846156,49,0,0,0.1801470588235294,0,2094,2369,0.9889705882352942,2096 matmul,1x16x16xf64,baseline,1430,3560,3557,0.0,0,240,257,0,0.1797202797202797,0.3273885350318471,785,0,0,0.548951048951049,0,0,1.0,1.0,1,0.0,785,0.9138533178114087,74,0,0,0.05174825174825175,0,2131,3564,0.6006993006993007,2133 matmul,1x16x16xf64,linalg_xdsl,355,2485,2482,0.0,0,256,290,0,0.8169014084507042,0.9931506849315068,292,0,0,0.8225352112676056,0,0,5.214285714285714,5.214285714285714,1,0.0,56,0.5,56,0,0,0.15774647887323945,0,2131,2489,0.9802816901408451,2133 matmul,1x16x20xf64,baseline,1788,3942,3939,0.0,0,300,321,0,0.17953020134228187,0.327217125382263,981,0,0,0.5486577181208053,0,0,1.0,1.0,1,0.0,981,0.9159663865546218,90,0,0,0.050335570469798654,0,2155,3946,0.598993288590604,2157 -matmul,1x16x20xf64,linalg_xdsl,430,2593,2590,0.0,0,320,362,0,0.8418604651162791,0.9945054945054945,364,0,0,0.8465116279069768,0,0,5.27536231884058,5.27536231884058,1,0.0,69,0.5348837209302325,60,0,0,0.13953488372093023,0,2164,2597,0.986046511627907,2166 +matmul,1x16x20xf64,linalg_xdsl,437,2565,2562,0.0,0,320,362,0,0.8283752860411899,0.9945054945054945,364,0,0,0.8329519450800915,0,0,5.352941176470588,5.352941176470588,1,0.0,68,0.544,57,0,0,0.13043478260869565,0,2129,2569,0.9633867276887872,2131 matmul,1x16x24xf64,baseline,2133,4297,4294,0.0,0,360,385,0,0.18049695264885138,0.32710280373831774,1177,0,0,0.5518049695264885,0,0,1.0,1.0,1,0.0,1177,0.9173811379579111,106,0,0,0.049695264885138306,0,2165,4301,0.6015002344116268,2167 -matmul,1x16x24xf64,linalg_xdsl,510,2671,2668,0.0,0,384,434,0,0.8509803921568627,0.9954128440366973,436,0,0,0.8549019607843137,0,0,5.317073170731708,5.317073170731708,1,0.0,82,0.5655172413793104,63,0,0,0.12352941176470589,0,2162,2675,0.9784313725490196,2164 +matmul,1x16x24xf64,linalg_xdsl,510,2640,2637,0.0,0,384,434,0,0.8509803921568627,0.9954128440366973,436,0,0,0.8549019607843137,0,0,5.449999999999999,5.45,1,0.0,80,0.583941605839416,57,0,0,0.11176470588235295,0,2131,2644,0.9666666666666667,2133 matmul,1x16x28xf64,baseline,2504,4682,4679,0.0,0,420,449,0,0.17931309904153356,0.32702112163146396,1373,0,0,0.5483226837060703,0,0,1.0,1.0,1,0.0,1373,0.9183946488294314,122,0,0,0.048722044728434506,0,2179,4686,0.5970447284345048,2181 -matmul,1x16x28xf64,linalg_xdsl,596,2784,2781,0.0,0,448,506,0,0.8489932885906041,0.9960629921259843,508,0,0,0.8523489932885906,0,0,5.347368421052631,5.347368421052631,1,0.0,95,0.5900621118012422,66,0,0,0.11073825503355705,0,2189,2788,0.9630872483221476,2191 +matmul,1x16x28xf64,linalg_xdsl,588,2726,2723,0.0,0,448,506,0,0.8605442176870748,0.9960629921259843,508,0,0,0.8639455782312925,0,0,5.521739130434782,5.521739130434782,1,0.0,92,0.6174496644295302,57,0,0,0.09693877551020408,0,2139,2730,0.9608843537414966,2141 matmul,1x16x32xf64,baseline,2838,5000,4997,0.0,0,480,513,0,0.18076109936575052,0.32695984703632885,1569,0,0,0.5528541226215645,0,0,1.0,1.0,1,0.0,1569,0.902242668200115,170,0,0,0.059901338971106416,0,2163,5004,0.6127554615926709,2165 matmul,1x16x32xf64,linalg_xdsl,652,2843,2840,0.0,0,512,578,0,0.8865030674846626,0.996551724137931,580,0,0,0.8895705521472392,0,0,5.37037037037037,5.37037037037037,1,0.0,108,0.6136363636363636,68,0,0,0.10429447852760736,0,2192,2847,0.9938650306748466,2194 matmul,1x16x36xf64,baseline,3190,5349,5346,0.0,0,540,577,0,0.18087774294670847,0.32691218130311617,1765,0,0,0.5532915360501567,0,0,1.0,1.0,1,0.0,1765,0.9028132992327366,190,0,0,0.05956112852664577,0,2160,5353,0.6128526645768024,2162 -matmul,1x16x36xf64,linalg_xdsl,726,2905,2902,0.0,0,576,650,0,0.8953168044077136,0.9969325153374233,652,0,0,0.8980716253443526,0,0,5.3884297520661155,5.3884297520661155,1,0.0,121,0.6302083333333334,71,0,0,0.09779614325068871,0,2180,2909,0.9958677685950413,2182 +matmul,1x16x36xf64,linalg_xdsl,729,2866,2863,0.0,0,576,650,0,0.8916323731138546,0.9969325153374233,652,0,0,0.8943758573388203,0,0,5.52542372881356,5.52542372881356,1,0.0,118,0.6555555555555556,62,0,0,0.0850480109739369,0,2138,2870,0.9794238683127572,2140 matmul,1x16x40xf64,baseline,3554,5721,5718,0.0,0,600,641,0,0.18036015756893642,0.32687404385517593,1961,0,0,0.5517726505346089,0,0,1.0,1.0,1,0.0,1961,0.886127428829643,252,0,0,0.07090602138435566,0,2168,5725,0.6226786719189645,2170 -matmul,1x16x40xf64,linalg_xdsl,800,2989,2986,0.0,0,640,722,0,0.9025,0.9972375690607734,724,0,0,0.905,0,0,5.402985074626866,5.402985074626866,1,0.0,134,0.6442307692307693,74,0,0,0.0925,0,2190,2993,0.9975,2192 +matmul,1x16x40xf64,linalg_xdsl,802,2968,2965,0.0,0,640,722,0,0.9002493765586035,0.9972375690607734,724,0,0,0.9027431421446384,0,0,5.484848484848485,5.484848484848484,1,0.0,132,0.66,68,0,0,0.08478802992518704,0,2167,2972,0.9875311720698254,2169 matmul,1x16x44xf64,baseline,3907,6098,6095,0.0,0,660,705,0,0.18044535449193755,0.32684283727399166,2157,0,0,0.5520859994880983,0,0,1.0,1.0,1,0.0,2157,0.8861955628594905,277,0,0,0.07089838750959816,0,2192,6102,0.6229843869976965,2194 matmul,1x16x44xf64,linalg_xdsl,874,3073,3070,0.0,0,704,794,0,0.9084668192219679,0.9974874371859297,796,0,0,0.9107551487414187,0,0,5.414965986394558,5.414965986394558,1,0.0,147,0.65625,77,0,0,0.08810068649885583,0,2200,3077,0.9988558352402745,2202 matmul,1x16x48xf64,baseline,4259,6455,6452,0.0,0,720,769,0,0.18055881662362055,0.3268168295792605,2353,0,0,0.5524771073021836,0,0,1.0,1.0,1,0.0,2353,0.886586284853052,301,0,0,0.07067386710495421,0,2197,6459,0.6231509744071377,2199 -matmul,1x16x48xf64,linalg_xdsl,948,3152,3149,0.0,0,768,866,0,0.9135021097046413,0.9976958525345622,868,0,0,0.9156118143459916,0,0,5.425,5.425,1,0.0,160,0.6666666666666666,80,0,0,0.08438818565400844,0,2205,3156,1.0,2207 +matmul,1x16x48xf64,linalg_xdsl,949,3111,3108,0.0,0,768,866,0,0.9125395152792413,0.9976958525345622,868,0,0,0.9146469968387777,0,0,5.564102564102564,5.564102564102564,1,0.0,156,0.6964285714285714,68,0,0,0.07165437302423604,0,2163,3115,0.9863013698630138,2165 matmul,1x16x4xf64,baseline,370,2437,2434,0.0,0,60,65,0,0.17567567567567569,0.3299492385786802,197,0,0,0.5324324324324324,0,0,1.0,1.0,1,0.0,197,0.9704433497536946,6,0,0,0.016216216216216217,0,2068,2441,0.5486486486486486,2070 matmul,1x16x4xf64,linalg_xdsl,113,2207,2204,0.0,0,64,73,0,0.6460176991150443,0.9733333333333334,75,0,0,0.6637168141592921,0,0,4.6875,4.6875,1,0.0,16,0.34782608695652173,30,0,0,0.26548672566371684,0,2095,2211,0.929203539823009,2097 matmul,1x16x52xf64,baseline,4606,6800,6797,0.0,0,780,833,0,0.18085106382978725,0.32679482149862693,2549,0,0,0.5534085974815458,0,0,1.0,1.0,1,0.0,2549,0.8702628883578013,380,0,0,0.08250108554059922,0,2195,6804,0.635909683022145,2197 matmul,1x16x52xf64,linalg_xdsl,1022,3236,3233,0.0,0,832,938,0,0.9178082191780822,0.997872340425532,940,0,0,0.9197651663405088,0,0,5.433526011560693,5.433526011560693,1,0.0,173,0.67578125,83,0,0,0.0812133072407045,0,2215,3240,1.0009784735812133,2217 matmul,1x16x56xf64,baseline,4958,7162,7159,0.0,0,840,897,0,0.1809197256958451,0.326775956284153,2745,0,0,0.5536506655909641,0,0,1.0,1.0,1,0.0,2745,0.8705994291151284,408,0,0,0.08229124647035095,0,2205,7166,0.635941912061315,2207 -matmul,1x16x56xf64,linalg_xdsl,1096,3320,3317,0.0,0,896,1010,0,0.9215328467153284,0.9980237154150198,1012,0,0,0.9233576642335767,0,0,5.440860215053763,5.440860215053763,1,0.0,186,0.6838235294117647,86,0,0,0.07846715328467153,0,2225,3324,1.0018248175182483,2227 +matmul,1x16x56xf64,linalg_xdsl,1085,3289,3286,0.0,0,896,1010,0,0.9308755760368663,0.9980237154150198,1012,0,0,0.9327188940092166,0,0,5.622222222222222,5.622222222222222,1,0.0,180,0.7258064516129032,68,0,0,0.06267281105990784,0,2205,3293,0.9953917050691244,2207 matmul,1x16x60xf64,baseline,5310,7524,7521,0.0,0,900,961,0,0.18097928436911487,0.3267596055763346,2941,0,0,0.5538606403013183,0,0,1.0,1.0,1,0.0,2941,0.8708913236600533,436,0,0,0.08210922787193974,0,2215,7528,0.6359698681732581,2217 -matmul,1x16x60xf64,linalg_xdsl,1170,3404,3401,0.0,0,960,1082,0,0.9247863247863248,0.9981549815498155,1084,0,0,0.9264957264957265,0,0,5.447236180904523,5.447236180904523,1,0.0,199,0.6909722222222222,89,0,0,0.07606837606837606,0,2235,3408,1.0025641025641026,2237 +matmul,1x16x60xf64,linalg_xdsl,1169,3356,3353,0.0,0,960,1082,0,0.9255774165953806,0.9981549815498155,1084,0,0,0.9272882805816938,0,0,5.587628865979381,5.587628865979381,1,0.0,194,0.7238805970149254,74,0,0,0.06330196749358426,0,2188,3360,0.9905902480752781,2190 matmul,1x16x64xf64,baseline,5662,7889,7886,0.0,0,960,1025,0,0.18103143765453902,0.326745298055467,3137,0,0,0.5540445072412575,0,0,1.0,1.0,1,0.0,3137,0.8557010365521004,529,0,0,0.09342988343341575,0,2228,7893,0.6474743906746733,2230 matmul,1x16x64xf64,linalg_xdsl,1244,3505,3502,0.0,0,1024,1154,0,0.927652733118971,0.9982698961937716,1156,0,0,0.9292604501607717,0,0,5.452830188679246,5.452830188679245,1,0.0,212,0.6973684210526315,92,0,0,0.07395498392282958,0,2262,3509,1.0032154340836013,2264 matmul,1x16x8xf64,baseline,721,2835,2832,0.0,0,120,129,0,0.17891816920943135,0.3282442748091603,393,0,0,0.5450762829403606,0,0,1.0,1.0,1,0.0,393,0.9055299539170507,41,0,0,0.056865464632454926,0,2115,2839,0.6019417475728155,2117 @@ -261,1473 +648,1473 @@ matmul,1x200x5xf64,linalg_4_xdsl,4080,6327,6324,0.0,0,1000,1012,0,0.248039215686 matmul,1x200x5xf64,linalg_5_xdsl,1056,3305,3302,0.0,0,1000,1011,0,0.9573863636363636,0.998025666337611,1013,0,0,0.959280303030303,0,0,53.31578947368421,53.31578947368421,1,0.0,19,0.38,31,0,0,0.029356060606060608,0,2250,3309,0.9886363636363635,2252 matmul,1x200x5xf64,linalg_xdsl,1056,3305,3302,0.0,0,1000,1011,0,0.9573863636363636,0.998025666337611,1013,0,0,0.959280303030303,0,0,53.31578947368421,53.31578947368421,1,0.0,19,0.38,31,0,0,0.029356060606060608,0,2250,3309,0.9886363636363635,2252 matmul,1x20x12xf64,baseline,1329,3441,3438,0.0,0,228,241,0,0.18133935289691497,0.32878581173260574,733,0,0,0.5515425131677953,0,0,1.0,1.0,1,0.0,733,0.9266750948166877,58,0,0,0.0436418359668924,0,2113,3445,0.5951843491346878,2115 -matmul,1x20x12xf64,linalg_xdsl,344,2488,2485,0.0,0,240,266,0,0.7732558139534884,0.9925373134328358,268,0,0,0.7790697674418605,0,0,6.232558139534884,6.232558139534884,1,0.0,43,0.4479166666666667,53,0,0,0.15406976744186046,0,2145,2492,0.933139534883721,2147 +matmul,1x20x12xf64,linalg_xdsl,337,2426,2423,0.0,0,240,266,0,0.7893175074183977,0.9925373134328358,268,0,0,0.7952522255192879,0,0,6.3809523809523805,6.380952380952381,1,0.0,42,0.45652173913043476,50,0,0,0.14836795252225518,0,2090,2430,0.9436201780415431,2092 matmul,1x20x16xf64,baseline,1771,3912,3909,0.0,0,304,321,0,0.18125352907961603,0.3285568065506653,977,0,0,0.551665725578769,0,0,1.0,1.0,1,0.0,977,0.9295908658420552,74,0,0,0.04178430265386787,0,2142,3916,0.5934500282326369,2144 matmul,1x20x16xf64,linalg_xdsl,435,2573,2570,0.0,0,320,354,0,0.8137931034482758,0.9943820224719101,356,0,0,0.8183908045977012,0,0,6.357142857142857,6.357142857142857,1,0.0,56,0.49557522123893805,57,0,0,0.1310344827586207,0,2139,2577,0.9494252873563219,2141 matmul,1x20x20xf64,baseline,2202,4344,4341,0.0,0,380,401,0,0.1821071752951862,0.3284193284193284,1221,0,0,0.5544959128065395,0,0,1.0,1.0,1,0.0,1221,0.931350114416476,90,0,0,0.04087193460490463,0,2143,4348,0.5953678474114442,2145 -matmul,1x20x20xf64,linalg_xdsl,516,2679,2676,0.0,0,400,442,0,0.8565891472868217,0.9954954954954955,444,0,0,0.8604651162790697,0,0,6.434782608695652,6.434782608695652,1,0.0,69,0.5348837209302325,60,0,0,0.11627906976744186,0,2164,2683,0.9767441860465116,2166 +matmul,1x20x20xf64,linalg_xdsl,517,2646,2643,0.0,0,400,442,0,0.8549323017408124,0.9954954954954955,444,0,0,0.8588007736943907,0,0,6.529411764705882,6.529411764705882,1,0.0,68,0.544,57,0,0,0.1102514506769826,0,2130,2650,0.9690522243713733,2132 matmul,1x20x24xf64,baseline,2653,4794,4791,0.0,0,456,481,0,0.18130418394270637,0.32832764505119455,1465,0,0,0.5522050508857896,0,0,1.0,1.0,1,0.0,1465,0.9325270528325907,106,0,0,0.03995476818695816,0,2142,4798,0.5921598190727478,2144 -matmul,1x20x24xf64,linalg_xdsl,600,2750,2747,0.0,0,480,530,0,0.8833333333333333,0.9962406015037594,532,0,0,0.8866666666666667,0,0,6.487804878048781,6.487804878048781,1,0.0,82,0.5655172413793104,63,0,0,0.105,0,2151,2754,0.9916666666666667,2153 +matmul,1x20x24xf64,linalg_xdsl,598,2742,2739,0.0,0,480,530,0,0.8862876254180602,0.9962406015037594,532,0,0,0.8896321070234113,0,0,6.65,6.65,1,0.0,80,0.583941605839416,57,0,0,0.09531772575250837,0,2145,2746,0.9849498327759197,2147 matmul,1x20x28xf64,baseline,3090,5242,5239,0.0,0,532,561,0,0.18155339805825244,0.32826214160327677,1709,0,0,0.553074433656958,0,0,1.0,1.0,1,0.0,1709,0.9188172043010753,151,0,0,0.04886731391585761,0,2153,5246,0.6019417475728156,2155 -matmul,1x20x28xf64,linalg_xdsl,696,2838,2835,0.0,0,560,618,0,0.8879310344827587,0.9967741935483871,620,0,0,0.8908045977011494,0,0,6.526315789473684,6.526315789473684,1,0.0,95,0.5900621118012422,66,0,0,0.09482758620689655,0,2143,2842,0.985632183908046,2145 +matmul,1x20x28xf64,linalg_xdsl,700,2874,2871,0.0,0,560,618,0,0.8828571428571429,0.9967741935483871,620,0,0,0.8857142857142857,0,0,6.739130434782608,6.739130434782608,1,0.0,92,0.6174496644295302,57,0,0,0.08142857142857143,0,2175,2878,0.9671428571428571,2177 matmul,1x20x32xf64,baseline,3513,5702,5699,0.0,0,608,641,0,0.18246512951892968,0.32821300563236044,1953,0,0,0.555935098206661,0,0,1.0,1.0,1,0.0,1953,0.9054242002781642,204,0,0,0.05807002561912895,0,2190,5706,0.61400512382579,2192 matmul,1x20x32xf64,linalg_xdsl,780,2969,2966,0.0,0,640,706,0,0.9051282051282051,0.9971751412429378,708,0,0,0.9076923076923077,0,0,6.555555555555556,6.555555555555555,1,0.0,108,0.6136363636363636,68,0,0,0.08717948717948718,0,2190,2973,0.9948717948717949,2192 matmul,1x20x36xf64,baseline,3949,6128,6125,0.0,0,684,721,0,0.1825778678146366,0.32817478379608556,2197,0,0,0.5563433780703976,0,0,1.0,1.0,1,0.0,2197,0.90560593569662,229,0,0,0.05798936439604963,0,2180,6132,0.6143327424664472,2182 -matmul,1x20x36xf64,linalg_xdsl,870,3069,3066,0.0,0,720,794,0,0.9126436781609195,0.9974874371859297,796,0,0,0.9149425287356322,0,0,6.578512396694214,6.578512396694215,1,0.0,121,0.6302083333333334,71,0,0,0.08160919540229886,0,2200,3073,0.996551724137931,2202 +matmul,1x20x36xf64,linalg_xdsl,873,3030,3027,0.0,0,720,794,0,0.9095074455899198,0.9974874371859297,796,0,0,0.9117983963344788,0,0,6.745762711864407,6.745762711864407,1,0.0,118,0.6555555555555556,62,0,0,0.07101947308132875,0,2158,3034,0.9828178694158075,2160 matmul,1x20x40xf64,baseline,4382,6591,6588,0.0,0,760,801,0,0.1827932450935646,0.3281442031954117,2441,0,0,0.5570515746234596,0,0,1.0,1.0,1,0.0,2441,0.9211320754716981,209,0,0,0.04769511638521223,0,2210,6595,0.6047466910086718,2212 -matmul,1x20x40xf64,linalg_xdsl,960,3169,3166,0.0,0,800,882,0,0.91875,0.997737556561086,884,0,0,0.9208333333333333,0,0,6.597014925373134,6.597014925373134,1,0.0,134,0.6442307692307693,74,0,0,0.07708333333333334,0,2210,3173,0.9979166666666666,2212 +matmul,1x20x40xf64,linalg_xdsl,962,3148,3145,0.0,0,800,882,0,0.9168399168399168,0.997737556561086,884,0,0,0.918918918918919,0,0,6.696969696969696,6.696969696969697,1,0.0,132,0.66,68,0,0,0.07068607068607069,0,2187,3152,0.9896049896049897,2189 matmul,1x20x44xf64,baseline,4834,7045,7042,0.0,0,836,881,0,0.18225072403806372,0.3281191806331471,2685,0,0,0.5554406288787753,0,0,1.0,1.0,1,0.0,2685,0.8923230309072782,324,0,0,0.06702523789822093,0,2212,7049,0.6224658667769962,2214 matmul,1x20x44xf64,linalg_xdsl,1051,3270,3267,0.0,0,880,970,0,0.922930542340628,0.9979423868312757,972,0,0,0.9248334919124643,0,0,6.612244897959184,6.612244897959184,1,0.0,147,0.65625,77,0,0,0.07326355851569934,0,2220,3274,0.9980970504281637,2222 matmul,1x20x48xf64,baseline,5270,7496,7493,0.0,0,912,961,0,0.18235294117647058,0.3280983270740867,2929,0,0,0.5557874762808349,0,0,1.0,1.0,1,0.0,2929,0.8927156354769887,352,0,0,0.0667931688804554,0,2227,7500,0.6225806451612903,2229 -matmul,1x20x48xf64,linalg_xdsl,1140,3374,3371,0.0,0,960,1058,0,0.9280701754385965,0.9981132075471698,1060,0,0,0.9298245614035088,0,0,6.625,6.625,1,0.0,160,0.6666666666666666,80,0,0,0.07017543859649122,0,2235,3378,1.0,2237 +matmul,1x20x48xf64,linalg_xdsl,1141,3328,3325,0.0,0,960,1058,0,0.9272567922874672,0.9981132075471698,1060,0,0,0.9290096406660824,0,0,6.794871794871795,6.794871794871795,1,0.0,156,0.6964285714285714,68,0,0,0.05959684487291849,0,2188,3332,0.9886064855390009,2190 matmul,1x20x4xf64,baseline,458,2530,2527,0.0,0,76,81,0,0.17685589519650655,0.3306122448979592,245,0,0,0.5349344978165939,0,0,1.0,1.0,1,0.0,245,0.9074074074074074,25,0,0,0.05458515283842795,0,2073,2534,0.5895196506550218,2075 matmul,1x20x4xf64,linalg_xdsl,129,2228,2225,0.0,0,80,89,0,0.689922480620155,0.978021978021978,91,0,0,0.7054263565891473,0,0,5.6875,5.6875,1,0.0,16,0.34782608695652173,30,0,0,0.23255813953488372,0,2100,2232,0.937984496124031,2102 matmul,1x20x52xf64,baseline,5701,7904,7901,0.0,0,988,1041,0,0.18259954393965971,0.3280806807437756,3173,0,0,0.5565690229784248,0,0,1.0,1.0,1,0.0,3173,0.8667030865883638,488,0,0,0.08559901771619015,0,2204,7908,0.642168040694615,2206 matmul,1x20x52xf64,linalg_xdsl,1230,3474,3471,0.0,0,1040,1146,0,0.9317073170731708,0.9982578397212544,1148,0,0,0.9333333333333333,0,0,6.635838150289017,6.635838150289017,1,0.0,173,0.67578125,83,0,0,0.06747967479674796,0,2245,3478,1.0008130081300812,2247 matmul,1x20x56xf64,baseline,6137,8350,8347,0.0,0,1064,1121,0,0.1826625386996904,0.328065554580041,3417,0,0,0.556786703601108,0,0,1.0,1.0,1,0.0,3417,0.8670388226338492,524,0,0,0.08538373798272772,0,2214,8354,0.6421704415838357,2216 -matmul,1x20x56xf64,linalg_xdsl,1320,3574,3571,0.0,0,1120,1234,0,0.9348484848484848,0.9983818770226537,1236,0,0,0.9363636363636364,0,0,6.645161290322581,6.645161290322581,1,0.0,186,0.6838235294117647,86,0,0,0.06515151515151515,0,2255,3578,1.0015151515151515,2257 +matmul,1x20x56xf64,linalg_xdsl,1309,3543,3540,0.0,0,1120,1234,0,0.9427043544690603,0.9983818770226537,1236,0,0,0.9442322383498855,0,0,6.866666666666666,6.866666666666666,1,0.0,180,0.7258064516129032,68,0,0,0.05194805194805195,0,2235,3547,0.9961802902979374,2237 matmul,1x20x60xf64,baseline,6573,8796,8793,0.0,0,1140,1201,0,0.18271717632739998,0.3280524446872439,3661,0,0,0.556975505857295,0,0,1.0,1.0,1,0.0,3661,0.867330016583748,560,0,0,0.08519701810436635,0,2224,8800,0.6421725239616614,2226 -matmul,1x20x60xf64,linalg_xdsl,1410,3674,3671,0.0,0,1200,1322,0,0.9375886524822695,0.9984894259818731,1324,0,0,0.9390070921985816,0,0,6.653266331658292,6.653266331658291,1,0.0,199,0.6909722222222222,89,0,0,0.06312056737588652,0,2265,3678,1.0021276595744681,2267 +matmul,1x20x60xf64,linalg_xdsl,1409,3631,3628,0.0,0,1200,1322,0,0.9382540809084458,0.9984894259818731,1324,0,0,0.9396735273243435,0,0,6.824742268041237,6.824742268041237,1,0.0,194,0.7238805970149254,74,0,0,0.0525195173882186,0,2223,3635,0.9921930447125621,2225 matmul,1x20x64xf64,baseline,7012,9266,9263,0.0,0,1216,1281,0,0.18268682258984598,0.32804097311139563,3905,0,0,0.5569024529378209,0,0,1.0,1.0,1,0.0,3905,0.8428663932657026,728,0,0,0.1038220193953223,0,2255,9270,0.6607244723331432,2257 matmul,1x20x64xf64,linalg_xdsl,1500,3774,3771,0.0,0,1280,1410,0,0.94,0.9985835694050992,1412,0,0,0.9413333333333334,0,0,6.660377358490566,6.660377358490566,1,0.0,212,0.6973684210526315,92,0,0,0.06133333333333333,0,2275,3778,1.0026666666666666,2277 matmul,1x20x8xf64,baseline,894,2985,2982,0.0,0,152,161,0,0.18008948545861297,0.3292433537832311,489,0,0,0.5469798657718121,0,0,1.0,1.0,1,0.0,489,0.9226415094339623,41,0,0,0.04586129753914989,0,2092,2989,0.592841163310962,2094 matmul,1x20x8xf64,linalg_xdsl,234,2353,2350,0.0,0,160,178,0,0.7606837606837606,0.9888888888888889,180,0,0,0.7692307692307693,0,0,6.0,6.0,1,0.0,30,0.379746835443038,49,0,0,0.2094017094017094,0,2120,2357,0.9786324786324787,2122 matmul,1x24x12xf64,baseline,1592,3722,3719,0.0,0,276,289,0,0.1815326633165829,0.3295324971493729,877,0,0,0.5508793969849246,0,0,1.0,1.0,1,0.0,877,0.9379679144385027,58,0,0,0.0364321608040201,0,2131,3726,0.5873115577889447,2133 -matmul,1x24x12xf64,linalg_xdsl,386,2498,2495,0.0,0,288,314,0,0.8134715025906736,0.9936708860759493,316,0,0,0.8186528497409327,0,0,7.348837209302325,7.348837209302325,1,0.0,43,0.44329896907216493,54,0,0,0.13989637305699482,0,2113,2502,0.9585492227979275,2115 +matmul,1x24x12xf64,linalg_xdsl,389,2517,2514,0.0,0,288,314,0,0.8071979434447301,0.9936708860759493,316,0,0,0.8123393316195373,0,0,7.523809523809524,7.523809523809524,1,0.0,42,0.45161290322580644,51,0,0,0.13110539845758354,0,2129,2521,0.9434447300771208,2131 matmul,1x24x16xf64,baseline,2105,4237,4234,0.0,0,368,385,0,0.1828978622327791,0.32934131736526945,1169,0,0,0.5553444180522565,0,0,1.0,1.0,1,0.0,1169,0.9404666130329847,74,0,0,0.03515439429928741,0,2133,4241,0.590498812351544,2135 matmul,1x24x16xf64,linalg_xdsl,499,2647,2644,0.0,0,384,418,0,0.8376753507014028,0.9952380952380953,420,0,0,0.8416833667334669,0,0,7.5,7.5,1,0.0,56,0.49557522123893805,57,0,0,0.11422845691382766,0,2149,2651,0.9559118236472945,2151 matmul,1x24x20xf64,baseline,2623,4773,4770,0.0,0,460,481,0,0.18337781166603126,0.32922655715263516,1461,0,0,0.5569958063286313,0,0,1.0,1.0,1,0.0,1461,0.941972920696325,90,0,0,0.03431185665268776,0,2151,4777,0.5913076629813191,2153 -matmul,1x24x20xf64,linalg_xdsl,590,2732,2729,0.0,0,480,522,0,0.8847457627118644,0.9961832061068703,524,0,0,0.888135593220339,0,0,7.594202898550724,7.594202898550725,1,0.0,69,0.5348837209302325,60,0,0,0.1016949152542373,0,2143,2736,0.9898305084745762,2145 +matmul,1x24x20xf64,linalg_xdsl,598,2761,2758,0.0,0,480,522,0,0.8729096989966555,0.9961832061068703,524,0,0,0.8762541806020067,0,0,7.705882352941177,7.705882352941177,1,0.0,68,0.544,57,0,0,0.09531772575250837,0,2164,2765,0.9715719063545151,2166 matmul,1x24x24xf64,baseline,3145,5322,5319,0.0,0,552,577,0,0.1834658187599364,0.3291500285225328,1753,0,0,0.5573926868044515,0,0,1.0,1.0,1,0.0,1753,0.9178010471204189,157,0,0,0.04992050874403815,0,2178,5326,0.6073131955484897,2180 -matmul,1x24x24xf64,linalg_xdsl,714,2865,2862,0.0,0,576,626,0,0.876750700280112,0.9968152866242038,628,0,0,0.8795518207282913,0,0,7.658536585365853,7.658536585365853,1,0.0,82,0.5655172413793104,63,0,0,0.08823529411764706,0,2152,2869,0.9677871148459384,2154 +matmul,1x24x24xf64,linalg_xdsl,702,2874,2871,0.0,0,576,626,0,0.8917378917378918,0.9968152866242038,628,0,0,0.8945868945868946,0,0,7.8500000000000005,7.85,1,0.0,80,0.583941605839416,57,0,0,0.0811965811965812,0,2173,2878,0.9757834757834758,2175 matmul,1x24x28xf64,baseline,3681,5841,5838,0.0,0,644,673,0,0.1828307525129041,0.32909535452322736,2045,0,0,0.5555555555555556,0,0,1.0,1.0,1,0.0,2045,0.9186882300089847,181,0,0,0.04917142080956262,0,2161,5845,0.6047269763651182,2163 -matmul,1x24x28xf64,linalg_xdsl,808,2965,2962,0.0,0,672,730,0,0.9034653465346535,0.9972677595628415,732,0,0,0.905940594059406,0,0,7.705263157894737,7.705263157894737,1,0.0,95,0.5900621118012422,66,0,0,0.08168316831683169,0,2158,2969,0.9876237623762376,2160 +matmul,1x24x28xf64,linalg_xdsl,812,3001,2998,0.0,0,672,730,0,0.8990147783251231,0.9972677595628415,732,0,0,0.9014778325123153,0,0,7.956521739130435,7.956521739130435,1,0.0,92,0.6174496644295302,57,0,0,0.07019704433497537,0,2190,3005,0.9716748768472907,2192 matmul,1x24x32xf64,baseline,4182,6335,6332,0.0,0,736,769,0,0.1838833094213295,0.3290543431750107,2337,0,0,0.5588235294117647,0,0,1.0,1.0,1,0.0,2337,0.932934131736527,168,0,0,0.040172166427546625,0,2154,6339,0.5989956958393113,2156 matmul,1x24x32xf64,linalg_xdsl,908,3112,3109,0.0,0,768,834,0,0.9185022026431718,0.9976076555023924,836,0,0,0.920704845814978,0,0,7.7407407407407405,7.7407407407407405,1,0.0,108,0.6136363636363636,68,0,0,0.07488986784140969,0,2205,3116,0.9955947136563877,2207 matmul,1x24x36xf64,baseline,4710,6907,6904,0.0,0,828,865,0,0.18365180467091294,0.3290224419931533,2629,0,0,0.5581740976645435,0,0,1.0,1.0,1,0.0,2629,0.9096885813148788,261,0,0,0.055414012738853505,0,2198,6911,0.613588110403397,2200 -matmul,1x24x36xf64,linalg_xdsl,1014,3233,3230,0.0,0,864,938,0,0.9250493096646942,0.997872340425532,940,0,0,0.9270216962524654,0,0,7.768595041322314,7.768595041322314,1,0.0,121,0.6302083333333334,71,0,0,0.07001972386587771,0,2220,3237,0.9970414201183432,2222 +matmul,1x24x36xf64,linalg_xdsl,1017,3189,3186,0.0,0,864,938,0,0.9223205506391348,0.997872340425532,940,0,0,0.9242871189773845,0,0,7.966101694915254,7.966101694915254,1,0.0,118,0.6555555555555556,62,0,0,0.06096361848574238,0,2173,3193,0.9852507374631269,2175 matmul,1x24x40xf64,baseline,5232,7458,7455,0.0,0,920,961,0,0.18367737003058104,0.32899691886340293,2921,0,0,0.5582951070336392,0,0,1.0,1.0,1,0.0,2921,0.8982164821648216,331,0,0,0.0632645259938838,0,2227,7462,0.6215596330275229,2229 -matmul,1x24x40xf64,linalg_xdsl,1120,3349,3346,0.0,0,960,1042,0,0.9303571428571429,0.9980842911877394,1044,0,0,0.9321428571428572,0,0,7.791044776119403,7.791044776119403,1,0.0,134,0.6442307692307693,74,0,0,0.06607142857142857,0,2230,3353,0.9982142857142857,2232 +matmul,1x24x40xf64,linalg_xdsl,1122,3328,3325,0.0,0,960,1042,0,0.928698752228164,0.9980842911877394,1044,0,0,0.93048128342246,0,0,7.909090909090909,7.909090909090909,1,0.0,132,0.66,68,0,0,0.06060606060606061,0,2207,3332,0.9910873440285206,2209 matmul,1x24x44xf64,baseline,5754,7947,7944,0.0,0,1012,1057,0,0.18369829683698297,0.3289760348583878,3213,0,0,0.5583941605839416,0,0,1.0,1.0,1,0.0,3213,0.8853678699366216,416,0,0,0.07229753215154675,0,2194,7951,0.6306916927354884,2196 matmul,1x24x44xf64,linalg_xdsl,1226,3470,3467,0.0,0,1056,1146,0,0.9347471451876019,0.9982578397212544,1148,0,0,0.9363784665579119,0,0,7.809523809523809,7.809523809523809,1,0.0,147,0.65625,77,0,0,0.06280587275693311,0,2245,3474,0.999184339314845,2247 matmul,1x24x48xf64,baseline,6274,8482,8479,0.0,0,1104,1153,0,0.18377430666241631,0.32895863052781743,3505,0,0,0.5586547656997131,0,0,1.0,1.0,1,0.0,3505,0.8857720495324741,452,0,0,0.07204335352247371,0,2209,8486,0.6306981192221868,2211 -matmul,1x24x48xf64,linalg_xdsl,1332,3591,3588,0.0,0,1152,1250,0,0.9384384384384384,0.9984025559105432,1252,0,0,0.93993993993994,0,0,7.824999999999999,7.825,1,0.0,160,0.6666666666666666,80,0,0,0.06006006006006006,0,2260,3595,1.0,2262 +matmul,1x24x48xf64,linalg_xdsl,1333,3545,3542,0.0,0,1152,1250,0,0.9377344336084021,0.9984025559105432,1252,0,0,0.9392348087021756,0,0,8.025641025641026,8.025641025641026,1,0.0,156,0.6964285714285714,68,0,0,0.05101275318829707,0,2213,3549,0.9902475618904727,2215 matmul,1x24x4xf64,baseline,535,2630,2627,0.0,0,92,97,0,0.18130841121495328,0.3310580204778157,293,0,0,0.5476635514018692,0,0,1.0,1.0,1,0.0,293,0.9213836477987422,25,0,0,0.04672897196261682,0,2096,2634,0.594392523364486,2098 matmul,1x24x4xf64,linalg_xdsl,145,2244,2241,0.0,0,96,105,0,0.7241379310344828,0.9813084112149533,107,0,0,0.7379310344827587,0,0,6.6875,6.6875,1,0.0,16,0.34782608695652173,30,0,0,0.20689655172413793,0,2100,2248,0.9448275862068966,2102 matmul,1x24x52xf64,baseline,6799,9068,9065,0.0,0,1196,1249,0,0.1837034858067363,0.32894390308138005,3797,0,0,0.5584644800705986,0,0,1.0,1.0,1,0.0,3797,0.8538340454238813,650,0,0,0.09560229445506692,0,2270,9072,0.6540667745256655,2272 matmul,1x24x52xf64,linalg_xdsl,1438,3707,3704,0.0,0,1248,1354,0,0.9415855354659249,0.9985250737463127,1356,0,0,0.9429763560500696,0,0,7.8381502890173405,7.838150289017341,1,0.0,173,0.67578125,83,0,0,0.057719054242002785,0,2270,3711,1.0006954102920724,2272 matmul,1x24x56xf64,baseline,7319,9583,9580,0.0,0,1288,1345,0,0.18376827435442,0.3289312790413304,4089,0,0,0.5586828801748873,0,0,1.0,1.0,1,0.0,4089,0.8540100250626567,699,0,0,0.09550485038939746,0,2265,9587,0.6541877305642848,2267 -matmul,1x24x56xf64,linalg_xdsl,1544,3828,3825,0.0,0,1344,1458,0,0.944300518134715,0.9986301369863013,1460,0,0,0.9455958549222798,0,0,7.849462365591398,7.849462365591398,1,0.0,186,0.6838235294117647,86,0,0,0.05569948186528497,0,2285,3832,1.0012953367875648,2287 +matmul,1x24x56xf64,linalg_xdsl,1533,3797,3794,0.0,0,1344,1458,0,0.9510763209393346,0.9986301369863013,1460,0,0,0.9523809523809523,0,0,8.11111111111111,8.11111111111111,1,0.0,180,0.7258064516129032,68,0,0,0.04435746901500326,0,2265,3801,0.9967384213959556,2267 matmul,1x24x60xf64,baseline,7839,10113,10110,0.0,0,1380,1441,0,0.18382446740655695,0.328920337822415,4381,0,0,0.5588723051409619,0,0,1.0,1.0,1,0.0,4381,0.8543291731669267,747,0,0,0.09529276693455797,0,2275,10117,0.6541650720755199,2277 -matmul,1x24x60xf64,linalg_xdsl,1650,3944,3941,0.0,0,1440,1562,0,0.9466666666666667,0.9987212276214834,1564,0,0,0.9478787878787879,0,0,7.85929648241206,7.85929648241206,1,0.0,199,0.6909722222222222,89,0,0,0.05393939393939394,0,2295,3948,1.0018181818181817,2297 +matmul,1x24x60xf64,linalg_xdsl,1649,3901,3898,0.0,0,1440,1562,0,0.9472407519708914,0.9987212276214834,1564,0,0,0.9484536082474226,0,0,8.061855670103093,8.061855670103093,1,0.0,194,0.7238805970149254,74,0,0,0.04487568223165555,0,2253,3905,0.9933292904790781,2255 matmul,1x24x64xf64,baseline,8370,10632,10629,0.0,0,1472,1537,0,0.18363201911589008,0.3289107639631928,4673,0,0,0.5583034647550776,0,0,1.0,1.0,1,5.0,4673,0.8439588224670399,864,5,1,0.1032258064516129,1,2263,10636,0.6615292712066906,2265 matmul,1x24x64xf64,linalg_xdsl,1756,4082,4079,0.0,0,1536,1666,0,0.94874715261959,0.9988009592326139,1668,0,0,0.9498861047835991,0,0,7.867924528301886,7.867924528301887,1,0.0,212,0.6973684210526315,92,0,0,0.05239179954441914,0,2327,4086,1.0022779043280183,2329 matmul,1x24x8xf64,baseline,1059,3156,3153,0.0,0,184,193,0,0.182247403210576,0.3299145299145299,585,0,0,0.5524079320113314,0,0,1.0,1.0,1,0.0,585,0.9345047923322684,41,0,0,0.03871576959395656,0,2098,3160,0.5911237016052879,2100 matmul,1x24x8xf64,linalg_xdsl,266,2390,2387,0.0,0,192,210,0,0.7894736842105263,0.9905660377358491,212,0,0,0.7969924812030075,0,0,7.066666666666666,7.066666666666666,1,0.0,30,0.379746835443038,49,0,0,0.18421052631578946,0,2125,2394,0.981203007518797,2127 matmul,1x28x12xf64,baseline,1844,3969,3966,0.0,0,324,337,0,0.18275488069414317,0.33006856023506365,1021,0,0,0.5536876355748374,0,0,1.0,1.0,1,0.0,1021,0.9462465245597775,58,0,0,0.031453362255965296,0,2126,3973,0.5851409978308026,2128 -matmul,1x28x12xf64,linalg_xdsl,434,2551,2548,0.0,0,336,362,0,0.8341013824884793,0.9945054945054945,364,0,0,0.8387096774193549,0,0,8.465116279069768,8.465116279069768,1,0.0,43,0.44329896907216493,54,0,0,0.12442396313364056,0,2118,2555,0.9631336405529954,2120 +matmul,1x28x12xf64,linalg_xdsl,437,2575,2572,0.0,0,336,362,0,0.8283752860411899,0.9945054945054945,364,0,0,0.8329519450800915,0,0,8.666666666666666,8.666666666666666,1,0.0,42,0.45161290322580644,51,0,0,0.11670480549199085,0,2139,2579,0.9496567505720823,2141 matmul,1x28x16xf64,baseline,2449,4569,4566,0.0,0,432,449,0,0.1833401388321764,0.3299044819985305,1361,0,0,0.555737035524704,0,0,1.0,1.0,1,0.0,1361,0.9484320557491289,74,0,0,0.030216414863209473,0,2121,4573,0.5859534503879135,2123 matmul,1x28x16xf64,linalg_xdsl,563,2716,2713,0.0,0,448,482,0,0.8561278863232682,0.9958677685950413,484,0,0,0.8596802841918295,0,0,8.642857142857144,8.642857142857142,1,0.0,56,0.49557522123893805,57,0,0,0.10124333925399645,0,2154,2720,0.9609236234458259,2156 matmul,1x28x20xf64,baseline,3047,5181,5178,0.0,0,540,561,0,0.18411552346570398,0.3298059964726631,1701,0,0,0.5582540203478832,0,0,1.0,1.0,1,0.0,1701,0.9274809160305344,133,0,0,0.04364949130292091,0,2135,5185,0.6019035116508041,2137 -matmul,1x28x20xf64,linalg_xdsl,685,2852,2849,0.0,0,560,602,0,0.8788321167883212,0.9966887417218543,604,0,0,0.8817518248175182,0,0,8.753623188405797,8.753623188405797,1,0.0,69,0.5348837209302325,60,0,0,0.08759124087591241,0,2168,2856,0.9693430656934306,2170 +matmul,1x28x20xf64,linalg_xdsl,679,2814,2811,0.0,0,560,602,0,0.8865979381443299,0.9966887417218543,604,0,0,0.8895434462444771,0,0,8.882352941176471,8.882352941176471,1,0.0,68,0.544,57,0,0,0.08394698085419734,0,2136,2818,0.9734904270986745,2138 matmul,1x28x24xf64,baseline,3656,5848,5845,0.0,0,648,673,0,0.18408096280087527,0.3297403233708966,2041,0,0,0.5582603938730853,0,0,1.0,1.0,1,0.0,2041,0.9285714285714286,157,0,0,0.04294310722100656,0,2193,5852,0.6012035010940919,2195 -matmul,1x28x24xf64,linalg_xdsl,810,2967,2964,0.0,0,672,722,0,0.891358024691358,0.9972375690607734,724,0,0,0.8938271604938272,0,0,8.829268292682928,8.829268292682928,1,0.0,82,0.5655172413793104,63,0,0,0.07777777777777778,0,2158,2971,0.971604938271605,2160 +matmul,1x28x24xf64,linalg_xdsl,800,2984,2981,0.0,0,672,722,0,0.9025,0.9972375690607734,724,0,0,0.905,0,0,9.05,9.05,1,0.0,80,0.583941605839416,57,0,0,0.07125,0,2185,2988,0.9762500000000001,2187 matmul,1x28x28xf64,baseline,4269,6470,6467,0.0,0,756,785,0,0.18388381353947061,0.32969340613187736,2381,0,0,0.5577418599203561,0,0,1.0,1.0,1,0.0,2381,0.9289894654701522,182,0,0,0.04263293511360974,0,2202,6474,0.6003747950339658,2204 -matmul,1x28x28xf64,linalg_xdsl,941,3137,3134,0.0,0,784,842,0,0.8947927736450585,0.9976303317535545,844,0,0,0.8969181721572795,0,0,8.884210526315789,8.884210526315789,1,0.0,95,0.5900621118012422,66,0,0,0.07013815090329437,0,2197,3141,0.9670563230605739,2199 +matmul,1x28x28xf64,linalg_xdsl,924,3125,3122,0.0,0,784,842,0,0.9112554112554112,0.9976303317535545,844,0,0,0.9134199134199135,0,0,9.173913043478262,9.173913043478262,1,0.0,92,0.6174496644295302,57,0,0,0.06168831168831169,0,2202,3129,0.9751082251082251,2204 matmul,1x28x32xf64,baseline,4864,7066,7063,0.0,0,864,897,0,0.18441611842105263,0.3296582138919515,2721,0,0,0.5594161184210527,0,0,1.0,1.0,1,0.0,2721,0.9009933774834437,299,0,0,0.06147203947368421,0,2203,7070,0.6208881578947368,2205 matmul,1x28x32xf64,linalg_xdsl,1036,3255,3252,0.0,0,896,962,0,0.9285714285714286,0.9979253112033195,964,0,0,0.9305019305019305,0,0,8.925925925925926,8.925925925925926,1,0.0,108,0.6136363636363636,68,0,0,0.06563706563706563,0,2220,3259,0.9961389961389961,2222 matmul,1x28x36xf64,baseline,5463,7661,7658,0.0,0,972,1009,0,0.18469705290133626,0.32963083959490364,3061,0,0,0.5603148453230825,0,0,1.0,1.0,1,0.0,3061,0.9010891963497203,336,0,0,0.061504667764964306,0,2199,7665,0.6218195130880468,2201 -matmul,1x28x36xf64,linalg_xdsl,1158,3397,3394,0.0,0,1008,1082,0,0.9343696027633851,0.9981549815498155,1084,0,0,0.9360967184801382,0,0,8.958677685950413,8.958677685950413,1,0.0,121,0.6302083333333334,71,0,0,0.0613126079447323,0,2240,3401,0.9974093264248705,2242 +matmul,1x28x36xf64,linalg_xdsl,1161,3353,3350,0.0,0,1008,1082,0,0.9319552110249785,0.9981549815498155,1084,0,0,0.9336778639104221,0,0,9.1864406779661,9.186440677966102,1,0.0,118,0.6555555555555556,62,0,0,0.053402239448751075,0,2193,3357,0.9870801033591732,2195 matmul,1x28x40xf64,baseline,6079,8310,8307,0.0,0,1080,1121,0,0.18440532982398422,0.329608938547486,3401,0,0,0.5594670176015792,0,0,1.0,1.0,1,0.0,3401,0.8994974874371859,380,0,0,0.06251028129626583,0,2232,8314,0.621977298897845,2234 -matmul,1x28x40xf64,linalg_xdsl,1280,3534,3531,0.0,0,1120,1202,0,0.9390625,0.9983388704318937,1204,0,0,0.940625,0,0,8.985074626865671,8.985074626865671,1,0.0,134,0.6442307692307693,74,0,0,0.0578125,0,2255,3538,0.9984375000000001,2257 +matmul,1x28x40xf64,linalg_xdsl,1282,3513,3510,0.0,0,1120,1202,0,0.9375975039001561,0.9983388704318937,1204,0,0,0.9391575663026521,0,0,9.121212121212121,9.121212121212121,1,0.0,132,0.66,68,0,0,0.0530421216848674,0,2232,3517,0.9921996879875196,2234 matmul,1x28x44xf64,baseline,6683,8952,8949,0.0,0,1188,1233,0,0.18449797994912465,0.32959101844426625,3741,0,0,0.5597785425707018,0,0,1.0,1.0,1,0.0,3741,0.8710128055878928,554,0,0,0.08289690258865778,0,2270,8956,0.6426754451593596,2272 matmul,1x28x44xf64,linalg_xdsl,1402,3666,3663,0.0,0,1232,1322,0,0.9429386590584878,0.9984894259818731,1324,0,0,0.9443651925820257,0,0,9.006802721088436,9.006802721088436,1,0.0,147,0.65625,77,0,0,0.05492154065620542,0,2265,3670,0.9992867332382311,2267 matmul,1x28x48xf64,baseline,7294,9575,9572,0.0,0,1296,1345,0,0.18439813545379763,0.32957608429306545,4081,0,0,0.5595009596928983,0,0,1.0,1.0,1,0.0,4081,0.8712638770281811,603,0,0,0.08267068823690704,0,2282,9579,0.6421716479298053,2284 -matmul,1x28x48xf64,linalg_xdsl,1524,3808,3805,0.0,0,1344,1442,0,0.9461942257217848,0.9986149584487535,1444,0,0,0.94750656167979,0,0,9.024999999999999,9.025,1,0.0,160,0.6666666666666666,80,0,0,0.05249343832020997,0,2285,3812,1.0,2287 +matmul,1x28x48xf64,linalg_xdsl,1525,3762,3759,0.0,0,1344,1442,0,0.9455737704918032,0.9986149584487535,1444,0,0,0.9468852459016394,0,0,9.256410256410255,9.256410256410257,1,0.0,156,0.6964285714285714,68,0,0,0.04459016393442623,0,2238,3766,0.9914754098360656,2240 matmul,1x28x4xf64,baseline,619,2707,2704,0.0,0,108,113,0,0.1825525040387722,0.3313782991202346,341,0,0,0.5508885298869144,0,0,1.0,1.0,1,0.0,341,0.9316939890710383,25,0,0,0.04038772213247173,0,2089,2711,0.5912762520193862,2091 matmul,1x28x4xf64,linalg_xdsl,161,2265,2262,0.0,0,112,121,0,0.7515527950310559,0.983739837398374,123,0,0,0.7639751552795031,0,0,7.6875,7.6875,1,0.0,16,0.34782608695652173,30,0,0,0.18633540372670807,0,2105,2269,0.9503105590062112,2107 matmul,1x28x52xf64,baseline,7900,10179,10176,0.0,0,1404,1457,0,0.18443037974683543,0.329563447183895,4421,0,0,0.559620253164557,0,0,1.0,1.0,1,5.5,4421,0.8524874662553027,765,11,2,0.09683544303797469,2,2280,10183,0.6564556962025316,2282 matmul,1x28x52xf64,linalg_xdsl,1646,3940,3937,0.0,0,1456,1562,0,0.9489671931956257,0.9987212276214834,1564,0,0,0.9501822600243013,0,0,9.040462427745664,9.040462427745664,1,0.0,173,0.67578125,83,0,0,0.050425273390036454,0,2295,3944,1.0006075334143378,2297 matmul,1x28x56xf64,baseline,8504,10798,10795,0.0,0,1512,1569,0,0.1845014111006585,0.3295526149968494,4761,0,0,0.5598541862652869,0,0,1.0,1.0,1,5.5,4761,0.852920100322465,821,11,2,0.09654280338664158,2,2295,10802,0.6563969896519285,2297 -matmul,1x28x56xf64,linalg_xdsl,1768,4082,4079,0.0,0,1568,1682,0,0.9513574660633484,0.998812351543943,1684,0,0,0.9524886877828054,0,0,9.053763440860216,9.053763440860216,1,0.0,186,0.6838235294117647,86,0,0,0.048642533936651584,0,2315,4086,1.001131221719457,2317 +matmul,1x28x56xf64,linalg_xdsl,1757,4051,4048,0.0,0,1568,1682,0,0.9573136027319294,0.998812351543943,1684,0,0,0.958451906659078,0,0,9.355555555555556,9.355555555555556,1,0.0,180,0.7258064516129032,68,0,0,0.03870233352305066,0,2295,4055,0.9971542401821286,2297 matmul,1x28x60xf64,baseline,9107,11396,11393,0.0,0,1620,1681,0,0.18458328758098166,0.3295432268182709,5101,0,0,0.5601185900955309,0,0,1.0,1.0,1,5.5,5101,0.8534381796888071,876,11,2,0.09618974415284946,2,2290,11400,0.6563083342483803,2292 -matmul,1x28x60xf64,linalg_xdsl,1890,4219,4216,0.0,0,1680,1802,0,0.9534391534391534,0.9988913525498891,1804,0,0,0.9544973544973545,0,0,9.06532663316583,9.06532663316583,1,0.0,199,0.6909722222222222,89,0,0,0.04708994708994709,0,2330,4223,1.0015873015873016,2332 +matmul,1x28x60xf64,linalg_xdsl,1889,4171,4168,0.0,0,1680,1802,0,0.9539438856537851,0.9988913525498891,1804,0,0,0.9550026469031233,0,0,9.29896907216495,9.29896907216495,1,0.0,194,0.7238805970149254,74,0,0,0.039174166225516144,0,2283,4175,0.9941768131286395,2285 matmul,1x28x64xf64,baseline,9714,12038,12035,0.0,0,1728,1793,0,0.1845789582046531,0.3295350119463334,5441,0,0,0.5601194152769199,0,0,1.0,1.0,1,5.5,5441,0.8360479409956976,1067,22,4,0.1098414659254684,4,2325,12042,0.6699608812023883,2327 matmul,1x28x64xf64,linalg_xdsl,2012,4356,4353,0.0,0,1792,1922,0,0.9552683896620279,0.998960498960499,1924,0,0,0.9562624254473161,0,0,9.075471698113207,9.075471698113208,1,0.0,212,0.6973684210526315,92,0,0,0.04572564612326044,0,2345,4360,1.0019880715705765,2347 matmul,1x28x8xf64,baseline,1227,3341,3338,0.0,0,216,225,0,0.18337408312958436,0.3303964757709251,681,0,0,0.5550122249388753,0,0,1.0,1.0,1,0.0,681,0.943213296398892,41,0,0,0.03341483292583537,0,2115,3345,0.5884270578647106,2117 matmul,1x28x8xf64,linalg_xdsl,298,2399,2396,0.0,0,224,242,0,0.8120805369127517,0.9918032786885246,244,0,0,0.8187919463087249,0,0,8.133333333333333,8.133333333333333,1,0.0,30,0.379746835443038,49,0,0,0.1644295302013423,0,2102,2403,0.9832214765100672,2104 matmul,1x32x12xf64,baseline,2100,4226,4223,0.0,0,372,385,0,0.18333333333333332,0.33047210300429186,1165,0,0,0.5547619047619048,0,0,1.0,1.0,1,0.0,1165,0.9525756336876533,58,0,0,0.02761904761904762,0,2127,4230,0.5823809523809524,2129 -matmul,1x32x12xf64,linalg_xdsl,482,2604,2601,0.0,0,384,410,0,0.8506224066390041,0.9951456310679612,412,0,0,0.8547717842323651,0,0,9.581395348837209,9.581395348837209,1,0.0,43,0.44329896907216493,54,0,0,0.11203319502074689,0,2123,2608,0.966804979253112,2125 +matmul,1x32x12xf64,linalg_xdsl,485,2628,2625,0.0,0,384,410,0,0.845360824742268,0.9951456310679612,412,0,0,0.8494845360824742,0,0,9.80952380952381,9.80952380952381,1,0.0,42,0.45161290322580644,51,0,0,0.10515463917525773,0,2144,2632,0.9546391752577319,2146 matmul,1x32x16xf64,baseline,2781,4931,4928,0.0,0,496,513,0,0.18446601941747573,0.330328396651642,1553,0,0,0.5584322186263934,0,0,1.0,1.0,1,0.0,1553,0.944647201946472,91,0,0,0.03272204243078029,0,2151,4935,0.5911542610571736,2153 matmul,1x32x16xf64,linalg_xdsl,612,2779,2776,0.0,0,512,546,0,0.8921568627450981,0.9963503649635036,548,0,0,0.8954248366013072,0,0,9.785714285714286,9.785714285714286,1,0.0,56,0.49557522123893805,57,0,0,0.09313725490196079,0,2168,2783,0.988562091503268,2170 matmul,1x32x20xf64,baseline,3476,5616,5613,0.0,0,620,641,0,0.18440736478711162,0.33024214322514167,1941,0,0,0.5584004602991944,0,0,1.0,1.0,1,0.0,1941,0.9358727097396335,133,0,0,0.038262370540851555,0,2141,5620,0.596662830840046,2143 -matmul,1x32x20xf64,linalg_xdsl,765,2947,2944,0.0,0,640,682,0,0.8915032679738563,0.9970760233918129,684,0,0,0.8941176470588236,0,0,9.91304347826087,9.91304347826087,1,0.0,69,0.5348837209302325,60,0,0,0.0784313725490196,0,2183,2951,0.9725490196078432,2185 +matmul,1x32x20xf64,linalg_xdsl,759,2904,2901,0.0,0,640,682,0,0.8985507246376812,0.9970760233918129,684,0,0,0.9011857707509882,0,0,10.058823529411764,10.058823529411764,1,0.0,68,0.544,57,0,0,0.07509881422924901,0,2146,2908,0.9762845849802372,2148 matmul,1x32x24xf64,baseline,4164,6344,6341,0.0,0,744,769,0,0.18467819404418828,0.3301846285959639,2329,0,0,0.5593179634966379,0,0,1.0,1.0,1,0.0,2329,0.9387343812978638,152,0,0,0.03650336215177714,0,2181,6348,0.5958213256484151,2183 -matmul,1x32x24xf64,linalg_xdsl,906,3073,3070,0.0,0,768,818,0,0.9028697571743929,0.9975609756097561,820,0,0,0.9050772626931567,0,0,10.000000000000002,10.0,1,0.0,82,0.5655172413793104,63,0,0,0.0695364238410596,0,2168,3077,0.9746136865342163,2170 +matmul,1x32x24xf64,linalg_xdsl,896,3090,3087,0.0,0,768,818,0,0.9129464285714286,0.9975609756097561,820,0,0,0.9151785714285714,0,0,10.25,10.25,1,0.0,80,0.583941605839416,57,0,0,0.06361607142857142,0,2195,3094,0.9787946428571428,2197 matmul,1x32x28xf64,baseline,4861,7075,7072,0.0,0,868,897,0,0.184529932112734,0.33014354066985646,2717,0,0,0.5589384900226291,0,0,1.0,1.0,1,0.0,2717,0.9273037542662116,213,0,0,0.043818144414729476,0,2215,7079,0.6027566344373585,2217 -matmul,1x32x28xf64,linalg_xdsl,1032,3214,3211,0.0,0,896,954,0,0.9244186046511628,0.997907949790795,956,0,0,0.9263565891472868,0,0,10.063157894736841,10.063157894736841,1,0.0,95,0.5900621118012422,66,0,0,0.06395348837209303,0,2183,3218,0.9903100775193798,2185 +matmul,1x32x28xf64,linalg_xdsl,1036,3250,3247,0.0,0,896,954,0,0.9208494208494209,0.997907949790795,956,0,0,0.9227799227799228,0,0,10.391304347826088,10.391304347826088,1,0.0,92,0.6174496644295302,57,0,0,0.05501930501930502,0,2215,3254,0.9777992277992278,2217 matmul,1x32x32xf64,baseline,5534,7758,7755,0.0,0,992,1025,0,0.1852186483556198,0.33011272141706927,3105,0,0,0.5610769786772678,0,0,1.0,1.0,1,0.0,3105,0.9191829484902309,273,0,0,0.0493314058547163,0,2225,7762,0.6104083845319841,2227 matmul,1x32x32xf64,linalg_xdsl,1170,3416,3413,0.0,0,1024,1090,0,0.9316239316239316,0.9981684981684982,1092,0,0,0.9333333333333333,0,0,10.111111111111112,10.11111111111111,1,0.0,108,0.6136363636363636,68,0,0,0.05811965811965812,0,2247,3420,0.9914529914529915,2249 matmul,1x32x36xf64,baseline,6225,8497,8494,0.0,0,1116,1153,0,0.18522088353413654,0.33008874892642426,3493,0,0,0.5611244979919678,0,0,1.0,1.0,1,0.0,3493,0.9103466249674225,344,0,0,0.055261044176706825,0,2273,8501,0.6163855421686747,2275 -matmul,1x32x36xf64,linalg_xdsl,1302,3556,3553,0.0,0,1152,1226,0,0.9416282642089093,0.998371335504886,1228,0,0,0.9431643625192012,0,0,10.148760330578511,10.148760330578513,1,0.0,121,0.6302083333333334,71,0,0,0.054531490015360985,0,2255,3560,0.9976958525345622,2257 +matmul,1x32x36xf64,linalg_xdsl,1305,3517,3514,0.0,0,1152,1226,0,0.939463601532567,0.998371335504886,1228,0,0,0.9409961685823754,0,0,10.40677966101695,10.40677966101695,1,0.0,118,0.6555555555555556,62,0,0,0.0475095785440613,0,2213,3521,0.9885057471264368,2215 matmul,1x32x40xf64,baseline,6920,9154,9151,0.0,0,1240,1281,0,0.18511560693641618,0.3300695696985313,3881,0,0,0.5608381502890173,0,0,1.0,1.0,1,0.0,3881,0.8846592204239799,506,0,0,0.073121387283237,0,2235,9158,0.6339595375722543,2237 -matmul,1x32x40xf64,linalg_xdsl,1440,3714,3711,0.0,0,1280,1362,0,0.9458333333333333,0.998533724340176,1364,0,0,0.9472222222222222,0,0,10.17910447761194,10.17910447761194,1,0.0,134,0.6442307692307693,74,0,0,0.05138888888888889,0,2275,3718,0.9986111111111111,2277 +matmul,1x32x40xf64,linalg_xdsl,1442,3693,3690,0.0,0,1280,1362,0,0.9445214979195562,0.998533724340176,1364,0,0,0.9459084604715673,0,0,10.333333333333334,10.333333333333334,1,0.0,132,0.66,68,0,0,0.047156726768377254,0,2252,3697,0.9930651872399445,2254 matmul,1x32x44xf64,baseline,7624,9905,9902,0.0,0,1364,1409,0,0.18481112277019937,0.33005387678613257,4269,0,0,0.5599422875131165,0,0,1.0,1.0,1,5.0,4269,0.8673303535148313,653,10,2,0.08565057712486883,2,2282,9909,0.6455928646379853,2284 matmul,1x32x44xf64,linalg_xdsl,1578,3867,3864,0.0,0,1408,1498,0,0.9493029150823827,0.9986666666666667,1500,0,0,0.9505703422053232,0,0,10.204081632653061,10.204081632653061,1,0.0,147,0.65625,77,0,0,0.048795944233206594,0,2290,3871,0.9993662864385298,2292 matmul,1x32x48xf64,baseline,8312,10597,10594,0.0,0,1488,1537,0,0.1849133782483157,0.33004079879750914,4657,0,0,0.560274302213667,0,0,1.0,1.0,1,5.0,4657,0.8678717853149459,709,10,2,0.08529836381135708,2,2286,10601,0.6455726660250241,2288 -matmul,1x32x48xf64,linalg_xdsl,1716,4042,4039,0.0,0,1536,1634,0,0.9522144522144522,0.9987775061124694,1636,0,0,0.9533799533799534,0,0,10.225000000000001,10.225,1,0.0,160,0.6666666666666666,80,0,0,0.046620046620046623,0,2327,4046,1.0,2329 +matmul,1x32x48xf64,linalg_xdsl,1717,4017,4014,0.0,0,1536,1634,0,0.9516598718695399,0.9987775061124694,1636,0,0,0.9528246942341293,0,0,10.487179487179487,10.487179487179487,1,0.0,156,0.6964285714285714,68,0,0,0.039603960396039604,0,2301,4021,0.9924286546301689,2303 matmul,1x32x4xf64,baseline,705,2806,2803,0.0,0,124,129,0,0.1829787234042553,0.33161953727506427,389,0,0,0.5517730496453901,0,0,1.0,1.0,1,0.0,389,0.9396135265700483,25,0,0,0.03546099290780142,0,2102,2810,0.5872340425531916,2104 matmul,1x32x4xf64,linalg_xdsl,177,2281,2278,0.0,0,128,137,0,0.7740112994350282,0.9856115107913669,139,0,0,0.7853107344632768,0,0,8.6875,8.6875,1,0.0,16,0.34782608695652173,30,0,0,0.1694915254237288,0,2105,2285,0.9548022598870056,2107 matmul,1x32x52xf64,baseline,9009,11311,11308,0.0,0,1612,1665,0,0.1848151848151848,0.33002973240832506,5045,0,0,0.5599955599955599,0,0,1.0,1.0,1,5.2,5045,0.8439277350284377,933,26,5,0.10356310356310357,5,2303,11315,0.6635586635586636,2305 matmul,1x32x52xf64,linalg_xdsl,1854,4178,4175,0.0,0,1664,1770,0,0.9546925566343042,0.9988713318284425,1772,0,0,0.9557713052858684,0,0,10.242774566473988,10.242774566473988,1,0.0,173,0.67578125,83,0,0,0.0447680690399137,0,2325,4182,1.000539374325782,2327 matmul,1x32x56xf64,baseline,9697,12014,12011,0.0,0,1736,1793,0,0.18490254717954008,0.33002024664089824,5433,0,0,0.5602763741363308,0,0,1.0,1.0,1,5.2,5433,0.8444202673298103,1001,26,5,0.10322780241311746,5,2318,12018,0.6635041765494483,2320 -matmul,1x32x56xf64,linalg_xdsl,1992,4331,4328,0.0,0,1792,1906,0,0.9568273092369478,0.9989517819706499,1908,0,0,0.9578313253012049,0,0,10.258064516129032,10.258064516129032,1,0.0,186,0.6838235294117647,86,0,0,0.04317269076305221,0,2340,4335,1.001004016064257,2342 +matmul,1x32x56xf64,linalg_xdsl,1981,4300,4297,0.0,0,1792,1906,0,0.9621403331650682,0.9989517819706499,1908,0,0,0.9631499242806664,0,0,10.6,10.6,1,0.0,180,0.7258064516129032,68,0,0,0.034326097930338216,0,2320,4304,0.9974760222110046,2322 matmul,1x32x60xf64,baseline,10386,12737,12734,0.0,0,1860,1921,0,0.18496052378201425,0.33001202542518465,5821,0,0,0.5604660119391488,0,0,1.0,1.0,1,5.2,5821,0.8447250036279205,1070,26,5,0.10302330059695744,5,2352,12741,0.6634893125361062,2354 -matmul,1x32x60xf64,linalg_xdsl,2130,4489,4486,0.0,0,1920,2042,0,0.9586854460093897,0.9990215264187867,2044,0,0,0.9596244131455399,0,0,10.271356783919598,10.271356783919598,1,0.0,199,0.6909722222222222,89,0,0,0.04178403755868545,0,2360,4493,1.0014084507042254,2362 +matmul,1x32x60xf64,linalg_xdsl,2129,4441,4438,0.0,0,1920,2042,0,0.9591357444809769,0.9990215264187867,2044,0,0,0.960075152653828,0,0,10.536082474226804,10.536082474226804,1,0.0,194,0.7238805970149254,74,0,0,0.03475810239549084,0,2313,4445,0.9948332550493189,2315 matmul,1x32x64xf64,baseline,11070,13437,13434,0.0,0,1984,2049,0,0.1850948509485095,0.33000483169592526,6209,0,0,0.5608852755194219,0,0,1.0,1.0,1,4.875,6209,0.8226020137784844,1339,39,8,0.12095754290876243,8,2368,13441,0.6818428184281844,2370 matmul,1x32x64xf64,linalg_xdsl,2268,4664,4661,0.0,0,2048,2178,0,0.9603174603174603,0.9990825688073395,2180,0,0,0.9611992945326279,0,0,10.283018867924527,10.283018867924529,1,0.0,212,0.6973684210526315,92,0,0,0.04056437389770723,0,2397,4668,1.001763668430335,2399 matmul,1x32x8xf64,baseline,1398,3529,3526,0.0,0,248,257,0,0.1838340486409156,0.3307593307593308,777,0,0,0.555793991416309,0,0,1.0,1.0,1,0.0,777,0.9487179487179487,42,0,0,0.030042918454935622,0,2132,3533,0.5858369098712447,2134 matmul,1x32x8xf64,linalg_xdsl,335,2466,2463,0.0,0,256,274,0,0.817910447761194,0.9927536231884058,276,0,0,0.8238805970149253,0,0,9.2,9.2,1,0.0,30,0.375,50,0,0,0.14925373134328357,0,2132,2470,0.9731343283582089,2134 matmul,1x36x12xf64,baseline,3087,5220,5217,0.0,0,431,444,0,0.14382896015549076,0.33636363636363636,1320,0,0,0.42759961127308066,0,0,1.0,1.0,1,0.0,1320,0.4480651731160896,1626,0,0,0.5267249757045676,0,2134,5224,0.9543245869776482,2136 -matmul,1x36x12xf64,linalg_xdsl,530,2662,2659,0.0,0,432,458,0,0.8641509433962264,0.9956521739130435,460,0,0,0.8679245283018868,0,0,10.69767441860465,10.69767441860465,1,0.0,43,0.44329896907216493,54,0,0,0.1018867924528302,0,2133,2666,0.969811320754717,2135 +matmul,1x36x12xf64,linalg_xdsl,533,2681,2678,0.0,0,432,458,0,0.8592870544090057,0.9956521739130435,460,0,0,0.8630393996247655,0,0,10.952380952380953,10.952380952380953,1,0.0,42,0.45161290322580644,51,0,0,0.09568480300187618,0,2149,2685,0.9587242026266417,2151 matmul,1x36x16xf64,baseline,4111,6308,6305,0.0,0,575,592,0,0.144003891997081,0.33636363636363636,1760,0,0,0.42811967891024083,0,0,1.0,1.0,1,0.0,1760,0.4426559356136821,2216,0,0,0.5390415957188032,0,2198,6312,0.967161274629044,2200 matmul,1x36x16xf64,linalg_xdsl,691,2863,2860,0.0,0,576,610,0,0.8827785817655571,0.9967320261437909,612,0,0,0.8856729377713459,0,0,10.928571428571427,10.928571428571429,1,0.0,56,0.49557522123893805,57,0,0,0.0824891461649783,0,2173,2867,0.9681620839363242,2175 matmul,1x36x20xf64,baseline,5241,7440,7437,0.0,0,720,742,0,0.14157603510780387,0.3369663941871026,2202,0,0,0.42014882655981683,0,0,1.0,1.0,1,0.0,2202,0.4208715596330275,3030,0,0,0.5781339439038351,0,2200,7444,0.9982827704636519,2202 -matmul,1x36x20xf64,linalg_xdsl,845,3034,3031,0.0,0,720,762,0,0.901775147928994,0.9973821989528796,764,0,0,0.9041420118343195,0,0,11.072463768115941,11.072463768115941,1,0.0,69,0.5348837209302325,60,0,0,0.07100591715976332,0,2190,3038,0.9751479289940829,2192 +matmul,1x36x20xf64,linalg_xdsl,832,2983,2980,0.0,0,720,762,0,0.9158653846153846,0.9973821989528796,764,0,0,0.9182692307692307,0,0,11.235294117647058,11.235294117647058,1,0.0,68,0.544,57,0,0,0.06850961538461539,0,2152,2987,0.9867788461538461,2154 matmul,1x36x24xf64,baseline,6286,8499,8496,0.0,0,864,890,0,0.14158447343302577,0.3368660105980318,2642,0,0,0.42029907731466754,0,0,1.0,1.0,1,0.0,2642,0.42096876991714466,3634,0,0,0.5781100859051861,0,2214,8503,0.9984091632198536,2216 -matmul,1x36x24xf64,linalg_xdsl,1002,3184,3181,0.0,0,864,914,0,0.9121756487025948,0.9978165938864629,916,0,0,0.9141716566866267,0,0,11.170731707317072,11.170731707317072,1,0.0,82,0.5655172413793104,63,0,0,0.06287425149700598,0,2183,3188,0.9770459081836327,2185 +matmul,1x36x24xf64,linalg_xdsl,992,3201,3198,0.0,0,864,914,0,0.9213709677419355,0.9978165938864629,916,0,0,0.9233870967741935,0,0,11.45,11.45,1,0.0,80,0.583941605839416,57,0,0,0.057459677419354836,0,2210,3205,0.9808467741935484,2212 matmul,1x36x28xf64,baseline,7330,9540,9537,0.0,0,1008,1038,0,0.14160982264665758,0.33679428942245293,3082,0,0,0.42046384720327423,0,0,1.0,1.0,1,0.0,3082,0.4210382513661202,4238,0,0,0.5781718963165074,0,2211,9544,0.9986357435197817,2213 -matmul,1x36x28xf64,linalg_xdsl,1144,3346,3343,0.0,0,1008,1066,0,0.9318181818181818,0.99812734082397,1068,0,0,0.9335664335664335,0,0,11.242105263157894,11.242105263157894,1,0.0,95,0.5900621118012422,66,0,0,0.057692307692307696,0,2203,3350,0.9912587412587412,2205 +matmul,1x36x28xf64,linalg_xdsl,1148,3377,3374,0.0,0,1008,1066,0,0.9285714285714286,0.99812734082397,1068,0,0,0.9303135888501742,0,0,11.608695652173914,11.608695652173912,1,0.0,92,0.6174496644295302,57,0,0,0.04965156794425087,0,2230,3381,0.9799651567944251,2232 matmul,1x36x32xf64,baseline,8374,10587,10584,0.0,0,1152,1186,0,0.14162885120611415,0.336740488358887,3522,0,0,0.42058753283974204,0,0,1.0,1.0,1,0.0,3522,0.4211407389692694,4841,0,0,0.5780988774779078,0,2214,10591,0.9986864103176498,2216 matmul,1x36x32xf64,linalg_xdsl,1292,3546,3543,0.0,0,1152,1218,0,0.9427244582043344,0.9983606557377049,1220,0,0,0.9442724458204335,0,0,11.296296296296298,11.296296296296296,1,0.0,108,0.6136363636363636,68,0,0,0.05263157894736842,0,2255,3550,0.9969040247678018,2257 matmul,1x36x36xf64,baseline,9418,11675,11672,0.0,0,1296,1334,0,0.14164366107453813,0.33669863705199393,3962,0,0,0.42068379698449776,0,0,1.0,1.0,1,0.0,3962,0.4211757202083555,5445,0,0,0.5781482267997452,0,2258,11679,0.998832023784243,2260 -matmul,1x36x36xf64,linalg_xdsl,1446,3737,3734,0.0,0,1296,1370,0,0.9474412171507607,0.9985422740524781,1372,0,0,0.9488243430152143,0,0,11.338842975206612,11.338842975206612,1,0.0,121,0.6302083333333334,71,0,0,0.04910096818810512,0,2292,3741,0.9979253112033195,2294 +matmul,1x36x36xf64,linalg_xdsl,1449,3714,3711,0.0,0,1296,1370,0,0.945479641131815,0.9985422740524781,1372,0,0,0.9468599033816425,0,0,11.627118644067798,11.627118644067796,1,0.0,118,0.6555555555555556,62,0,0,0.04278812974465148,0,2266,3718,0.989648033126294,2268 matmul,1x36x40xf64,baseline,10462,12715,12712,0.0,0,1440,1482,0,0.1416555151978589,0.3366651522035438,4402,0,0,0.42076084878608294,0,0,1.0,1.0,1,0.0,4402,0.42120371256339106,6049,0,0,0.5781877270120436,0,2254,12719,0.9989485757981265,2256 -matmul,1x36x40xf64,linalg_xdsl,1600,3894,3891,0.0,0,1440,1522,0,0.95125,0.9986876640419947,1524,0,0,0.9525,0,0,11.373134328358208,11.373134328358208,1,0.0,134,0.6442307692307693,74,0,0,0.04625,0,2295,3898,0.99875,2297 +matmul,1x36x40xf64,linalg_xdsl,1602,3873,3870,0.0,0,1440,1522,0,0.9500624219725343,0.9986876640419947,1524,0,0,0.951310861423221,0,0,11.545454545454547,11.545454545454545,1,0.0,132,0.66,68,0,0,0.04244694132334582,0,2272,3877,0.9937578027465668,2274 matmul,1x36x44xf64,baseline,11506,13779,13776,0.0,0,1584,1630,0,0.1416652181470537,0.33663775299463033,4842,0,0,0.4208239179558491,0,0,1.0,1.0,1,0.0,4842,0.4212266202696825,6653,0,0,0.5782200590996002,0,2274,13783,0.9990439770554493,2276 matmul,1x36x44xf64,linalg_xdsl,1754,4068,4065,0.0,0,1584,1674,0,0.9543899657924744,0.9988066825775657,1676,0,0,0.9555302166476625,0,0,11.401360544217688,11.401360544217686,1,0.0,147,0.65625,77,0,0,0.04389965792474344,0,2315,4072,0.999429874572406,2317 matmul,1x36x48xf64,baseline,12550,14843,14840,0.0,0,1728,1778,0,0.14167330677290838,0.33661491859144266,5282,0,0,0.42087649402390437,0,0,1.0,1.0,1,0.0,5282,0.42124571337427225,7257,0,0,0.5782470119521912,0,2294,14847,0.9991235059760956,2296 -matmul,1x36x48xf64,linalg_xdsl,1908,4242,4239,0.0,0,1728,1826,0,0.9570230607966457,0.9989059080962801,1828,0,0,0.9580712788259959,0,0,11.424999999999999,11.425,1,0.0,160,0.6666666666666666,80,0,0,0.041928721174004195,0,2335,4246,1.0,2337 +matmul,1x36x48xf64,linalg_xdsl,1909,4196,4193,0.0,0,1728,1826,0,0.9565217391304348,0.9989059080962801,1828,0,0,0.9575694080670508,0,0,11.717948717948717,11.717948717948717,1,0.0,156,0.6964285714285714,68,0,0,0.035620743844945,0,2288,4200,0.9931901519119958,2290 matmul,1x36x4xf64,baseline,997,3063,3060,0.0,0,143,148,0,0.14844533600802406,0.33636363636363636,440,0,0,0.44132397191574724,0,0,1.0,1.0,1,0.0,440,0.496054114994363,447,0,0,0.4483450351053159,0,2067,3067,0.8896690070210631,2069 matmul,1x36x4xf64,linalg_xdsl,193,2297,2294,0.0,0,144,153,0,0.7927461139896373,0.9870967741935484,155,0,0,0.8031088082901554,0,0,9.6875,9.6875,1,0.0,16,0.34782608695652173,30,0,0,0.15544041450777202,0,2105,2301,0.9585492227979274,2107 matmul,1x36x52xf64,baseline,13594,15907,15904,0.0,0,1872,1926,0,0.1416801530086803,0.3365955959454736,5722,0,0,0.42092099455642196,0,0,1.0,1.0,1,0.0,5722,0.42126187145696825,7861,0,0,0.57826982492276,0,2314,15911,0.999190819479182,2316 matmul,1x36x52xf64,linalg_xdsl,2062,4416,4413,0.0,0,1872,1978,0,0.9592628516003879,0.998989898989899,1980,0,0,0.9602327837051406,0,0,11.445086705202312,11.445086705202312,1,0.0,173,0.67578125,83,0,0,0.040252182347235696,0,2355,4420,1.0004849660523762,2357 matmul,1x36x56xf64,baseline,14638,16971,16968,0.0,0,2016,2074,0,0.14168602268069408,0.3365790327815644,6162,0,0,0.42095914742451157,0,0,1.0,1.0,1,0.0,6162,0.42127572297805427,8465,0,0,0.5782893837956005,0,2334,16975,0.999248531220112,2336 -matmul,1x36x56xf64,linalg_xdsl,2216,4590,4587,0.0,0,2016,2130,0,0.9611913357400722,0.99906191369606,2132,0,0,0.9620938628158845,0,0,11.46236559139785,11.46236559139785,1,0.0,186,0.6838235294117647,86,0,0,0.0388086642599278,0,2375,4594,1.0009025270758123,2377 +matmul,1x36x56xf64,linalg_xdsl,2205,4559,4556,0.0,0,2016,2130,0,0.9659863945578231,0.99906191369606,2132,0,0,0.9668934240362812,0,0,11.844444444444445,11.844444444444445,1,0.0,180,0.7258064516129032,68,0,0,0.030839002267573697,0,2355,4563,0.997732426303855,2357 matmul,1x36x60xf64,baseline,15682,18030,18027,0.0,0,2160,2222,0,0.14169111082770056,0.3365646773704938,6602,0,0,0.4209922203800536,0,0,1.0,1.0,1,0.0,6602,0.4212877289260417,9069,0,0,0.578306338477235,0,2349,18034,0.9992985588572886,2351 -matmul,1x36x60xf64,linalg_xdsl,2370,4759,4756,0.0,0,2160,2282,0,0.9628691983122363,0.999124343257443,2284,0,0,0.9637130801687763,0,0,11.477386934673367,11.477386934673367,1,0.0,199,0.6909722222222222,89,0,0,0.03755274261603375,0,2390,4763,1.0012658227848101,2392 +matmul,1x36x60xf64,linalg_xdsl,2369,4711,4708,0.0,0,2160,2282,0,0.9632756437315323,0.999124343257443,2284,0,0,0.9641198818066695,0,0,11.77319587628866,11.77319587628866,1,0.0,194,0.7238805970149254,74,0,0,0.03123680878007598,0,2343,4715,0.9953566905867455,2345 matmul,1x36x64xf64,baseline,16726,19094,19091,0.0,0,2304,2370,0,0.14169556379289727,0.33655211587617156,7042,0,0,0.4210211646538324,0,0,1.0,1.0,1,0.0,7042,0.42129823511815734,9673,0,0,0.5783211766112639,0,2369,19098,0.9993423412650964,2371 matmul,1x36x64xf64,linalg_xdsl,2524,4933,4930,0.0,0,2304,2434,0,0.9643423137876387,0.9991789819376026,2436,0,0,0.96513470681458,0,0,11.490566037735851,11.49056603773585,1,0.0,212,0.6973684210526315,92,0,0,0.03645007923930269,0,2410,4937,1.0015847860538827,2412 matmul,1x36x8xf64,baseline,2041,4157,4154,0.0,0,287,296,0,0.14502694757471826,0.33636363636363636,880,0,0,0.43116119549240567,0,0,1.0,1.0,1,0.0,880,0.4590505998956703,1037,0,0,0.5080842724154826,0,2117,4161,0.9392454679078883,2119 matmul,1x36x8xf64,linalg_xdsl,368,2480,2477,0.0,0,288,306,0,0.8315217391304348,0.9935064935064936,308,0,0,0.8369565217391305,0,0,10.266666666666666,10.266666666666667,1,0.0,30,0.37037037037037035,51,0,0,0.13858695652173914,0,2113,2484,0.9755434782608696,2115 matmul,1x40x12xf64,baseline,3502,5645,5642,0.0,0,480,493,0,0.1407766990291262,0.336518771331058,1465,0,0,0.4183323814962878,0,0,1.0,1.0,1,0.0,1465,0.4273628938156359,1963,0,0,0.5605368360936608,0,2144,5649,0.9788692175899486,2146 -matmul,1x40x12xf64,linalg_xdsl,585,2742,2739,0.0,0,480,506,0,0.864957264957265,0.9960629921259843,508,0,0,0.8683760683760684,0,0,11.813953488372093,11.813953488372093,1,0.0,43,0.44329896907216493,54,0,0,0.09230769230769231,0,2158,2746,0.9606837606837607,2160 +matmul,1x40x12xf64,linalg_xdsl,572,2717,2714,0.0,0,480,506,0,0.8846153846153846,0.9960629921259843,508,0,0,0.8881118881118881,0,0,12.095238095238095,12.095238095238095,1,0.0,42,0.45161290322580644,51,0,0,0.08916083916083917,0,2146,2721,0.9772727272727273,2148 matmul,1x40x16xf64,baseline,4670,6833,6830,0.0,0,640,657,0,0.14068522483940044,0.33640552995391704,1953,0,0,0.41820128479657387,0,0,1.0,1.0,1,0.0,1953,0.42753940455341505,2615,0,0,0.5599571734475375,0,2164,6837,0.9781584582441114,2166 matmul,1x40x16xf64,linalg_xdsl,755,2932,2929,0.0,0,640,674,0,0.8927152317880794,0.9970414201183432,676,0,0,0.895364238410596,0,0,12.071428571428573,12.071428571428571,1,0.0,56,0.49557522123893805,57,0,0,0.07549668874172186,0,2178,2936,0.9708609271523179,2180 matmul,1x40x20xf64,baseline,5802,8007,8004,0.0,0,800,822,0,0.14167528438469493,0.3366093366093366,2442,0,0,0.42088934850051707,0,0,1.0,1.0,1,0.0,2442,0.42161602209944754,3350,0,0,0.5773871078938297,0,2206,8011,0.9982764563943468,2208 -matmul,1x40x20xf64,linalg_xdsl,926,3128,3125,0.0,0,800,842,0,0.9092872570194385,0.9976303317535545,844,0,0,0.9114470842332614,0,0,12.231884057971014,12.231884057971014,1,0.0,69,0.5348837209302325,60,0,0,0.06479481641468683,0,2203,3132,0.9762419006479482,2205 +matmul,1x40x20xf64,linalg_xdsl,919,3084,3081,0.0,0,800,842,0,0.9162132752992383,0.9976303317535545,844,0,0,0.9183895538628944,0,0,12.411764705882353,12.411764705882353,1,0.0,68,0.544,57,0,0,0.062023939064200215,0,2166,3088,0.9804134929270947,2168 matmul,1x40x24xf64,baseline,6958,9186,9183,0.0,0,960,986,0,0.14170738718022421,0.336518771331058,2930,0,0,0.4210980166714573,0,0,1.0,1.0,1,0.0,2930,0.4217040875071963,4018,0,0,0.5774647887323944,0,2229,9190,0.9985628054038517,2231 -matmul,1x40x24xf64,linalg_xdsl,1098,3290,3287,0.0,0,960,1010,0,0.9198542805100182,0.9980237154150198,1012,0,0,0.9216757741347905,0,0,12.341463414634145,12.341463414634147,1,0.0,82,0.5655172413793104,63,0,0,0.05737704918032787,0,2193,3294,0.9790528233151183,2195 +matmul,1x40x24xf64,linalg_xdsl,1088,3307,3304,0.0,0,960,1010,0,0.9283088235294118,0.9980237154150198,1012,0,0,0.9301470588235294,0,0,12.65,12.65,1,0.0,80,0.583941605839416,57,0,0,0.05238970588235294,0,2220,3311,0.9825367647058824,2222 matmul,1x40x28xf64,baseline,8114,10339,10336,0.0,0,1120,1150,0,0.14173034261769782,0.33645406670567585,3418,0,0,0.42124722701503575,0,0,1.0,1.0,1,0.0,3418,0.4217670286278381,4686,0,0,0.5775203352230712,0,2226,10343,0.9987675622381069,2228 -matmul,1x40x28xf64,linalg_xdsl,1256,3468,3465,0.0,0,1120,1178,0,0.9378980891719745,0.9983050847457627,1180,0,0,0.9394904458598726,0,0,12.421052631578947,12.421052631578947,1,0.0,95,0.5900621118012422,66,0,0,0.052547770700636945,0,2213,3472,0.9920382165605096,2215 +matmul,1x40x28xf64,linalg_xdsl,1260,3504,3501,0.0,0,1120,1178,0,0.9349206349206349,0.9983050847457627,1180,0,0,0.9365079365079365,0,0,12.82608695652174,12.826086956521738,1,0.0,92,0.6174496644295302,57,0,0,0.04523809523809524,0,2245,3508,0.9817460317460317,2247 matmul,1x40x32xf64,baseline,9270,11498,11495,0.0,0,1280,1314,0,0.141747572815534,0.33640552995391704,3906,0,0,0.42135922330097086,0,0,1.0,1.0,1,0.0,3906,0.4218598120747381,5353,0,0,0.5774541531823085,0,2229,11502,0.9988133764832794,2231 matmul,1x40x32xf64,linalg_xdsl,1420,3689,3686,0.0,0,1280,1346,0,0.9478873239436619,0.9985163204747775,1348,0,0,0.9492957746478873,0,0,12.481481481481483,12.481481481481481,1,0.0,108,0.6136363636363636,68,0,0,0.04788732394366197,0,2270,3693,0.9971830985915493,2272 matmul,1x40x36xf64,baseline,10426,12679,12676,0.0,0,1440,1478,0,0.14176098215998464,0.33636777423759673,4394,0,0,0.42144638403990026,0,0,1.0,1.0,1,0.0,4394,0.42189150264042247,6021,0,0,0.5774985612890849,0,2254,12683,0.9989449453289851,2256 -matmul,1x40x36xf64,linalg_xdsl,1590,3884,3881,0.0,0,1440,1514,0,0.9522012578616352,0.9986807387862797,1516,0,0,0.9534591194968554,0,0,12.52892561983471,12.52892561983471,1,0.0,121,0.6302083333333334,71,0,0,0.04465408805031446,0,2295,3888,0.9981132075471698,2297 +matmul,1x40x36xf64,linalg_xdsl,1593,3840,3837,0.0,0,1440,1514,0,0.9504080351537979,0.9986807387862797,1516,0,0,0.9516635279347144,0,0,12.847457627118644,12.847457627118644,1,0.0,118,0.6555555555555556,62,0,0,0.0389202762084118,0,2248,3844,0.9905838041431262,2250 matmul,1x40x40xf64,baseline,11582,13879,13876,0.0,0,1600,1642,0,0.14177171472975306,0.33633756657107744,4882,0,0,0.4215161457433949,0,0,1.0,1.0,1,0.0,4882,0.421916861118313,6689,0,0,0.577534104645139,0,2298,13883,0.9990502503885339,2300 -matmul,1x40x40xf64,linalg_xdsl,1760,4091,4088,0.0,0,1600,1682,0,0.9556818181818182,0.998812351543943,1684,0,0,0.9568181818181818,0,0,12.567164179104477,12.567164179104477,1,0.0,134,0.6442307692307693,74,0,0,0.042045454545454546,0,2332,4095,0.9988636363636363,2334 +matmul,1x40x40xf64,linalg_xdsl,1755,4051,4048,0.0,0,1600,1682,0,0.9584045584045584,0.998812351543943,1684,0,0,0.9595441595441595,0,0,12.757575757575758,12.757575757575758,1,0.0,132,0.66,68,0,0,0.038746438746438745,0,2297,4055,0.9982905982905983,2299 matmul,1x40x44xf64,baseline,12738,15069,15066,0.0,0,1760,1806,0,0.14178049929345266,0.33631284916201115,5370,0,0,0.4215732454074423,0,0,1.0,1.0,1,0.0,5370,0.4219376129488489,7357,0,0,0.5775631967341812,0,2332,15073,0.9991364421416236,2334 matmul,1x40x44xf64,linalg_xdsl,1930,4256,4253,0.0,0,1760,1850,0,0.9585492227979274,0.9989200863930886,1852,0,0,0.9595854922279793,0,0,12.598639455782312,12.598639455782314,1,0.0,147,0.65625,77,0,0,0.03989637305699482,0,2327,4260,0.9994818652849741,2329 matmul,1x40x48xf64,baseline,13894,16212,16209,0.0,0,1920,1970,0,0.14178782208147403,0.3362922499146466,5858,0,0,0.4216208435295811,0,0,1.0,1.0,1,0.0,5858,0.4219549088813657,8025,0,0,0.5775874478192026,0,2319,16216,0.9992082913487836,2321 -matmul,1x40x48xf64,linalg_xdsl,2100,4459,4456,0.0,0,1920,2018,0,0.960952380952381,0.999009900990099,2020,0,0,0.9619047619047619,0,0,12.625,12.625,1,0.0,160,0.6666666666666666,80,0,0,0.0380952380952381,0,2360,4463,1.0,2362 +matmul,1x40x48xf64,linalg_xdsl,2101,4413,4410,0.0,0,1920,2018,0,0.9604950023798191,0.999009900990099,2020,0,0,0.9614469300333175,0,0,12.948717948717949,12.948717948717949,1,0.0,156,0.6964285714285714,68,0,0,0.03236554021894336,0,2313,4417,0.9938124702522608,2315 matmul,1x40x4xf64,baseline,1170,3275,3272,0.0,0,160,165,0,0.14102564102564102,0.3374233128834356,489,0,0,0.41794871794871796,0,0,1.0,1.0,1,0.0,489,0.42632955536181344,658,0,0,0.5623931623931624,0,2106,3279,0.9803418803418804,2108 matmul,1x40x4xf64,linalg_xdsl,209,2318,2315,0.0,0,160,169,0,0.8086124401913876,0.9883040935672515,171,0,0,0.8181818181818182,0,0,10.6875,10.6875,1,0.0,16,0.34782608695652173,30,0,0,0.14354066985645933,0,2110,2322,0.9617224880382775,2112 matmul,1x40x52xf64,baseline,15050,17388,17385,0.0,0,2080,2134,0,0.1417940199335548,0.33627481878348564,6346,0,0,0.4216611295681063,0,0,1.0,1.0,1,0.0,6346,0.42196954584746327,8693,0,0,0.5776079734219269,0,2339,17392,0.9992691029900332,2341 matmul,1x40x52xf64,linalg_xdsl,2272,4651,4648,0.0,0,2080,2186,0,0.9621478873239436,0.9990859232175503,2188,0,0,0.9630281690140845,0,0,12.647398843930635,12.647398843930636,1,0.0,173,0.67578125,83,0,0,0.03653169014084507,0,2380,4655,0.9995598591549296,2382 matmul,1x40x56xf64,baseline,16206,18564,18561,0.0,0,2240,2298,0,0.1417993335801555,0.3362598770851624,6834,0,0,0.42169566827101074,0,0,1.0,1.0,1,0.0,6834,0.42198209323865393,9361,0,0,0.5776255707762558,0,2359,18568,0.9993212390472666,2361 -matmul,1x40x56xf64,linalg_xdsl,2440,4839,4836,0.0,0,2240,2354,0,0.9647540983606557,0.9991511035653651,2356,0,0,0.9655737704918033,0,0,12.666666666666666,12.666666666666666,1,0.0,186,0.6838235294117647,86,0,0,0.03524590163934426,0,2400,4843,1.0008196721311475,2402 +matmul,1x40x56xf64,linalg_xdsl,2429,4808,4805,0.0,0,2240,2354,0,0.9691230959242486,0.9991511035653651,2356,0,0,0.9699464800329354,0,0,13.088888888888889,13.088888888888889,1,0.0,180,0.7258064516129032,68,0,0,0.02799505969534788,0,2380,4812,0.9979415397282833,2382 matmul,1x40x60xf64,baseline,17362,19745,19742,0.0,0,2400,2462,0,0.14180393963829052,0.3362469270691068,7322,0,0,0.4217256076488884,0,0,1.0,1.0,1,0.0,7322,0.42199296870497377,10029,0,0,0.5776408247897707,0,2384,19749,0.9993664324386591,2386 -matmul,1x40x60xf64,linalg_xdsl,2610,5034,5031,0.0,0,2400,2522,0,0.9662835249042145,0.9992076069730587,2524,0,0,0.9670498084291188,0,0,12.683417085427136,12.683417085427136,1,0.0,199,0.6909722222222222,89,0,0,0.03409961685823755,0,2425,5038,1.0011494252873563,2427 +matmul,1x40x60xf64,linalg_xdsl,2609,4981,4978,0.0,0,2400,2522,0,0.9666538903794557,0.9992076069730587,2524,0,0,0.9674204676121119,0,0,13.010309278350515,13.010309278350515,1,0.0,194,0.7238805970149254,74,0,0,0.028363357608279034,0,2373,4985,0.9957838252203909,2375 matmul,1x40x64xf64,baseline,18518,20945,20942,0.0,0,2560,2626,0,0.14180797062317746,0.33623559539052494,7810,0,0,0.4217518090506534,0,0,1.0,1.0,1,0.0,7810,0.4220024855460096,10697,0,0,0.5776541743168808,0,2428,20949,0.9994059833675342,2430 matmul,1x40x64xf64,linalg_xdsl,2780,5241,5238,0.0,0,2560,2690,0,0.9676258992805755,0.9992570579494799,2692,0,0,0.9683453237410072,0,0,12.69811320754717,12.69811320754717,1,0.0,212,0.6973684210526315,92,0,0,0.033093525179856115,0,2462,5245,1.0014388489208634,2464 matmul,1x40x8xf64,baseline,2340,4465,4462,0.0,0,320,329,0,0.1405982905982906,0.3367451381780962,977,0,0,0.41752136752136754,0,0,1.0,1.0,1,0.0,977,0.42701048951048953,1311,0,0,0.5602564102564103,0,2126,4469,0.9777777777777779,2128 matmul,1x40x8xf64,linalg_xdsl,400,2517,2514,0.0,0,320,338,0,0.845,0.9941176470588236,340,0,0,0.85,0,0,11.333333333333334,11.333333333333334,1,0.0,30,0.37037037037037035,51,0,0,0.1275,0,2118,2521,0.9775,2120 matmul,1x44x12xf64,baseline,3838,5991,5988,0.0,0,528,541,0,0.1409588327253778,0.3362336855189559,1609,0,0,0.4192287649817613,0,0,1.0,1.0,1,0.0,1609,0.42747077577045695,2155,0,0,0.561490359562272,0,2154,5995,0.9807191245440333,2156 -matmul,1x44x12xf64,linalg_xdsl,633,2795,2792,0.0,0,528,554,0,0.8751974723538705,0.9964028776978417,556,0,0,0.8783570300157978,0,0,12.930232558139535,12.930232558139535,1,0.0,43,0.44329896907216493,54,0,0,0.08530805687203792,0,2163,2799,0.9636650868878357,2165 +matmul,1x44x12xf64,linalg_xdsl,620,2775,2772,0.0,0,528,554,0,0.8935483870967742,0.9964028776978417,556,0,0,0.896774193548387,0,0,13.238095238095237,13.238095238095237,1,0.0,42,0.45161290322580644,51,0,0,0.08225806451612903,0,2156,2779,0.9790322580645161,2158 matmul,1x44x16xf64,baseline,5118,7291,7288,0.0,0,704,721,0,0.14087534193044157,0.3361305361305361,2145,0,0,0.4191090269636577,0,0,1.0,1.0,1,0.0,2145,0.4276315789473684,2871,0,0,0.5609613130128956,0,2174,7295,0.9800703399765534,2176 matmul,1x44x16xf64,linalg_xdsl,819,3006,3003,0.0,0,704,738,0,0.9010989010989011,0.9972972972972973,740,0,0,0.9035409035409036,0,0,13.214285714285714,13.214285714285714,1,0.0,56,0.49557522123893805,57,0,0,0.0695970695970696,0,2188,3010,0.9731379731379731,2190 matmul,1x44x20xf64,baseline,6362,8577,8574,0.0,0,880,902,0,0.14177931468091795,0.33631618195376584,2682,0,0,0.4215655454259667,0,0,1.0,1.0,1,0.0,2682,0.4222292191435768,3670,0,0,0.5768626218170386,0,2216,8581,0.9984281672430053,2218 -matmul,1x44x20xf64,linalg_xdsl,1005,3217,3214,0.0,0,880,922,0,0.9174129353233831,0.9978354978354979,924,0,0,0.9194029850746268,0,0,13.391304347826088,13.391304347826088,1,0.0,69,0.5348837209302325,60,0,0,0.05970149253731343,0,2213,3221,0.9791044776119402,2215 +matmul,1x44x20xf64,linalg_xdsl,999,3174,3171,0.0,0,880,922,0,0.9229229229229229,0.9978354978354979,924,0,0,0.924924924924925,0,0,13.588235294117647,13.588235294117647,1,0.0,68,0.544,57,0,0,0.057057057057057055,0,2176,3178,0.981981981981982,2178 matmul,1x44x24xf64,baseline,7630,9873,9870,0.0,0,1056,1082,0,0.1418086500655308,0.3362336855189559,3218,0,0,0.4217562254259502,0,0,1.0,1.0,1,0.0,3218,0.42230971128608924,4402,0,0,0.5769331585845348,0,2244,9877,0.9986893840104849,2246 -matmul,1x44x24xf64,linalg_xdsl,1194,3401,3398,0.0,0,1056,1106,0,0.9262981574539364,0.9981949458483754,1108,0,0,0.9279731993299832,0,0,13.51219512195122,13.512195121951219,1,0.0,82,0.5655172413793104,63,0,0,0.052763819095477386,0,2208,3405,0.9807370184254606,2210 +matmul,1x44x24xf64,linalg_xdsl,1184,3418,3415,0.0,0,1056,1106,0,0.9341216216216216,0.9981949458483754,1108,0,0,0.9358108108108109,0,0,13.85,13.85,1,0.0,80,0.583941605839416,57,0,0,0.04814189189189189,0,2235,3422,0.9839527027027027,2237 matmul,1x44x28xf64,baseline,8898,11133,11130,0.0,0,1232,1262,0,0.14182962463474938,0.33617474693660093,3754,0,0,0.421892560125871,0,0,1.0,1.0,1,0.0,3754,0.4223672367236724,5134,0,0,0.5769835918183861,0,2236,11137,0.998876151944257,2238 -matmul,1x44x28xf64,linalg_xdsl,1368,3636,3633,0.0,0,1232,1290,0,0.9429824561403509,0.9984520123839009,1292,0,0,0.9444444444444444,0,0,13.600000000000001,13.6,1,0.0,95,0.5900621118012422,66,0,0,0.04824561403508772,0,2269,3640,0.9926900584795322,2271 +matmul,1x44x28xf64,linalg_xdsl,1372,3646,3643,0.0,0,1232,1290,0,0.9402332361516035,0.9984520123839009,1292,0,0,0.9416909620991254,0,0,14.043478260869566,14.043478260869565,1,0.0,92,0.6174496644295302,57,0,0,0.04154518950437318,0,2275,3650,0.9832361516034985,2277 matmul,1x44x32xf64,baseline,10166,12414,12411,0.0,0,1408,1442,0,0.14184536690930552,0.3361305361305361,4290,0,0,0.4219948849104859,0,0,1.0,1.0,1,0.0,4290,0.4224519940915805,5865,0,0,0.5769230769230769,0,2249,12418,0.9989179618335629,2251 matmul,1x44x32xf64,linalg_xdsl,1548,3837,3834,0.0,0,1408,1474,0,0.9521963824289406,0.9986449864498645,1476,0,0,0.9534883720930233,0,0,13.666666666666666,13.666666666666666,1,0.0,108,0.6136363636363636,68,0,0,0.04392764857881137,0,2290,3841,0.9974160206718347,2292 matmul,1x44x36xf64,baseline,11434,13707,13704,0.0,0,1584,1622,0,0.14185761763162497,0.3360961458765023,4826,0,0,0.42207451460556233,0,0,1.0,1.0,1,0.0,4826,0.4224809594677405,6597,0,0,0.5769634423648767,0,2274,13711,0.9990379569704391,2276 -matmul,1x44x36xf64,linalg_xdsl,1734,4048,4045,0.0,0,1584,1658,0,0.9561707035755479,0.9987951807228915,1660,0,0,0.9573241061130334,0,0,13.719008264462811,13.71900826446281,1,0.0,121,0.6302083333333334,71,0,0,0.040945790080738176,0,2315,4052,0.9982698961937716,2317 +matmul,1x44x36xf64,linalg_xdsl,1737,4004,4001,0.0,0,1584,1658,0,0.9545192861255037,0.9987951807228915,1660,0,0,0.9556706966033391,0,0,14.067796610169493,14.067796610169491,1,0.0,118,0.6555555555555556,62,0,0,0.035693724812895795,0,2268,4008,0.9913644214162349,2270 matmul,1x44x40xf64,baseline,12702,15033,15030,0.0,0,1760,1802,0,0.14186742245315698,0.3360686311077956,5362,0,0,0.4221382459455204,0,0,1.0,1.0,1,0.0,5362,0.42250413678985105,7329,0,0,0.576995748700992,0,2332,15037,0.9991339946465124,2334 -matmul,1x44x40xf64,linalg_xdsl,1920,4246,4243,0.0,0,1760,1842,0,0.959375,0.9989154013015185,1844,0,0,0.9604166666666667,0,0,13.761194029850747,13.761194029850746,1,0.0,134,0.6442307692307693,74,0,0,0.03854166666666667,0,2327,4250,0.9989583333333334,2329 +matmul,1x44x40xf64,linalg_xdsl,1922,4236,4233,0.0,0,1760,1842,0,0.9583766909469302,0.9989154013015185,1844,0,0,0.959417273673257,0,0,13.96969696969697,13.969696969696969,1,0.0,132,0.66,68,0,0,0.03537981269510926,0,2315,4240,0.9947970863683663,2317 matmul,1x44x44xf64,baseline,13970,16312,16309,0.0,0,1936,1982,0,0.1418754473872584,0.3360461173279078,5898,0,0,0.42219040801717966,0,0,1.0,1.0,1,0.0,5898,0.4225231033741672,8061,0,0,0.5770221904080172,0,2343,16316,0.9992125984251968,2345 matmul,1x44x44xf64,linalg_xdsl,2106,4482,4479,0.0,0,1936,2026,0,0.9620132953466287,0.9990138067061144,2028,0,0,0.9629629629629629,0,0,13.795918367346939,13.795918367346939,1,0.0,147,0.65625,77,0,0,0.0365622032288699,0,2377,4486,0.9995251661918328,2379 matmul,1x44x48xf64,baseline,15238,17581,17578,0.0,0,2112,2162,0,0.14188213676335476,0.33602735467827166,6434,0,0,0.422233888961806,0,0,1.0,1.0,1,0.0,6434,0.42253891114467723,8793,0,0,0.577044231526447,0,2344,17585,0.999278120488253,2346 -matmul,1x44x48xf64,linalg_xdsl,2292,4676,4673,0.0,0,2112,2210,0,0.9642233856893543,0.9990958408679927,2212,0,0,0.9650959860383944,0,0,13.825000000000001,13.825,1,0.0,160,0.6666666666666666,80,0,0,0.034904013961605584,0,2385,4680,1.0,2387 +matmul,1x44x48xf64,linalg_xdsl,2293,4630,4627,0.0,0,2112,2210,0,0.963802878325338,0.9990958408679927,2212,0,0,0.9646750981247274,0,0,14.179487179487179,14.179487179487179,1,0.0,156,0.6964285714285714,68,0,0,0.02965547317924117,0,2338,4634,0.9943305713039686,2340 matmul,1x44x4xf64,baseline,1282,3387,3384,0.0,0,176,181,0,0.14118564742589704,0.3370577281191806,537,0,0,0.41887675507020283,0,0,1.0,1.0,1,0.0,537,0.42652899126290705,722,0,0,0.5631825273010921,0,2106,3391,0.9820592823712949,2108 matmul,1x44x4xf64,linalg_xdsl,225,2334,2331,0.0,0,176,185,0,0.8222222222222222,0.9893048128342246,187,0,0,0.8311111111111111,0,0,11.6875,11.6875,1,0.0,16,0.34782608695652173,30,0,0,0.13333333333333333,0,2110,2338,0.9644444444444444,2112 matmul,1x44x52xf64,baseline,16506,18907,18904,0.0,0,2288,2342,0,0.141887798376348,0.33601147776183643,6970,0,0,0.42227068944626195,0,0,1.0,1.0,1,0.0,6970,0.42255228857229465,9525,0,0,0.5770628862231916,0,2402,18911,0.9993335756694535,2404 matmul,1x44x52xf64,linalg_xdsl,2478,4874,4871,0.0,0,2288,2394,0,0.9661016949152542,0.9991652754590985,2396,0,0,0.966908797417272,0,0,13.849710982658959,13.84971098265896,1,0.0,173,0.67578125,83,0,0,0.03349475383373689,0,2397,4878,1.0004035512510088,2399 matmul,1x44x56xf64,baseline,17774,20162,20159,0.0,0,2464,2522,0,0.14189265218859007,0.3359978683719691,7506,0,0,0.4223022392258355,0,0,1.0,1.0,1,0.0,7506,0.42256375612227665,10257,0,0,0.5770788792618431,0,2389,20166,0.9993811184876786,2391 -matmul,1x44x56xf64,linalg_xdsl,2664,5093,5090,0.0,0,2464,2578,0,0.9677177177177178,0.9992248062015504,2580,0,0,0.9684684684684685,0,0,13.870967741935482,13.870967741935484,1,0.0,186,0.6838235294117647,86,0,0,0.03228228228228228,0,2430,5097,1.0007507507507507,2432 +matmul,1x44x56xf64,linalg_xdsl,2653,5062,5059,0.0,0,2464,2578,0,0.9717301168488504,0.9992248062015504,2580,0,0,0.9724839803995476,0,0,14.333333333333334,14.333333333333334,1,0.0,180,0.7258064516129032,68,0,0,0.025631360723709008,0,2410,5066,0.9981153411232566,2412 matmul,1x44x60xf64,baseline,19042,21455,21452,0.0,0,2640,2702,0,0.1418968595735742,0.33598607311614026,8042,0,0,0.42232958722823233,0,0,1.0,1.0,1,0.0,8042,0.4225736955493668,10989,0,0,0.5770927423589959,0,2414,21459,0.9994223295872282,2416 -matmul,1x44x60xf64,linalg_xdsl,2850,5304,5301,0.0,0,2640,2762,0,0.9691228070175438,0.9992764109985528,2764,0,0,0.9698245614035088,0,0,13.889447236180905,13.889447236180905,1,0.0,199,0.6909722222222222,89,0,0,0.031228070175438598,0,2455,5308,1.0010526315789474,2457 +matmul,1x44x60xf64,linalg_xdsl,2849,5256,5253,0.0,0,2640,2762,0,0.9694629694629695,0.9992764109985528,2764,0,0,0.9701649701649702,0,0,14.24742268041237,14.24742268041237,1,0.0,194,0.7238805970149254,74,0,0,0.025974025974025976,0,2408,5260,0.9961389961389961,2410 matmul,1x44x64xf64,baseline,20310,22748,22745,0.0,0,2816,2882,0,0.14190054160512064,0.3359757519235253,8578,0,0,0.4223535204332841,0,0,1.0,1.0,1,0.0,8578,0.42258239322134095,11721,0,0,0.5771048744460857,0,2439,22752,0.9994583948793698,2441 matmul,1x44x64xf64,linalg_xdsl,3036,5510,5507,0.0,0,2816,2946,0,0.9703557312252964,0.9993215739484396,2948,0,0,0.9710144927536232,0,0,13.905660377358492,13.90566037735849,1,0.0,212,0.6973684210526315,92,0,0,0.030303030303030304,0,2475,5514,1.0013175230566536,2477 matmul,1x44x8xf64,baseline,2564,4694,4691,0.0,0,352,361,0,0.14079563182527302,0.3364398881640261,1073,0,0,0.41848673946957876,0,0,1.0,1.0,1,0.0,1073,0.4271496815286624,1439,0,0,0.5612324492979719,0,2131,4698,0.9797191887675507,2133 matmul,1x44x8xf64,linalg_xdsl,432,2554,2551,0.0,0,352,370,0,0.8564814814814815,0.9946236559139785,372,0,0,0.8611111111111112,0,0,12.4,12.4,1,0.0,30,0.37037037037037035,51,0,0,0.11805555555555555,0,2123,2558,0.9791666666666667,2125 matmul,1x48x12xf64,baseline,4174,6332,6329,0.0,0,576,589,0,0.14111164350742691,0.3359954363947519,1753,0,0,0.41998083373263057,0,0,1.0,1.0,1,0.0,1753,0.4275609756097561,2347,0,0,0.5622903689506469,0,2159,6336,0.9822712026832774,2161 -matmul,1x48x12xf64,linalg_xdsl,681,2853,2850,0.0,0,576,602,0,0.8839941262848752,0.9966887417218543,604,0,0,0.8869309838472834,0,0,14.046511627906977,14.046511627906977,1,0.0,43,0.44329896907216493,54,0,0,0.07929515418502203,0,2173,2857,0.9662261380323054,2175 +matmul,1x48x12xf64,linalg_xdsl,668,2828,2825,0.0,0,576,602,0,0.9011976047904192,0.9966887417218543,604,0,0,0.9041916167664671,0,0,14.380952380952381,14.380952380952381,1,0.0,42,0.45161290322580644,51,0,0,0.07634730538922156,0,2161,2832,0.9805389221556886,2163 matmul,1x48x16xf64,baseline,5566,7749,7746,0.0,0,768,785,0,0.14103485447358965,0.33590072742832694,2337,0,0,0.4198706431908013,0,0,1.0,1.0,1,0.0,2337,0.4277086383601757,3127,0,0,0.561803808839382,0,2184,7753,0.9816744520301832,2186 matmul,1x48x16xf64,linalg_xdsl,883,3080,3077,0.0,0,768,802,0,0.9082672706681767,0.9975124378109452,804,0,0,0.9105322763306908,0,0,14.357142857142858,14.357142857142858,1,0.0,56,0.49557522123893805,57,0,0,0.06455266138165346,0,2198,3084,0.9750849377123443,2200 matmul,1x48x20xf64,baseline,6922,9135,9132,0.0,0,960,982,0,0.1418665125686218,0.33607118412046544,2922,0,0,0.4221323316960416,0,0,1.0,1.0,1,0.0,2922,0.4227430555555556,3990,0,0,0.5764229991331985,0,2214,9139,0.9985553308292401,2216 -matmul,1x48x20xf64,linalg_xdsl,1070,3298,3295,0.0,0,960,1002,0,0.9364485981308411,0.99800796812749,1004,0,0,0.9383177570093458,0,0,14.55072463768116,14.55072463768116,1,0.0,69,0.5348837209302325,60,0,0,0.056074766355140186,0,2229,3302,0.994392523364486,2231 +matmul,1x48x20xf64,linalg_xdsl,1079,3302,3299,0.0,0,960,1002,0,0.9286376274328082,0.99800796812749,1004,0,0,0.9304911955514366,0,0,14.76470588235294,14.764705882352942,1,0.0,68,0.544,57,0,0,0.05282669138090825,0,2224,3306,0.9833178869323448,2226 matmul,1x48x24xf64,baseline,8302,10555,10552,0.0,0,1152,1178,0,0.14189351963382318,0.3359954363947519,3506,0,0,0.4223078776198506,0,0,1.0,1.0,1,0.0,3506,0.42281717317896766,4786,0,0,0.5764875933509997,0,2254,10559,0.9987954709708504,2256 -matmul,1x48x24xf64,linalg_xdsl,1290,3507,3504,0.0,0,1152,1202,0,0.931782945736434,0.9983388704318937,1204,0,0,0.9333333333333333,0,0,14.682926829268292,14.682926829268293,1,0.0,82,0.5655172413793104,63,0,0,0.04883720930232558,0,2218,3511,0.982170542635659,2220 +matmul,1x48x24xf64,linalg_xdsl,1280,3524,3521,0.0,0,1152,1202,0,0.9390625,0.9983388704318937,1204,0,0,0.940625,0,0,15.049999999999999,15.05,1,0.0,80,0.583941605839416,57,0,0,0.04453125,0,2245,3528,0.9851562500000001,2247 matmul,1x48x28xf64,baseline,9682,11932,11929,0.0,0,1344,1374,0,0.14191282792811402,0.3359413202933985,4090,0,0,0.4224333815327412,0,0,1.0,1.0,1,0.0,4090,0.4228701406120761,5582,0,0,0.5765337740136336,0,2251,11936,0.9989671555463748,2253 -matmul,1x48x28xf64,linalg_xdsl,1480,3722,3719,0.0,0,1344,1402,0,0.9472972972972973,0.9985754985754985,1404,0,0,0.9486486486486486,0,0,14.778947368421054,14.778947368421052,1,0.0,95,0.5900621118012422,66,0,0,0.0445945945945946,0,2243,3726,0.9932432432432432,2245 +matmul,1x48x28xf64,linalg_xdsl,1484,3758,3755,0.0,0,1344,1402,0,0.944743935309973,0.9985754985754985,1404,0,0,0.9460916442048517,0,0,15.260869565217392,15.26086956521739,1,0.0,92,0.6174496644295302,57,0,0,0.03840970350404313,0,2275,3762,0.9845013477088949,2277 matmul,1x48x32xf64,baseline,11062,13354,13351,0.0,0,1536,1570,0,0.14192731874887002,0.33590072742832694,4674,0,0,0.42252757186765505,0,0,1.0,1.0,1,0.0,4674,0.42294814948873405,6377,0,0,0.5764780329054421,0,2293,13358,0.9990056047730971,2295 matmul,1x48x32xf64,linalg_xdsl,1676,4002,3999,0.0,0,1536,1602,0,0.9558472553699284,0.9987531172069826,1604,0,0,0.9570405727923628,0,0,14.851851851851853,14.851851851851851,1,0.0,108,0.6136363636363636,68,0,0,0.0405727923627685,0,2327,4006,0.9976133651551312,2329 matmul,1x48x36xf64,baseline,12442,14730,14727,0.0,0,1728,1766,0,0.14193859508117665,0.33586915176873333,5258,0,0,0.4226008680276483,0,0,1.0,1.0,1,0.0,5258,0.4229748210119862,7173,0,0,0.5765150297379843,0,2289,14734,0.9991158977656326,2291 -matmul,1x48x36xf64,linalg_xdsl,1878,4207,4204,0.0,0,1728,1802,0,0.9595314164004259,0.9988913525498891,1804,0,0,0.9605963791267306,0,0,14.909090909090908,14.909090909090908,1,0.0,121,0.6302083333333334,71,0,0,0.03780617678381257,0,2330,4211,0.9984025559105432,2332 +matmul,1x48x36xf64,linalg_xdsl,1881,4163,4160,0.0,0,1728,1802,0,0.9580010632642212,0.9988913525498891,1804,0,0,0.9590643274853801,0,0,15.288135593220337,15.288135593220339,1,0.0,118,0.6555555555555556,62,0,0,0.0329611908559277,0,2283,4167,0.9920255183413078,2285 matmul,1x48x40xf64,baseline,13822,16135,16132,0.0,0,1920,1962,0,0.1419476197366517,0.3358438890790825,5842,0,0,0.42265952828823616,0,0,1.0,1.0,1,0.0,5842,0.42299616247918326,7969,0,0,0.5765446389813341,0,2314,16139,0.9992041672695703,2316 -matmul,1x48x40xf64,linalg_xdsl,2080,4434,4431,0.0,0,1920,2002,0,0.9625,0.999001996007984,2004,0,0,0.9634615384615385,0,0,14.955223880597016,14.955223880597014,1,0.0,134,0.6442307692307693,74,0,0,0.035576923076923075,0,2355,4438,0.9990384615384615,2357 +matmul,1x48x40xf64,linalg_xdsl,2082,4413,4410,0.0,0,1920,2002,0,0.9615754082612872,0.999001996007984,2004,0,0,0.962536023054755,0,0,15.181818181818182,15.181818181818182,1,0.0,132,0.66,68,0,0,0.03266090297790586,0,2332,4417,0.995196926032661,2334 matmul,1x48x44xf64,baseline,15202,17545,17542,0.0,0,2112,2158,0,0.14195500592027366,0.33582321817615934,6426,0,0,0.4227075384817787,0,0,1.0,1.0,1,0.0,6426,0.4230136264893687,8765,0,0,0.5765688725167741,0,2344,17549,0.9992764109985528,2346 matmul,1x48x44xf64,linalg_xdsl,2282,4666,4663,0.0,0,2112,2202,0,0.964943032427695,0.9990925589836661,2204,0,0,0.9658194566170026,0,0,14.993197278911563,14.993197278911564,1,0.0,147,0.65625,77,0,0,0.03374233128834356,0,2385,4670,0.9995617879053462,2387 matmul,1x48x48xf64,baseline,16582,18974,18971,0.0,0,2304,2354,0,0.14196116270654927,0.33580599144079887,7010,0,0,0.42274755759257027,0,0,1.0,1.0,1,0.0,7010,0.42302818176332146,9561,0,0,0.5765890724882402,0,2393,18978,0.9993366300808104,2395 -matmul,1x48x48xf64,linalg_xdsl,2484,4910,4907,0.0,0,2304,2402,0,0.966988727858293,0.9991680532445923,2404,0,0,0.9677938808373591,0,0,15.024999999999999,15.025,1,0.0,160,0.6666666666666666,80,0,0,0.0322061191626409,0,2427,4914,1.0,2429 +matmul,1x48x48xf64,linalg_xdsl,2485,4885,4882,0.0,0,2304,2402,0,0.9665995975855131,0.9991680532445923,2404,0,0,0.9674044265593561,0,0,15.41025641025641,15.41025641025641,1,0.0,156,0.6964285714285714,68,0,0,0.027364185110663984,0,2401,4889,0.9947686116700201,2403 matmul,1x48x4xf64,baseline,1394,3504,3501,0.0,0,192,197,0,0.14131994261119082,0.3367521367521368,585,0,0,0.41965566714490676,0,0,1.0,1.0,1,0.0,585,0.42669584245076586,786,0,0,0.563845050215208,0,2111,3508,0.9835007173601148,2113 matmul,1x48x4xf64,linalg_xdsl,241,2350,2347,0.0,0,192,201,0,0.8340248962655602,0.9901477832512315,203,0,0,0.8423236514522822,0,0,12.6875,12.6875,1,0.0,16,0.34782608695652173,30,0,0,0.12448132780082988,0,2110,2354,0.966804979253112,2112 matmul,1x48x52xf64,baseline,17962,20355,20352,0.0,0,2496,2550,0,0.14196637345507182,0.33579141427442716,7594,0,0,0.4227814274579668,0,0,1.0,1.0,1,0.0,7594,0.42304049913653835,10357,0,0,0.5766061685781093,0,2394,20359,0.9993875960360761,2396 matmul,1x48x52xf64,linalg_xdsl,2686,5120,5117,0.0,0,2496,2602,0,0.9687267311988086,0.999231950844854,2604,0,0,0.9694713328369322,0,0,15.052023121387283,15.052023121387283,1,0.0,173,0.67578125,83,0,0,0.03090096798212956,0,2435,5124,1.0003723008190617,2437 matmul,1x48x56xf64,baseline,19342,21760,21757,0.0,0,2688,2746,0,0.14197084065763624,0.33577891905111273,8178,0,0,0.42281046427463553,0,0,1.0,1.0,1,0.0,8178,0.4230510578862966,11153,0,0,0.5766208251473477,0,2419,21764,0.9994312894219832,2421 -matmul,1x48x56xf64,linalg_xdsl,2888,5347,5344,0.0,0,2688,2802,0,0.9702216066481995,0.9992867332382311,2804,0,0,0.9709141274238227,0,0,15.0752688172043,15.075268817204302,1,0.0,186,0.6838235294117647,86,0,0,0.029778393351800554,0,2460,5351,1.0006925207756232,2462 +matmul,1x48x56xf64,linalg_xdsl,2877,5316,5313,0.0,0,2688,2802,0,0.9739311783107404,0.9992867332382311,2804,0,0,0.9746263468891206,0,0,15.577777777777778,15.577777777777778,1,0.0,180,0.7258064516129032,68,0,0,0.023635731664928744,0,2440,5320,0.9982620785540494,2442 matmul,1x48x60xf64,baseline,20722,23165,23162,0.0,0,2880,2942,0,0.14197471286555352,0.3357680894772883,8762,0,0,0.4228356336260979,0,0,1.0,1.0,1,0.0,8762,0.4230602095504804,11949,0,0,0.5766335295820867,0,2444,23169,0.9994691632081846,2446 -matmul,1x48x60xf64,linalg_xdsl,3090,5574,5571,0.0,0,2880,3002,0,0.9715210355987055,0.9993342210386151,3004,0,0,0.972168284789644,0,0,15.095477386934673,15.095477386934673,1,0.0,199,0.6909722222222222,89,0,0,0.028802588996763755,0,2485,5578,1.0009708737864078,2487 +matmul,1x48x60xf64,linalg_xdsl,3089,5526,5523,0.0,0,2880,3002,0,0.9718355454839754,0.9993342210386151,3004,0,0,0.9724830042084817,0,0,15.484536082474227,15.484536082474227,1,0.0,194,0.7238805970149254,74,0,0,0.02395597280673357,0,2438,5530,0.9964389770152152,2440 matmul,1x48x64xf64,baseline,22102,24599,24596,0.0,0,3072,3138,0,0.14197810152927337,0.33575861331050716,9346,0,0,0.4228576599402769,0,0,1.0,1.0,1,0.0,9346,0.4230682178262641,12745,0,0,0.5766446475432088,0,2498,24603,0.9995023074834857,2500 matmul,1x48x64xf64,linalg_xdsl,3292,5823,5820,0.0,0,3072,3202,0,0.9726609963547995,0.9993757802746567,3204,0,0,0.9732685297691372,0,0,15.11320754716981,15.11320754716981,1,0.0,212,0.6973684210526315,92,0,0,0.027946537059538274,0,2532,5827,1.0012150668286754,2534 matmul,1x48x8xf64,baseline,2788,4918,4915,0.0,0,384,393,0,0.140961262553802,0.3361847733105218,1169,0,0,0.41929698708751795,0,0,1.0,1.0,1,0.0,1169,0.427266081871345,1567,0,0,0.562051649928264,0,2131,4922,0.9813486370157819,2133 matmul,1x48x8xf64,linalg_xdsl,464,2586,2583,0.0,0,384,402,0,0.8663793103448276,0.995049504950495,404,0,0,0.8706896551724138,0,0,13.466666666666667,13.466666666666667,1,0.0,30,0.37037037037037035,51,0,0,0.10991379310344827,0,2123,2590,0.9806034482758621,2125 matmul,1x4x12xf64,baseline,322,2389,2386,0.0,0,36,49,0,0.15217391304347827,0.31210191082802546,157,0,0,0.48757763975155277,0,0,1.0,1.0,1,0.0,157,0.7336448598130841,57,0,0,0.17701863354037267,0,2068,2393,0.6645962732919255,2070 -matmul,1x4x12xf64,linalg_xdsl,132,2223,2220,0.0,0,48,74,0,0.5606060606060606,0.9736842105263158,76,0,0,0.5757575757575758,0,0,1.767441860465116,1.7674418604651163,1,0.0,43,0.45263157894736844,52,0,0,0.3939393939393939,0,2092,2227,0.9696969696969697,2094 +matmul,1x4x12xf64,linalg_xdsl,128,2201,2198,0.0,0,48,74,0,0.578125,0.9736842105263158,76,0,0,0.59375,0,0,1.8095238095238095,1.8095238095238095,1,0.0,42,0.46153846153846156,49,0,0,0.3828125,0,2074,2205,0.9765625,2076 matmul,1x4x16xf64,baseline,422,2503,2500,0.0,0,48,65,0,0.15402843601895735,0.31100478468899523,209,0,0,0.495260663507109,0,0,1.0,1.0,1,0.0,209,0.7411347517730497,73,0,0,0.17298578199052134,0,2082,2507,0.6682464454976303,2084 matmul,1x4x16xf64,linalg_xdsl,158,2267,2264,0.0,0,64,98,0,0.620253164556962,0.98,100,0,0,0.6329113924050633,0,0,1.7857142857142858,1.7857142857142858,1,0.0,56,0.5045045045045045,55,0,0,0.34810126582278483,0,2110,2271,0.9810126582278482,2112 matmul,1x4x20xf64,baseline,522,2594,2591,0.0,0,60,81,0,0.15517241379310345,0.3103448275862069,261,0,0,0.5,0,0,1.0,1.0,1,0.0,261,0.7457142857142857,89,0,0,0.17049808429118773,0,2073,2598,0.6704980842911877,2075 -matmul,1x4x20xf64,linalg_xdsl,184,2280,2277,0.0,0,80,122,0,0.6630434782608695,0.9838709677419355,124,0,0,0.6739130434782609,0,0,1.7971014492753623,1.7971014492753623,1,0.0,69,0.5433070866141733,58,0,0,0.31521739130434784,0,2097,2284,0.9891304347826086,2099 +matmul,1x4x20xf64,linalg_xdsl,182,2274,2271,0.0,0,80,122,0,0.6703296703296703,0.9838709677419355,124,0,0,0.6813186813186813,0,0,1.8235294117647058,1.8235294117647058,1,0.0,68,0.5528455284552846,55,0,0,0.3021978021978022,0,2093,2278,0.9835164835164836,2095 matmul,1x4x24xf64,baseline,622,2737,2734,0.0,0,72,97,0,0.15594855305466238,0.30990415335463256,313,0,0,0.5032154340836013,0,0,1.0,1.0,1,0.0,313,0.7488038277511961,105,0,0,0.16881028938906753,0,2116,2741,0.6720257234726688,2118 -matmul,1x4x24xf64,linalg_xdsl,215,2333,2330,0.0,0,96,146,0,0.6790697674418604,0.9864864864864865,148,0,0,0.6883720930232559,0,0,1.8048780487804879,1.8048780487804879,1,0.0,82,0.5734265734265734,61,0,0,0.2837209302325581,0,2119,2337,0.972093023255814,2121 +matmul,1x4x24xf64,linalg_xdsl,214,2290,2287,0.0,0,96,146,0,0.6822429906542056,0.9864864864864865,148,0,0,0.6915887850467289,0,0,1.8499999999999999,1.85,1,0.0,80,0.5925925925925926,55,0,0,0.2570093457943925,0,2077,2294,0.9485981308411214,2079 matmul,1x4x28xf64,baseline,716,2842,2839,0.0,0,84,113,0,0.15782122905027932,0.3095890410958904,365,0,0,0.5097765363128491,0,0,1.0,1.0,1,0.0,365,0.7510288065843621,121,0,0,0.16899441340782123,0,2127,2846,0.6787709497206704,2129 -matmul,1x4x28xf64,linalg_xdsl,241,2370,2367,0.0,0,112,170,0,0.7053941908713693,0.9883720930232558,172,0,0,0.7136929460580913,0,0,1.8105263157894738,1.8105263157894738,1,0.0,95,0.5974842767295597,64,0,0,0.26556016597510373,0,2130,2374,0.9792531120331951,2132 +matmul,1x4x28xf64,linalg_xdsl,250,2340,2337,0.0,0,112,170,0,0.68,0.9883720930232558,172,0,0,0.688,0,0,1.8695652173913044,1.8695652173913044,1,0.0,92,0.6258503401360545,55,0,0,0.22,0,2091,2344,0.9079999999999999,2093 matmul,1x4x32xf64,baseline,823,2927,2924,0.0,0,96,129,0,0.15674362089914945,0.30935251798561153,417,0,0,0.5066828675577156,0,0,1.0,1.0,1,0.0,417,0.7527075812274369,137,0,0,0.16646415552855406,0,2105,2931,0.6731470230862697,2107 matmul,1x4x32xf64,linalg_xdsl,273,2394,2391,0.0,0,128,194,0,0.7106227106227107,0.9897959183673469,196,0,0,0.717948717948718,0,0,1.8148148148148149,1.8148148148148149,1,0.0,108,0.6171428571428571,67,0,0,0.2454212454212454,0,2122,2398,0.9633699633699634,2124 matmul,1x4x36xf64,baseline,923,3027,3024,0.0,0,108,145,0,0.1570964247020585,0.3091684434968017,469,0,0,0.5081256771397616,0,0,1.0,1.0,1,0.0,469,0.7540192926045016,153,0,0,0.1657638136511376,0,2105,3031,0.6738894907908992,2107 -matmul,1x4x36xf64,linalg_xdsl,299,2420,2417,0.0,0,144,218,0,0.7290969899665551,0.990909090909091,220,0,0,0.7357859531772575,0,0,1.8181818181818181,1.8181818181818181,1,0.0,121,0.6335078534031413,70,0,0,0.23411371237458195,0,2122,2424,0.9698996655518395,2124 +matmul,1x4x36xf64,linalg_xdsl,293,2392,2389,0.0,0,144,218,0,0.7440273037542662,0.990909090909091,220,0,0,0.7508532423208191,0,0,1.8644067796610169,1.8644067796610169,1,0.0,118,0.659217877094972,61,0,0,0.20819112627986347,0,2100,2396,0.9590443686006825,2102 matmul,1x4x40xf64,baseline,1023,3132,3129,0.0,0,120,161,0,0.1573802541544477,0.30902111324376197,521,0,0,0.509286412512219,0,0,1.0,1.0,1,0.0,521,0.755072463768116,169,0,0,0.1652003910068426,0,2110,3136,0.6744868035190615,2112 -matmul,1x4x40xf64,linalg_xdsl,325,2451,2448,0.0,0,160,242,0,0.7446153846153846,0.9918032786885246,244,0,0,0.7507692307692307,0,0,1.8208955223880599,1.8208955223880596,1,0.0,134,0.6473429951690821,73,0,0,0.2246153846153846,0,2127,2455,0.9753846153846153,2129 +matmul,1x4x40xf64,linalg_xdsl,314,2431,2428,0.0,0,160,242,0,0.7707006369426752,0.9918032786885246,244,0,0,0.7770700636942676,0,0,1.8484848484848484,1.8484848484848484,1,0.0,132,0.6633165829145728,67,0,0,0.21337579617834396,0,2118,2435,0.9904458598726116,2120 matmul,1x4x44xf64,baseline,1123,3232,3229,0.0,0,132,177,0,0.15761353517364202,0.3089005235602094,573,0,0,0.5102404274265361,0,0,1.0,1.0,1,0.0,573,0.7559366754617414,185,0,0,0.1647373107747106,0,2110,3236,0.6749777382012467,2112 matmul,1x4x44xf64,linalg_xdsl,351,2477,2474,0.0,0,176,266,0,0.7578347578347578,0.9925373134328358,268,0,0,0.7635327635327636,0,0,1.8231292517006803,1.8231292517006803,1,0.0,147,0.6591928251121076,76,0,0,0.21652421652421652,0,2127,2481,0.98005698005698,2129 matmul,1x4x48xf64,baseline,1223,3337,3334,0.0,0,144,193,0,0.15780866721177433,0.3088,625,0,0,0.5110384300899428,0,0,1.0,1.0,1,0.0,625,0.7566585956416465,201,0,0,0.1643499591169256,0,2115,3341,0.6753883892068684,2117 -matmul,1x4x48xf64,linalg_xdsl,377,2508,2505,0.0,0,192,290,0,0.7692307692307693,0.9931506849315068,292,0,0,0.7745358090185677,0,0,1.825,1.825,1,0.0,160,0.6694560669456067,79,0,0,0.20954907161803712,0,2132,2512,0.9840848806366048,2134 +matmul,1x4x48xf64,linalg_xdsl,369,2478,2475,0.0,0,192,290,0,0.7859078590785907,0.9931506849315068,292,0,0,0.7913279132791328,0,0,1.8717948717948718,1.8717948717948718,1,0.0,156,0.6995515695067265,67,0,0,0.18157181571815717,0,2110,2482,0.9728997289972899,2112 matmul,1x4x4xf64,baseline,121,2175,2172,0.0,0,12,17,0,0.14049586776859505,0.32075471698113206,53,0,0,0.4380165289256198,0,0,1.0,1.0,1,0.0,53,0.8983050847457628,6,0,0,0.049586776859504134,0,2055,2179,0.48760330578512395,2057 matmul,1x4x4xf64,linalg_xdsl,65,2121,2118,0.0,0,16,25,0,0.38461538461538464,0.9259259259259259,27,0,0,0.4153846153846154,0,0,1.6875,1.6875,1,0.0,16,0.34782608695652173,30,0,0,0.46153846153846156,0,2057,2125,0.8769230769230769,2059 matmul,1x4x52xf64,baseline,1323,3437,3434,0.0,0,156,209,0,0.15797430083144368,0.3087149187592319,677,0,0,0.5117157974300831,0,0,1.0,1.0,1,0.0,677,0.7572706935123042,217,0,0,0.164021164021164,0,2115,3441,0.6757369614512472,2117 matmul,1x4x52xf64,linalg_xdsl,403,2534,2531,0.0,0,208,314,0,0.7791563275434243,0.9936708860759493,316,0,0,0.7841191066997518,0,0,1.8265895953757227,1.8265895953757225,1,0.0,173,0.6784313725490196,82,0,0,0.20347394540942929,0,2132,2538,0.9875930521091811,2134 matmul,1x4x56xf64,baseline,1423,3542,3539,0.0,0,168,225,0,0.15811665495432187,0.30864197530864196,729,0,0,0.5122979620520028,0,0,1.0,1.0,1,0.0,729,0.7577962577962578,233,0,0,0.16373858046380885,0,2120,3546,0.6760365425158117,2122 -matmul,1x4x56xf64,linalg_xdsl,429,2565,2562,0.0,0,224,338,0,0.7878787878787878,0.9941176470588236,340,0,0,0.7925407925407926,0,0,1.8279569892473118,1.8279569892473118,1,0.0,186,0.6863468634686347,85,0,0,0.19813519813519814,0,2137,2569,0.9906759906759908,2139 +matmul,1x4x56xf64,linalg_xdsl,420,2515,2512,0.0,0,224,338,0,0.8047619047619048,0.9941176470588236,340,0,0,0.8095238095238095,0,0,1.8888888888888888,1.8888888888888888,1,0.0,180,0.728744939271255,67,0,0,0.1595238095238095,0,2096,2519,0.969047619047619,2098 matmul,1x4x60xf64,baseline,1523,3642,3639,0.0,0,180,241,0,0.1582403151674327,0.3085787451984635,781,0,0,0.5128036769533815,0,0,1.0,1.0,1,0.0,781,0.7582524271844661,249,0,0,0.16349310571240971,0,2120,3646,0.6762967826657912,2122 -matmul,1x4x60xf64,linalg_xdsl,455,2591,2588,0.0,0,240,362,0,0.7956043956043956,0.9945054945054945,364,0,0,0.8,0,0,1.8291457286432162,1.829145728643216,1,0.0,199,0.6933797909407665,88,0,0,0.1934065934065934,0,2137,2595,0.9934065934065934,2139 +matmul,1x4x60xf64,linalg_xdsl,445,2559,2556,0.0,0,240,362,0,0.8134831460674158,0.9945054945054945,364,0,0,0.8179775280898877,0,0,1.8762886597938144,1.8762886597938144,1,0.0,194,0.7265917602996255,73,0,0,0.16404494382022472,0,2115,2563,0.9820224719101124,2117 matmul,1x4x64xf64,baseline,1621,3720,3717,0.0,0,192,257,0,0.15854410857495374,0.3085234093637455,833,0,0,0.5138803207896361,0,0,1.0,1.0,1,0.0,833,0.7586520947176685,265,0,0,0.1634793337446021,0,2100,3724,0.6773596545342382,2102 matmul,1x4x64xf64,linalg_xdsl,475,2638,2635,0.0,0,256,386,0,0.8126315789473684,0.9948453608247423,388,0,0,0.8168421052631579,0,0,1.8301886792452828,1.830188679245283,1,0.0,212,0.6996699669966997,91,0,0,0.19157894736842104,0,2164,2642,1.0084210526315789,2166 matmul,1x4x8xf64,baseline,213,2317,2314,0.0,0,24,33,0,0.15492957746478872,0.3142857142857143,105,0,0,0.49295774647887325,0,0,1.0,1.0,1,0.0,105,0.9459459459459459,6,0,0,0.028169014084507043,0,2105,2321,0.5211267605633803,2107 matmul,1x4x8xf64,linalg_xdsl,106,2210,2207,0.0,0,32,50,0,0.4716981132075472,0.9615384615384616,52,0,0,0.49056603773584906,0,0,1.7333333333333334,1.7333333333333334,1,0.0,30,0.379746835443038,49,0,0,0.46226415094339623,0,2105,2214,0.9528301886792453,2107 matmul,1x52x12xf64,baseline,4510,6673,6670,0.0,0,624,637,0,0.14124168514412416,0.33579335793357934,1897,0,0,0.42062084257206206,0,0,1.0,1.0,1,0.0,1897,0.4276375112714157,2539,0,0,0.5629711751662971,0,2164,6677,0.9835920177383592,2166 -matmul,1x52x12xf64,linalg_xdsl,729,2906,2903,0.0,0,624,650,0,0.8916323731138546,0.9969325153374233,652,0,0,0.8943758573388203,0,0,15.162790697674419,15.162790697674419,1,0.0,43,0.44329896907216493,54,0,0,0.07407407407407407,0,2178,2910,0.9684499314128944,2180 +matmul,1x52x12xf64,linalg_xdsl,716,2881,2878,0.0,0,624,650,0,0.9078212290502793,0.9969325153374233,652,0,0,0.9106145251396648,0,0,15.523809523809524,15.523809523809524,1,0.0,42,0.45161290322580644,51,0,0,0.0712290502793296,0,2166,2885,0.9818435754189944,2168 matmul,1x52x16xf64,baseline,6014,8207,8204,0.0,0,832,849,0,0.1411706019288327,0.33570581257413995,2529,0,0,0.4205187894911872,0,0,1.0,1.0,1,0.0,2529,0.4277740189445196,3383,0,0,0.5625207848353841,0,2194,8211,0.9830395743265714,2196 matmul,1x52x16xf64,linalg_xdsl,947,3154,3151,0.0,0,832,866,0,0.914466737064414,0.9976958525345622,868,0,0,0.9165786694825766,0,0,15.5,15.5,1,0.0,56,0.49557522123893805,57,0,0,0.06019007391763464,0,2208,3158,0.9767687434002112,2210 matmul,1x52x20xf64,baseline,7482,9717,9714,0.0,0,1040,1062,0,0.14194065757818766,0.33586337760910817,3162,0,0,0.42261427425821974,0,0,1.0,1.0,1,0.0,3162,0.4231798715203426,4310,0,0,0.5760491847099706,0,2236,9721,0.9986634589681903,2238 -matmul,1x52x20xf64,linalg_xdsl,1165,3397,3394,0.0,0,1040,1082,0,0.9287553648068669,0.9981549815498155,1084,0,0,0.9304721030042918,0,0,15.710144927536232,15.710144927536232,1,0.0,69,0.5348837209302325,60,0,0,0.05150214592274678,0,2233,3401,0.9819742489270387,2235 +matmul,1x52x20xf64,linalg_xdsl,1159,3359,3356,0.0,0,1040,1082,0,0.9335634167385677,0.9981549815498155,1084,0,0,0.9352890422778257,0,0,15.941176470588236,15.941176470588236,1,0.0,68,0.544,57,0,0,0.04918032786885246,0,2201,3363,0.9844693701466782,2203 matmul,1x52x24xf64,baseline,8974,11232,11229,0.0,0,1248,1274,0,0.1419656786271451,0.33579335793357934,3794,0,0,0.42277691107644305,0,0,1.0,1.0,1,0.0,3794,0.4232485497545739,5170,0,0,0.5761087586360597,0,2259,11236,0.9988856697125028,2261 -matmul,1x52x24xf64,linalg_xdsl,1386,3626,3623,0.0,0,1248,1298,0,0.9365079365079365,0.9984615384615385,1300,0,0,0.937950937950938,0,0,15.853658536585366,15.853658536585366,1,0.0,82,0.5655172413793104,63,0,0,0.045454545454545456,0,2241,3630,0.9834054834054834,2243 +matmul,1x52x24xf64,linalg_xdsl,1374,3641,3638,0.0,0,1248,1298,0,0.9446870451237264,0.9984615384615385,1300,0,0,0.9461426491994177,0,0,16.25,16.25,1,0.0,80,0.583941605839416,57,0,0,0.04148471615720524,0,2268,3645,0.987627365356623,2270 matmul,1x52x28xf64,baseline,10466,12731,12728,0.0,0,1456,1486,0,0.1419835658322186,0.3357433348395843,4426,0,0,0.422893177909421,0,0,1.0,1.0,1,0.0,4426,0.42329762815608263,6030,0,0,0.5761513472195682,0,2266,12735,0.9990445251289892,2268 -matmul,1x52x28xf64,linalg_xdsl,1592,3849,3846,0.0,0,1456,1514,0,0.9510050251256281,0.9986807387862797,1516,0,0,0.9522613065326633,0,0,15.957894736842105,15.957894736842105,1,0.0,95,0.5900621118012422,66,0,0,0.0414572864321608,0,2258,3853,0.9937185929648241,2260 +matmul,1x52x28xf64,linalg_xdsl,1596,3885,3882,0.0,0,1456,1514,0,0.9486215538847118,0.9986807387862797,1516,0,0,0.949874686716792,0,0,16.478260869565215,16.47826086956522,1,0.0,92,0.6174496644295302,57,0,0,0.03571428571428571,0,2290,3889,0.9855889724310777,2292 matmul,1x52x32xf64,baseline,11958,14241,14238,0.0,0,1664,1698,0,0.14199698946312092,0.33570581257413995,5058,0,0,0.422980431510286,0,0,1.0,1.0,1,0.0,5058,0.42336988365279987,6889,0,0,0.5760996822211072,0,2284,14245,0.9990801137313932,2286 matmul,1x52x32xf64,linalg_xdsl,1804,4128,4125,0.0,0,1664,1730,0,0.958980044345898,0.9988452655889145,1732,0,0,0.9600886917960089,0,0,16.037037037037038,16.037037037037038,1,0.0,108,0.6136363636363636,68,0,0,0.037694013303769404,0,2325,4132,0.9977827050997783,2327 matmul,1x52x36xf64,baseline,13450,15758,15755,0.0,0,1872,1910,0,0.14200743494423793,0.335676625659051,5690,0,0,0.4230483271375465,0,0,1.0,1.0,1,0.0,5690,0.42339459781233724,7749,0,0,0.5761338289962825,0,2309,15762,0.999182156133829,2311 -matmul,1x52x36xf64,linalg_xdsl,2022,4371,4368,0.0,0,1872,1946,0,0.9624134520276953,0.9989733059548255,1948,0,0,0.963402571711177,0,0,16.09917355371901,16.09917355371901,1,0.0,121,0.6302083333333334,71,0,0,0.0351137487636004,0,2350,4375,0.9985163204747775,2352 +matmul,1x52x36xf64,linalg_xdsl,2025,4332,4329,0.0,0,1872,1946,0,0.9609876543209876,0.9989733059548255,1948,0,0,0.9619753086419753,0,0,16.508474576271187,16.508474576271187,1,0.0,118,0.6555555555555556,62,0,0,0.030617283950617285,0,2308,4336,0.9925925925925926,2310 matmul,1x52x40xf64,baseline,14942,17280,17277,0.0,0,2080,2122,0,0.14201579440503279,0.33565327428029107,6322,0,0,0.42310266363271315,0,0,1.0,1.0,1,0.0,6322,0.4234143727814614,8609,0,0,0.5761611564716905,0,2339,17284,0.9992638201044037,2341 -matmul,1x52x40xf64,linalg_xdsl,2240,4619,4616,0.0,0,2080,2162,0,0.9651785714285714,0.9990757855822551,2164,0,0,0.9660714285714286,0,0,16.149253731343283,16.149253731343283,1,0.0,134,0.6442307692307693,74,0,0,0.033035714285714286,0,2380,4623,0.9991071428571429,2382 +matmul,1x52x40xf64,linalg_xdsl,2242,4598,4595,0.0,0,2080,2162,0,0.9643175735950045,0.9990757855822551,2164,0,0,0.9652096342551294,0,0,16.393939393939394,16.393939393939394,1,0.0,132,0.66,68,0,0,0.030330062444246207,0,2357,4602,0.9955396966993756,2359 matmul,1x52x44xf64,baseline,16434,18835,18832,0.0,0,2288,2334,0,0.14202263599853962,0.3356341673856773,6954,0,0,0.42314713399050746,0,0,1.0,1.0,1,0.0,6954,0.42343055470985813,9469,0,0,0.5761835219666545,0,2402,18839,0.999330655957162,2404 matmul,1x52x44xf64,linalg_xdsl,2459,4855,4852,0.0,0,2288,2378,0,0.967059780398536,0.9991596638655462,2380,0,0,0.9678731191541277,0,0,16.19047619047619,16.19047619047619,1,0.0,147,0.65625,77,0,0,0.0313135420902806,0,2397,4859,0.9991866612444082,2399 matmul,1x52x48xf64,baseline,17926,20319,20316,0.0,0,2496,2546,0,0.14202833872587303,0.33561824413393093,7586,0,0,0.4231842017181747,0,0,1.0,1.0,1,0.0,7586,0.42344404130616803,10329,0,0,0.5762021644538659,0,2394,20323,0.9993863661720406,2396 -matmul,1x52x48xf64,linalg_xdsl,2676,5110,5107,0.0,0,2496,2594,0,0.9693572496263079,0.9992295839753467,2596,0,0,0.9701046337817638,0,0,16.224999999999998,16.225,1,0.0,160,0.6666666666666666,80,0,0,0.029895366218236172,0,2435,5114,1.0,2437 +matmul,1x52x48xf64,linalg_xdsl,2677,5064,5061,0.0,0,2496,2594,0,0.9689951438177064,0.9992295839753467,2596,0,0,0.9697422487859544,0,0,16.641025641025642,16.641025641025642,1,0.0,156,0.6964285714285714,68,0,0,0.02540156892043332,0,2388,5068,0.9951438177063877,2390 matmul,1x52x4xf64,baseline,1523,3643,3640,0.0,0,208,213,0,0.13985554826001312,0.33649289099526064,633,0,0,0.4156270518713066,0,0,1.0,1.0,1,0.0,633,0.42654986522911054,851,0,0,0.5587655942219304,0,2121,3647,0.9743926460932371,2123 matmul,1x52x4xf64,linalg_xdsl,262,2402,2399,0.0,0,208,217,0,0.8282442748091603,0.9908675799086758,219,0,0,0.8358778625954199,0,0,13.6875,13.6875,1,0.0,16,0.3404255319148936,31,0,0,0.1183206106870229,0,2141,2406,0.9541984732824428,2143 matmul,1x52x52xf64,baseline,19418,21865,21862,0.0,0,2704,2758,0,0.14203316510454217,0.33560477001703576,8218,0,0,0.42321557317952413,0,0,1.0,1.0,1,0.0,8218,0.4234554542175504,11189,0,0,0.5762179421155629,0,2448,21869,0.9994335152950871,2450 matmul,1x52x52xf64,linalg_xdsl,2894,5370,5367,0.0,0,2704,2810,0,0.9709744298548721,0.9992887624466572,2812,0,0,0.9716655148583275,0,0,16.254335260115607,16.254335260115607,1,0.0,173,0.67578125,83,0,0,0.02868002764340014,0,2477,5374,1.0003455425017276,2479 matmul,1x52x56xf64,baseline,20910,23358,23355,0.0,0,2912,2970,0,0.14203730272596843,0.33559322033898303,8850,0,0,0.4232424677187948,0,0,1.0,1.0,1,0.0,8850,0.42346523757117566,12049,0,0,0.5762314681970349,0,2449,23362,0.9994739359158297,2451 -matmul,1x52x56xf64,linalg_xdsl,3112,5601,5598,0.0,0,2912,3026,0,0.9723650385604113,0.9993394980184941,3028,0,0,0.9730077120822622,0,0,16.27956989247312,16.27956989247312,1,0.0,186,0.6838235294117647,86,0,0,0.027634961439588688,0,2490,5605,1.000642673521851,2492 +matmul,1x52x56xf64,linalg_xdsl,3101,5570,5567,0.0,0,2912,3026,0,0.9758142534666236,0.9993394980184941,3028,0,0,0.9764592067075137,0,0,16.82222222222222,16.822222222222223,1,0.0,180,0.7258064516129032,68,0,0,0.021928410190261205,0,2470,5574,0.998387616897775,2472 matmul,1x52x60xf64,baseline,22402,24880,24877,0.0,0,3120,3182,0,0.14204088920632085,0.3355832102931871,9482,0,0,0.4232657798410856,0,0,1.0,1.0,1,0.0,9482,0.4234737171184851,12909,0,0,0.5762431925720918,0,2479,24884,0.9995089724131774,2481 -matmul,1x52x60xf64,linalg_xdsl,3330,5849,5846,0.0,0,3120,3242,0,0.9735735735735735,0.9993834771886559,3244,0,0,0.9741741741741742,0,0,16.30150753768844,16.301507537688444,1,0.0,199,0.6909722222222222,89,0,0,0.026726726726726727,0,2520,5853,1.000900900900901,2522 +matmul,1x52x60xf64,linalg_xdsl,3329,5796,5793,0.0,0,3120,3242,0,0.9738660258335836,0.9993834771886559,3244,0,0,0.9744668068489035,0,0,16.721649484536083,16.721649484536083,1,0.0,194,0.7238805970149254,74,0,0,0.022228897566836887,0,2468,5800,0.9966957044157404,2470 matmul,1x52x64xf64,baseline,23894,26397,26394,0.0,0,3328,3394,0,0.1420440277894032,0.3355744512556852,10114,0,0,0.4232861806311208,0,0,1.0,1.0,1,0.0,10114,0.4234811372105682,13769,0,0,0.5762534527496442,0,2504,26401,0.999539633380765,2506 matmul,1x52x64xf64,linalg_xdsl,3548,6092,6089,0.0,0,3328,3458,0,0.9746335963923337,0.999421965317919,3460,0,0,0.9751972942502819,0,0,16.32075471698113,16.32075471698113,1,0.0,212,0.6973684210526315,92,0,0,0.02593010146561443,0,2545,6096,1.0011273957158964,2547 matmul,1x52x8xf64,baseline,3012,5147,5144,0.0,0,416,425,0,0.1411022576361222,0.3359683794466403,1265,0,0,0.4199867197875166,0,0,1.0,1.0,1,0.0,1265,0.42736486486486486,1695,0,0,0.5627490039840638,0,2136,5151,0.9827357237715804,2138 matmul,1x52x8xf64,linalg_xdsl,496,2623,2620,0.0,0,416,434,0,0.875,0.9954128440366973,436,0,0,0.8790322580645161,0,0,14.533333333333333,14.533333333333333,1,0.0,30,0.37037037037037035,51,0,0,0.1028225806451613,0,2128,2627,0.9818548387096774,2130 matmul,1x56x12xf64,baseline,4846,7014,7011,0.0,0,672,685,0,0.14135369376805612,0.33561979421852034,2041,0,0,0.4211721007016096,0,0,1.0,1.0,1,0.0,2041,0.4277032690695725,2731,0,0,0.5635575732562939,0,2169,7018,0.9847296739579035,2171 -matmul,1x56x12xf64,linalg_xdsl,777,2959,2956,0.0,0,672,698,0,0.8983268983268984,0.9971428571428571,700,0,0,0.9009009009009009,0,0,16.27906976744186,16.27906976744186,1,0.0,43,0.44329896907216493,54,0,0,0.0694980694980695,0,2183,2963,0.9703989703989704,2185 +matmul,1x56x12xf64,linalg_xdsl,764,2934,2931,0.0,0,672,698,0,0.9136125654450262,0.9971428571428571,700,0,0,0.9162303664921466,0,0,16.666666666666668,16.666666666666668,1,0.0,42,0.45161290322580644,51,0,0,0.06675392670157068,0,2171,2938,0.9829842931937173,2173 matmul,1x56x16xf64,baseline,6462,8660,8657,0.0,0,896,913,0,0.14128752708139894,0.33553840499816245,2721,0,0,0.42107706592386257,0,0,1.0,1.0,1,0.0,2721,0.42783018867924527,3639,0,0,0.5631383472609099,0,2199,8664,0.9842154131847725,2201 matmul,1x56x16xf64,linalg_xdsl,1011,3223,3220,0.0,0,896,930,0,0.9198813056379822,0.9978540772532188,932,0,0,0.9218595450049456,0,0,16.642857142857142,16.642857142857142,1,0.0,56,0.49557522123893805,57,0,0,0.05637982195845697,0,2213,3227,0.9782393669634025,2215 matmul,1x56x20xf64,baseline,8042,10287,10284,0.0,0,1120,1142,0,0.1420044764983835,0.3356848912404468,3402,0,0,0.42302909723949267,0,0,1.0,1.0,1,0.0,3402,0.4235557768924303,4630,0,0,0.5757274309873166,0,2246,10291,0.9987565282268093,2248 -matmul,1x56x20xf64,linalg_xdsl,1245,3487,3484,0.0,0,1120,1162,0,0.9333333333333333,0.9982817869415808,1164,0,0,0.9349397590361446,0,0,16.8695652173913,16.869565217391305,1,0.0,69,0.5348837209302325,60,0,0,0.04819277108433735,0,2243,3491,0.983132530120482,2245 +matmul,1x56x20xf64,linalg_xdsl,1239,3444,3441,0.0,0,1120,1162,0,0.9378531073446328,0.9982817869415808,1164,0,0,0.9394673123486683,0,0,17.117647058823533,17.11764705882353,1,0.0,68,0.544,57,0,0,0.04600484261501211,0,2206,3448,0.9854721549636805,2208 matmul,1x56x24xf64,baseline,9646,11924,11921,0.0,0,1344,1370,0,0.1420277835372175,0.33561979421852034,4082,0,0,0.42318059299191374,0,0,1.0,1.0,1,0.0,4082,0.4236197592361976,5554,0,0,0.5757827078581795,0,2279,11928,0.9989633008500933,2281 -matmul,1x56x24xf64,linalg_xdsl,1482,3724,3721,0.0,0,1344,1394,0,0.9406207827260459,0.998567335243553,1396,0,0,0.941970310391363,0,0,17.024390243902438,17.024390243902438,1,0.0,82,0.5655172413793104,63,0,0,0.04251012145748988,0,2243,3728,0.9844804318488529,2245 +matmul,1x56x24xf64,linalg_xdsl,1472,3741,3738,0.0,0,1344,1394,0,0.9470108695652174,0.998567335243553,1396,0,0,0.9483695652173914,0,0,17.45,17.45,1,0.0,80,0.583941605839416,57,0,0,0.03872282608695652,0,2270,3745,0.9870923913043479,2272 matmul,1x56x28xf64,baseline,11250,13530,13527,0.0,0,1568,1598,0,0.14204444444444445,0.3355732885342293,4762,0,0,0.4232888888888889,0,0,1.0,1.0,1,0.0,4762,0.42366548042704627,6478,0,0,0.5758222222222222,0,2281,13534,0.9991111111111111,2283 -matmul,1x56x28xf64,linalg_xdsl,1704,3976,3973,0.0,0,1568,1626,0,0.954225352112676,0.9987714987714987,1628,0,0,0.9553990610328639,0,0,17.136842105263156,17.13684210526316,1,0.0,95,0.5900621118012422,66,0,0,0.03873239436619718,0,2273,3980,0.994131455399061,2275 +matmul,1x56x28xf64,linalg_xdsl,1708,4012,4009,0.0,0,1568,1626,0,0.9519906323185011,0.9987714987714987,1628,0,0,0.9531615925058547,0,0,17.695652173913047,17.695652173913043,1,0.0,92,0.6174496644295302,57,0,0,0.03337236533957846,0,2305,4016,0.9865339578454332,2307 matmul,1x56x32xf64,baseline,12854,15152,15149,0.0,0,1792,1826,0,0.14205694725377316,0.33553840499816245,5442,0,0,0.4233701571495254,0,0,1.0,1.0,1,0.0,5442,0.423732772716655,7401,0,0,0.575774078107982,0,2299,15156,0.9991442352575074,2301 matmul,1x56x32xf64,linalg_xdsl,1932,4271,4268,0.0,0,1792,1858,0,0.9616977225672878,0.9989247311827957,1860,0,0,0.9627329192546584,0,0,17.22222222222222,17.22222222222222,1,0.0,108,0.6136363636363636,68,0,0,0.035196687370600416,0,2340,4275,0.9979296066252589,2342 matmul,1x56x36xf64,baseline,14458,16786,16783,0.0,0,2016,2054,0,0.1420666758887813,0.33551127082652726,6122,0,0,0.4234333932770784,0,0,1.0,1.0,1,0.0,6122,0.4237557970512909,8325,0,0,0.5758057822658735,0,2329,16790,0.9992391755429519,2331 -matmul,1x56x36xf64,linalg_xdsl,2166,4535,4532,0.0,0,2016,2090,0,0.9649122807017544,0.9990439770554493,2092,0,0,0.9658356417359187,0,0,17.289256198347108,17.289256198347108,1,0.0,121,0.6302083333333334,71,0,0,0.03277931671283472,0,2370,4539,0.9986149584487535,2372 +matmul,1x56x36xf64,linalg_xdsl,2169,4491,4488,0.0,0,2016,2090,0,0.9635776855693868,0.9990439770554493,2092,0,0,0.9644997694790226,0,0,17.728813559322035,17.728813559322035,1,0.0,118,0.6555555555555556,62,0,0,0.02858460119870908,0,2323,4495,0.9930843706777317,2325 matmul,1x56x40xf64,baseline,16062,18420,18417,0.0,0,2240,2282,0,0.1420744614618354,0.3354895618935607,6802,0,0,0.42348399950193,0,0,1.0,1.0,1,0.0,6802,0.4237742196747866,9249,0,0,0.5758311542771759,0,2359,18424,0.9993151537791058,2361 -matmul,1x56x40xf64,linalg_xdsl,2400,4799,4796,0.0,0,2240,2322,0,0.9675,0.9991394148020654,2324,0,0,0.9683333333333334,0,0,17.34328358208955,17.34328358208955,1,0.0,134,0.6442307692307693,74,0,0,0.030833333333333334,0,2400,4803,0.9991666666666668,2402 +matmul,1x56x40xf64,linalg_xdsl,2402,4778,4775,0.0,0,2240,2322,0,0.9666944213155704,0.9991394148020654,2324,0,0,0.9675270607826811,0,0,17.606060606060606,17.606060606060606,1,0.0,132,0.66,68,0,0,0.028309741881765195,0,2377,4782,0.9958368026644463,2379 matmul,1x56x44xf64,baseline,17666,20054,20051,0.0,0,2464,2510,0,0.14208083323899015,0.3354717989842288,7482,0,0,0.42352541605343597,0,0,1.0,1.0,1,0.0,7482,0.4237892948173322,10173,0,0,0.5758519189403374,0,2389,20058,0.9993773349937733,2391 matmul,1x56x44xf64,linalg_xdsl,2634,5063,5060,0.0,0,2464,2554,0,0.9696279422930904,0.9992175273865415,2556,0,0,0.9703872437357631,0,0,17.387755102040817,17.387755102040817,1,0.0,147,0.65625,77,0,0,0.029233105542900532,0,2430,5067,0.9996203492786636,2432 matmul,1x56x48xf64,baseline,19270,21688,21685,0.0,0,2688,2738,0,0.142086144265698,0.33545699583435434,8162,0,0,0.4235599377270368,0,0,1.0,1.0,1,0.0,8162,0.4238018588711771,11097,0,0,0.5758692267773742,0,2419,21692,0.999429164504411,2421 -matmul,1x56x48xf64,linalg_xdsl,2868,5327,5324,0.0,0,2688,2786,0,0.9714086471408647,0.9992826398852224,2788,0,0,0.9721059972105998,0,0,17.425,17.425,1,0.0,160,0.6666666666666666,80,0,0,0.02789400278940028,0,2460,5331,1.0,2462 +matmul,1x56x48xf64,linalg_xdsl,2869,5276,5273,0.0,0,2688,2786,0,0.9710700592540955,0.9992826398852224,2788,0,0,0.9717671662600209,0,0,17.871794871794872,17.871794871794872,1,0.0,156,0.6964285714285714,68,0,0,0.023701638201463926,0,2408,5280,0.9954688044614848,2410 matmul,1x56x4xf64,baseline,1635,3755,3752,0.0,0,224,229,0,0.1400611620795107,0.33627019089574156,681,0,0,0.41651376146788993,0,0,1.0,1.0,1,0.0,681,0.4266917293233083,915,0,0,0.5596330275229358,0,2121,3759,0.9761467889908257,2123 matmul,1x56x4xf64,linalg_xdsl,278,2418,2415,0.0,0,224,233,0,0.8381294964028777,0.9914893617021276,235,0,0,0.8453237410071942,0,0,14.6875,14.6875,1,0.0,16,0.3404255319148936,31,0,0,0.11151079136690648,0,2141,2422,0.9568345323741007,2143 matmul,1x56x52xf64,baseline,20874,23322,23319,0.0,0,2912,2966,0,0.14209063907253042,0.3354444695770188,8842,0,0,0.42358915397144775,0,0,1.0,1.0,1,0.0,8842,0.4238124910127978,12021,0,0,0.5758838746766313,0,2449,23326,0.9994730286480791,2451 matmul,1x56x52xf64,linalg_xdsl,3102,5591,5588,0.0,0,2912,3018,0,0.9729206963249516,0.9993377483443708,3020,0,0,0.973565441650548,0,0,17.45664739884393,17.45664739884393,1,0.0,173,0.67578125,83,0,0,0.02675693101225016,0,2490,5595,1.000322372662798,2492 matmul,1x56x56xf64,baseline,22478,24980,24977,0.0,0,3136,3194,0,0.1420944923925616,0.33543373240915775,9522,0,0,0.4236142005516505,0,0,1.0,1.0,1,0.0,9522,0.42382160502069705,12945,0,0,0.5758964320669099,0,2503,24984,0.9995106326185603,2505 -matmul,1x56x56xf64,linalg_xdsl,3336,5872,5869,0.0,0,3136,3250,0,0.9742206235011991,0.9993849938499385,3252,0,0,0.9748201438848921,0,0,17.483870967741936,17.483870967741936,1,0.0,186,0.6838235294117647,86,0,0,0.02577937649880096,0,2537,5876,1.000599520383693,2539 +matmul,1x56x56xf64,linalg_xdsl,3324,5803,5800,0.0,0,3136,3250,0,0.9777376654632972,0.9993849938499385,3252,0,0,0.9783393501805054,0,0,18.066666666666666,18.066666666666666,1,0.0,180,0.7258064516129032,68,0,0,0.02045728038507822,0,2480,5807,0.9987966305655837,2482 matmul,1x56x60xf64,baseline,24082,26590,26587,0.0,0,3360,3422,0,0.14209783240594634,0.33542442658302296,10202,0,0,0.42363591063865125,0,0,1.0,1.0,1,0.0,10202,0.4238295043828674,13869,0,0,0.5759073166680508,0,2509,26594,0.9995432273067021,2511 -matmul,1x56x60xf64,linalg_xdsl,3570,6119,6116,0.0,0,3360,3482,0,0.9753501400560224,0.9994259471871412,3484,0,0,0.9759103641456582,0,0,17.50753768844221,17.507537688442213,1,0.0,199,0.6909722222222222,89,0,0,0.02492997198879552,0,2550,6123,1.0008403361344538,2552 +matmul,1x56x60xf64,linalg_xdsl,3569,6066,6063,0.0,0,3360,3482,0,0.9756234239282712,0.9994259471871412,3484,0,0,0.9761838049873914,0,0,17.95876288659794,17.95876288659794,1,0.0,194,0.7238805970149254,74,0,0,0.020734099187447463,0,2498,6070,0.9969179041748389,2500 matmul,1x56x64xf64,baseline,25686,28248,28245,0.0,0,3584,3650,0,0.1421007552752472,0.33541628377136556,10882,0,0,0.42365490928910693,0,0,1.0,1.0,1,0.0,10882,0.42383641674780914,14793,0,0,0.5759168418593786,0,2563,28252,0.9995717511484856,2565 matmul,1x56x64xf64,linalg_xdsl,3804,6400,6397,0.0,0,3584,3714,0,0.9763406940063092,0.9994617868675996,3716,0,0,0.9768664563617245,0,0,17.528301886792452,17.528301886792452,1,0.0,212,0.6973684210526315,92,0,0,0.024185068349106203,0,2597,6404,1.0010515247108307,2599 matmul,1x56x8xf64,baseline,3236,5376,5373,0.0,0,448,457,0,0.14122373300370827,0.3357825128581925,1361,0,0,0.42058096415327567,0,0,1.0,1.0,1,0.0,1361,0.4274497487437186,1823,0,0,0.5633498145859085,0,2141,5380,0.9839307787391842,2143 matmul,1x56x8xf64,linalg_xdsl,528,2660,2657,0.0,0,448,466,0,0.8825757575757576,0.9957264957264957,468,0,0,0.8863636363636364,0,0,15.6,15.6,1,0.0,30,0.37037037037037035,51,0,0,0.09659090909090909,0,2133,2664,0.9829545454545454,2135 matmul,1x60x12xf64,baseline,5182,7331,7328,0.0,0,720,733,0,0.14145117715167888,0.3354691075514874,2185,0,0,0.4216518718641451,0,0,1.0,1.0,1,0.0,2185,0.42776037588097104,2923,0,0,0.5640679274411424,0,2150,7335,0.9857197993052875,2152 -matmul,1x60x12xf64,linalg_xdsl,825,3015,3012,0.0,0,720,746,0,0.9042424242424243,0.9973262032085561,748,0,0,0.9066666666666666,0,0,17.3953488372093,17.3953488372093,1,0.0,43,0.44329896907216493,54,0,0,0.06545454545454546,0,2191,3019,0.972121212121212,2193 +matmul,1x60x12xf64,linalg_xdsl,812,2985,2982,0.0,0,720,746,0,0.9187192118226601,0.9973262032085561,748,0,0,0.9211822660098522,0,0,17.80952380952381,17.80952380952381,1,0.0,42,0.45161290322580644,51,0,0,0.06280788177339902,0,2174,2989,0.9839901477832512,2176 matmul,1x60x16xf64,baseline,6910,9120,9117,0.0,0,960,977,0,0.14138929088277857,0.3353930655681428,2913,0,0,0.4215629522431259,0,0,1.0,1.0,1,0.0,2913,0.4278789659224442,3895,0,0,0.5636758321273516,0,2211,9124,0.9852387843704775,2213 matmul,1x60x16xf64,linalg_xdsl,1060,3293,3290,0.0,0,960,994,0,0.9377358490566038,0.9979919678714859,996,0,0,0.939622641509434,0,0,17.785714285714285,17.785714285714285,1,0.0,56,0.49557522123893805,57,0,0,0.05377358490566038,0,2234,3297,0.9933962264150944,2236 matmul,1x60x20xf64,baseline,8602,10857,10854,0.0,0,1200,1222,0,0.14205998604975587,0.3355299286106535,3642,0,0,0.42338990932341314,0,0,1.0,1.0,1,0.0,3642,0.4238826815642458,4950,0,0,0.5754475703324808,0,2256,10861,0.998837479655894,2258 -matmul,1x60x20xf64,linalg_xdsl,1325,3577,3574,0.0,0,1200,1242,0,0.9373584905660377,0.9983922829581994,1244,0,0,0.9388679245283019,0,0,18.028985507246375,18.028985507246375,1,0.0,69,0.5348837209302325,60,0,0,0.045283018867924525,0,2253,3581,0.9841509433962264,2255 +matmul,1x60x20xf64,linalg_xdsl,1319,3539,3536,0.0,0,1200,1242,0,0.9416224412433661,0.9983922829581994,1244,0,0,0.9431387414708112,0,0,18.294117647058822,18.294117647058822,1,0.0,68,0.544,57,0,0,0.043214556482183475,0,2221,3543,0.9863532979529948,2223 matmul,1x60x24xf64,baseline,10318,12611,12608,0.0,0,1440,1466,0,0.1420817987982167,0.3354691075514874,4370,0,0,0.4235316921884086,0,0,1.0,1.0,1,0.0,4370,0.4239425688785409,5938,0,0,0.5754991277379337,0,2294,12615,0.9990308199263422,2296 -matmul,1x60x24xf64,linalg_xdsl,1578,3835,3832,0.0,0,1440,1490,0,0.944233206590621,0.9986595174262735,1492,0,0,0.9455006337135615,0,0,18.195121951219512,18.195121951219512,1,0.0,82,0.5655172413793104,63,0,0,0.039923954372623575,0,2258,3839,0.985424588086185,2260 +matmul,1x60x24xf64,linalg_xdsl,1568,3852,3849,0.0,0,1440,1490,0,0.9502551020408163,0.9986595174262735,1492,0,0,0.951530612244898,0,0,18.65,18.65,1,0.0,80,0.583941605839416,57,0,0,0.03635204081632653,0,2285,3856,0.9878826530612245,2287 matmul,1x60x28xf64,baseline,12034,14329,14326,0.0,0,1680,1710,0,0.14209739072627556,0.33542565712043937,5098,0,0,0.4236330397207911,0,0,1.0,1.0,1,0.0,5098,0.4239853626081171,6926,0,0,0.5755359813860728,0,2296,14333,0.9991690211068638,2298 -matmul,1x60x28xf64,linalg_xdsl,1816,4103,4100,0.0,0,1680,1738,0,0.9570484581497798,0.9988505747126437,1740,0,0,0.9581497797356828,0,0,18.31578947368421,18.31578947368421,1,0.0,95,0.5900621118012422,66,0,0,0.03634361233480176,0,2288,4107,0.9944933920704846,2290 +matmul,1x60x28xf64,linalg_xdsl,1820,4139,4136,0.0,0,1680,1738,0,0.954945054945055,0.9988505747126437,1740,0,0,0.9560439560439561,0,0,18.913043478260867,18.91304347826087,1,0.0,92,0.6174496644295302,57,0,0,0.03131868131868132,0,2320,4143,0.9873626373626374,2322 matmul,1x60x32xf64,baseline,13750,16068,16065,0.0,0,1920,1954,0,0.1421090909090909,0.3353930655681428,5826,0,0,0.4237090909090909,0,0,1.0,1.0,1,0.0,5826,0.4240483295727491,7913,0,0,0.575490909090909,0,2319,16072,0.9992,2321 matmul,1x60x32xf64,linalg_xdsl,2060,4419,4416,0.0,0,1920,1986,0,0.9640776699029127,0.9989939637826962,1988,0,0,0.9650485436893204,0,0,18.40740740740741,18.40740740740741,1,0.0,108,0.6136363636363636,68,0,0,0.03300970873786408,0,2360,4423,0.9980582524271845,2362 matmul,1x60x36xf64,baseline,15466,17814,17811,0.0,0,2160,2198,0,0.1421181947497737,0.335367714372902,6554,0,0,0.423768265873529,0,0,1.0,1.0,1,0.0,6554,0.4240698802976383,8901,0,0,0.5755204965731282,0,2349,17818,0.9992887624466572,2351 -matmul,1x60x36xf64,linalg_xdsl,2310,4699,4696,0.0,0,2160,2234,0,0.9670995670995671,0.9991055456171736,2236,0,0,0.9679653679653679,0,0,18.479338842975206,18.479338842975206,1,0.0,121,0.6302083333333334,71,0,0,0.030735930735930735,0,2390,4703,0.9987012987012986,2392 +matmul,1x60x36xf64,linalg_xdsl,2313,4655,4652,0.0,0,2160,2234,0,0.9658452226545612,0.9991055456171736,2236,0,0,0.9667099005620406,0,0,18.94915254237288,18.949152542372882,1,0.0,118,0.6555555555555556,62,0,0,0.02680501513186338,0,2343,4659,0.993514915693904,2345 matmul,1x60x40xf64,baseline,17182,19565,19562,0.0,0,2400,2442,0,0.14212548015364918,0.33534743202416917,7282,0,0,0.4238156209987196,0,0,1.0,1.0,1,0.0,7282,0.42408712363869316,9889,0,0,0.5755441741357235,0,2384,19569,0.9993597951344431,2386 -matmul,1x60x40xf64,linalg_xdsl,2560,4979,4976,0.0,0,2400,2482,0,0.96953125,0.999194847020934,2484,0,0,0.9703125,0,0,18.53731343283582,18.53731343283582,1,0.0,134,0.6442307692307693,74,0,0,0.02890625,0,2420,4983,0.99921875,2422 +matmul,1x60x40xf64,linalg_xdsl,2562,4958,4955,0.0,0,2400,2482,0,0.9687743950039032,0.999194847020934,2484,0,0,0.9695550351288056,0,0,18.81818181818182,18.818181818181817,1,0.0,132,0.66,68,0,0,0.02654176424668228,0,2397,4962,0.9960967993754879,2399 matmul,1x60x44xf64,baseline,18898,21311,21308,0.0,0,2640,2686,0,0.1421314424806858,0.33533083645443196,8010,0,0,0.4238543761244576,0,0,1.0,1.0,1,0.0,8010,0.424101233652777,10877,0,0,0.5755635516985924,0,2414,21315,0.99941792782305,2416 matmul,1x60x44xf64,linalg_xdsl,2810,5264,5261,0.0,0,2640,2730,0,0.9715302491103203,0.9992679355783309,2732,0,0,0.9722419928825623,0,0,18.585034013605444,18.58503401360544,1,0.0,147,0.65625,77,0,0,0.027402135231316727,0,2455,5268,0.999644128113879,2457 matmul,1x60x48xf64,baseline,20614,23057,23054,0.0,0,2880,2930,0,0.1421364121470845,0.33531700617990384,8738,0,0,0.4238866789560493,0,0,1.0,1.0,1,0.0,8738,0.4241129932534097,11865,0,0,0.5755797031143883,0,2444,23061,0.9994663820704377,2446 -matmul,1x60x48xf64,linalg_xdsl,3060,5544,5541,0.0,0,2880,2978,0,0.973202614379085,0.9993288590604027,2980,0,0,0.9738562091503268,0,0,18.625,18.625,1,0.0,160,0.6666666666666666,80,0,0,0.026143790849673203,0,2485,5548,1.0,2487 +matmul,1x60x48xf64,linalg_xdsl,3061,5498,5495,0.0,0,2880,2978,0,0.9728846782097353,0.9993288590604027,2980,0,0,0.9735380594576936,0,0,19.102564102564102,19.102564102564102,1,0.0,156,0.6964285714285714,68,0,0,0.02221496243057824,0,2438,5502,0.9957530218882717,2440 matmul,1x60x4xf64,baseline,1747,3872,3869,0.0,0,240,245,0,0.14024041213508873,0.33607681755829905,729,0,0,0.41728677733257014,0,0,1.0,1.0,1,0.0,729,0.4268149882903981,979,0,0,0.5603892386949055,0,2126,3876,0.9776760160274757,2128 matmul,1x60x4xf64,linalg_xdsl,294,2439,2436,0.0,0,240,249,0,0.8469387755102041,0.9920318725099602,251,0,0,0.8537414965986394,0,0,15.6875,15.6875,1,0.0,16,0.3404255319148936,31,0,0,0.1054421768707483,0,2146,2443,0.9591836734693877,2148 matmul,1x60x52xf64,baseline,22330,24808,24805,0.0,0,3120,3174,0,0.14214061800268696,0.3353053031903655,9466,0,0,0.4239140170174653,0,0,1.0,1.0,1,0.0,9466,0.4241229445763699,12853,0,0,0.5755933721450963,0,2479,24812,0.9995073891625617,2481 matmul,1x60x52xf64,linalg_xdsl,3310,5829,5826,0.0,0,3120,3226,0,0.9746223564954682,0.9993804213135068,3228,0,0,0.9752265861027191,0,0,18.658959537572255,18.658959537572255,1,0.0,173,0.67578125,83,0,0,0.025075528700906343,0,2520,5833,1.0003021148036253,2522 matmul,1x60x56xf64,baseline,24046,26554,26551,0.0,0,3360,3418,0,0.14214422357148798,0.33529527172846774,10194,0,0,0.42393745321467186,0,0,1.0,1.0,1,0.0,10194,0.4241314749323903,13841,0,0,0.5756050902436995,0,2509,26558,0.9995425434583713,2511 -matmul,1x60x56xf64,linalg_xdsl,3560,6109,6106,0.0,0,3360,3474,0,0.9758426966292135,0.9994246260069045,3476,0,0,0.9764044943820225,0,0,18.688172043010752,18.688172043010752,1,0.0,186,0.6838235294117647,86,0,0,0.024157303370786518,0,2550,6113,1.000561797752809,2552 +matmul,1x60x56xf64,linalg_xdsl,3549,6078,6075,0.0,0,3360,3474,0,0.9788672865595942,0.9994246260069045,3476,0,0,0.9794308255846718,0,0,19.31111111111111,19.31111111111111,1,0.0,180,0.7258064516129032,68,0,0,0.019160326852634545,0,2530,6082,0.9985911524373063,2532 matmul,1x60x60xf64,baseline,25762,28329,28326,0.0,0,3600,3662,0,0.14214734880832233,0.33528657754989927,10922,0,0,0.4239577672540952,0,0,1.0,1.0,1,0.0,10922,0.42413886839346043,14829,0,0,0.5756152472634112,0,2568,28333,0.9995730145175064,2570 -matmul,1x60x60xf64,linalg_xdsl,3810,6406,6403,0.0,0,3600,3722,0,0.9769028871391076,0.9994629430719656,3724,0,0,0.9774278215223097,0,0,18.71356783919598,18.71356783919598,1,0.0,199,0.6909722222222222,89,0,0,0.023359580052493438,0,2597,6410,1.000787401574803,2599 +matmul,1x60x60xf64,linalg_xdsl,3809,6379,6376,0.0,0,3600,3722,0,0.9771593594119191,0.9994629430719656,3724,0,0,0.9776844316093463,0,0,19.195876288659793,19.195876288659793,1,0.0,194,0.7238805970149254,74,0,0,0.01942767130480441,0,2571,6383,0.9971121029141506,2573 matmul,1x60x64xf64,baseline,27478,30051,30048,0.0,0,3840,3906,0,0.1421500837033263,0.33527896995708156,11650,0,0,0.4239755440716209,0,0,1.0,1.0,1,0.0,11650,0.42414533804201404,15817,0,0,0.5756241356721741,0,2574,30055,0.9995996797437949,2576 matmul,1x60x64xf64,linalg_xdsl,4060,6674,6671,0.0,0,3840,3970,0,0.9778325123152709,0.999496475327291,3972,0,0,0.9783251231527094,0,0,18.735849056603772,18.735849056603772,1,0.0,212,0.6973684210526315,92,0,0,0.022660098522167486,0,2615,6678,1.000985221674877,2617 matmul,1x60x8xf64,baseline,3462,5610,5607,0.0,0,480,489,0,0.1412478336221837,0.335621139327385,1457,0,0,0.42085499711149627,0,0,1.0,1.0,1,0.0,1457,0.42752347417840375,1951,0,0,0.5635470826112073,0,2149,5614,0.9844020797227035,2151 matmul,1x60x8xf64,linalg_xdsl,575,2737,2734,0.0,0,480,498,0,0.8660869565217392,0.996,500,0,0,0.8695652173913043,0,0,16.666666666666668,16.666666666666668,1,0.0,30,0.37037037037037035,51,0,0,0.08869565217391304,0,2163,2741,0.9582608695652174,2165 matmul,1x64x12xf64,baseline,5518,7701,7698,0.0,0,768,781,0,0.14153678869155492,0.33533705452984114,2329,0,0,0.4220732149329467,0,0,1.0,1.0,1,0.0,2329,0.4278104335047759,3115,0,0,0.5645161290322581,0,2184,7705,0.9865893439652048,2186 -matmul,1x64x12xf64,linalg_xdsl,873,3070,3067,0.0,0,768,794,0,0.9095074455899198,0.9974874371859297,796,0,0,0.9117983963344788,0,0,18.511627906976745,18.511627906976745,1,0.0,43,0.44329896907216493,54,0,0,0.061855670103092786,0,2198,3074,0.9736540664375716,2200 +matmul,1x64x12xf64,linalg_xdsl,860,3045,3042,0.0,0,768,794,0,0.9232558139534883,0.9974874371859297,796,0,0,0.9255813953488372,0,0,18.952380952380953,18.952380952380953,1,0.0,42,0.45161290322580644,51,0,0,0.05930232558139535,0,2186,3049,0.9848837209302326,2188 matmul,1x64x16xf64,baseline,7358,9578,9575,0.0,0,1024,1041,0,0.1414786626800761,0.3352657004830918,3105,0,0,0.4219896711062789,0,0,1.0,1.0,1,0.0,3105,0.42792171995589856,4151,0,0,0.5641478662680076,0,2221,9582,0.9861375373742864,2223 matmul,1x64x16xf64,linalg_xdsl,1124,3361,3358,0.0,0,1024,1058,0,0.9412811387900356,0.9981132075471698,1060,0,0,0.9430604982206405,0,0,18.928571428571427,18.928571428571427,1,0.0,56,0.49557522123893805,57,0,0,0.050711743772241996,0,2238,3365,0.9937722419928825,2240 matmul,1x64x20xf64,baseline,9162,11432,11429,0.0,0,1280,1302,0,0.1421087098886706,0.33539412673879443,3882,0,0,0.42370661427635886,0,0,1.0,1.0,1,0.0,3882,0.4241695804195804,5270,0,0,0.5752019209779524,0,2271,11436,0.9989085352543112,2273 -matmul,1x64x20xf64,linalg_xdsl,1405,3672,3669,0.0,0,1280,1322,0,0.9409252669039145,0.9984894259818731,1324,0,0,0.9423487544483986,0,0,19.188405797101453,19.18840579710145,1,0.0,69,0.5348837209302325,60,0,0,0.042704626334519574,0,2268,3676,0.9850533807829182,2270 +matmul,1x64x20xf64,linalg_xdsl,1399,3624,3621,0.0,0,1280,1322,0,0.9449606862044317,0.9984894259818731,1324,0,0,0.9463902787705504,0,0,19.47058823529412,19.470588235294116,1,0.0,68,0.544,57,0,0,0.0407433881343817,0,2226,3628,0.9871336669049321,2228 matmul,1x64x24xf64,baseline,10990,13289,13286,0.0,0,1536,1562,0,0.1421292083712466,0.33533705452984114,4658,0,0,0.42383985441310285,0,0,1.0,1.0,1,0.0,4658,0.42422586520947175,6322,0,0,0.5752502274795268,0,2300,13293,0.9990900818926296,2302 -matmul,1x64x24xf64,linalg_xdsl,1674,3950,3947,0.0,0,1536,1586,0,0.9474313022700119,0.9987405541561712,1588,0,0,0.948626045400239,0,0,19.365853658536583,19.365853658536587,1,0.0,82,0.5655172413793104,63,0,0,0.03763440860215054,0,2277,3954,0.9862604540023895,2279 +matmul,1x64x24xf64,linalg_xdsl,1662,3964,3961,0.0,0,1536,1586,0,0.9542719614921781,0.9987405541561712,1588,0,0,0.9554753309265944,0,0,19.85,19.85,1,0.0,80,0.583941605839416,57,0,0,0.03429602888086643,0,2303,3968,0.9897713598074609,2305 matmul,1x64x28xf64,baseline,12818,15128,15125,0.0,0,1792,1822,0,0.14214386019659853,0.33529628266470374,5434,0,0,0.4239350912778905,0,0,1.0,1.0,1,0.0,5434,0.4242660836976889,7374,0,0,0.5752847558121392,0,2311,15132,0.9992198470900298,2313 -matmul,1x64x28xf64,linalg_xdsl,1928,4230,4227,0.0,0,1792,1850,0,0.9595435684647303,0.9989200863930886,1852,0,0,0.9605809128630706,0,0,19.49473684210526,19.49473684210526,1,0.0,95,0.5900621118012422,66,0,0,0.03423236514522822,0,2303,4234,0.9948132780082988,2305 +matmul,1x64x28xf64,linalg_xdsl,1932,4266,4263,0.0,0,1792,1850,0,0.9575569358178054,0.9989200863930886,1852,0,0,0.9585921325051759,0,0,20.130434782608695,20.130434782608695,1,0.0,92,0.6174496644295302,57,0,0,0.029503105590062112,0,2335,4270,0.988095238095238,2337 matmul,1x64x32xf64,baseline,14646,17003,17000,0.0,0,2048,2082,0,0.14215485456780008,0.3352657004830918,6210,0,0,0.42400655469070053,0,0,1.0,1.0,1,0.0,6210,0.4243252476938845,8425,0,0,0.5752423869998634,0,2358,17007,0.9992489416905639,2360 matmul,1x64x32xf64,linalg_xdsl,2188,4579,4576,0.0,0,2048,2114,0,0.9661791590493601,0.999054820415879,2116,0,0,0.9670932358318098,0,0,19.59259259259259,19.59259259259259,1,0.0,108,0.6136363636363636,68,0,0,0.031078610603290677,0,2392,4583,0.9981718464351005,2394 matmul,1x64x36xf64,baseline,16474,18842,18839,0.0,0,2304,2342,0,0.14216340900813404,0.33524191239622103,6986,0,0,0.4240621585528712,0,0,1.0,1.0,1,0.0,6986,0.42434550203486604,9477,0,0,0.5752701226174578,0,2369,18846,0.999332281170329,2371 -matmul,1x64x36xf64,linalg_xdsl,2454,4863,4860,0.0,0,2304,2378,0,0.9690301548492257,0.9991596638655462,2380,0,0,0.9698451507742462,0,0,19.669421487603305,19.669421487603305,1,0.0,121,0.6302083333333334,71,0,0,0.02893235533822331,0,2410,4867,0.9987775061124695,2412 +matmul,1x64x36xf64,linalg_xdsl,2457,4814,4811,0.0,0,2304,2378,0,0.9678469678469679,0.9991596638655462,2380,0,0,0.9686609686609686,0,0,20.16949152542373,20.16949152542373,1,0.0,118,0.6555555555555556,62,0,0,0.025234025234025233,0,2358,4818,0.9938949938949938,2360 matmul,1x64x40xf64,baseline,18302,20729,20726,0.0,0,2560,2602,0,0.14217025461698174,0.3352228807008503,7762,0,0,0.42410665501038136,0,0,1.0,1.0,1,0.0,7762,0.4243617079437975,10529,0,0,0.5752923177794776,0,2428,20733,0.999398972789859,2430 -matmul,1x64x40xf64,linalg_xdsl,2720,5181,5178,0.0,0,2560,2642,0,0.9713235294117647,0.9992435703479576,2644,0,0,0.9720588235294118,0,0,19.73134328358209,19.73134328358209,1,0.0,134,0.6442307692307693,74,0,0,0.027205882352941177,0,2462,5185,0.9992647058823529,2464 +matmul,1x64x40xf64,linalg_xdsl,2715,5141,5138,0.0,0,2560,2642,0,0.9731123388581953,0.9992435703479576,2644,0,0,0.9738489871086556,0,0,20.03030303030303,20.03030303030303,1,0.0,132,0.66,68,0,0,0.025046040515653775,0,2427,5145,0.9988950276243094,2429 matmul,1x64x44xf64,baseline,20130,22563,22560,0.0,0,2816,2862,0,0.1421758569299553,0.3352073085031623,8538,0,0,0.4241430700447094,0,0,1.0,1.0,1,0.0,8538,0.4243749689348377,11581,0,0,0.5753104818678589,0,2434,22567,0.9994535519125683,2436 matmul,1x64x44xf64,linalg_xdsl,2986,5460,5457,0.0,0,2816,2906,0,0.9732083054253181,0.9993122420907841,2908,0,0,0.9738780977896851,0,0,19.782312925170068,19.782312925170068,1,0.0,147,0.65625,77,0,0,0.02578700602813128,0,2475,5464,0.9996651038178165,2477 matmul,1x64x48xf64,baseline,21958,24455,24452,0.0,0,3072,3122,0,0.1421805264596047,0.33519433111445135,9314,0,0,0.4241734219874306,0,0,1.0,1.0,1,0.0,9314,0.42438602086845584,12633,0,0,0.5753256216413153,0,2498,24459,0.9994990436287459,2500 -matmul,1x64x48xf64,linalg_xdsl,3252,5783,5780,0.0,0,3072,3170,0,0.9747847478474785,0.9993694829760403,3172,0,0,0.97539975399754,0,0,19.825,19.825,1,0.0,160,0.6666666666666666,80,0,0,0.024600246002460024,0,2532,5787,1.0,2534 +matmul,1x64x48xf64,linalg_xdsl,3253,5753,5750,0.0,0,3072,3170,0,0.974485090685521,0.9993694829760403,3172,0,0,0.9750999077774362,0,0,20.333333333333336,20.333333333333332,1,0.0,156,0.6964285714285714,68,0,0,0.02090378112511528,0,2501,5757,0.9960036889025514,2503 matmul,1x64x4xf64,baseline,1859,3951,3948,0.0,0,256,261,0,0.14039806347498654,0.3359073359073359,777,0,0,0.4179666487358795,0,0,1.0,1.0,1,0.0,777,0.4269230769230769,1043,0,0,0.5610543302850995,0,2093,3955,0.9790209790209791,2095 matmul,1x64x4xf64,linalg_xdsl,316,2458,2455,0.0,0,256,265,0,0.8386075949367089,0.9925093632958801,267,0,0,0.8449367088607594,0,0,16.6875,16.6875,1,0.0,16,0.3404255319148936,31,0,0,0.0981012658227848,0,2143,2462,0.9430379746835442,2145 matmul,1x64x52xf64,baseline,23786,26289,26286,0.0,0,3328,3382,0,0.14218447826452535,0.33518334985133796,10090,0,0,0.4241991087194148,0,0,1.0,1.0,1,0.0,10090,0.42439537329127236,13685,0,0,0.5753384343731607,0,2504,26293,0.9995375430925755,2506 matmul,1x64x52xf64,linalg_xdsl,3518,6062,6059,0.0,0,3328,3434,0,0.9761227970437749,0.9994179278230501,3436,0,0,0.9766913018760659,0,0,19.86127167630058,19.86127167630058,1,0.0,173,0.67578125,83,0,0,0.02359295054007959,0,2545,6066,1.0002842524161455,2547 matmul,1x64x56xf64,baseline,25614,28176,28173,0.0,0,3584,3642,0,0.14218786601077535,0.33517393705135284,10866,0,0,0.42422112907003984,0,0,1.0,1.0,1,0.0,10866,0.4244033902277077,14737,0,0,0.5753494182868744,0,2563,28180,0.9995705473569142,2565 -matmul,1x64x56xf64,linalg_xdsl,3784,6380,6377,0.0,0,3584,3698,0,0.9772727272727273,0.9994594594594595,3700,0,0,0.9778012684989429,0,0,19.89247311827957,19.892473118279568,1,0.0,186,0.6838235294117647,86,0,0,0.022727272727272728,0,2597,6384,1.0005285412262157,2599 +matmul,1x64x56xf64,linalg_xdsl,3772,6311,6308,0.0,0,3584,3698,0,0.9803817603393425,0.9994594594594595,3700,0,0,0.9809119830328739,0,0,20.555555555555554,20.555555555555557,1,0.0,180,0.7258064516129032,68,0,0,0.018027571580063628,0,2540,6315,0.9989395546129375,2542 matmul,1x64x60xf64,baseline,27442,30015,30012,0.0,0,3840,3902,0,0.1421908024196487,0.3351657790757602,11642,0,0,0.42424021572771664,0,0,1.0,1.0,1,0.0,11642,0.42441033866793043,15789,0,0,0.5753589388528533,0,2574,30019,0.9995991545805699,2576 -matmul,1x64x60xf64,linalg_xdsl,4050,6664,6661,0.0,0,3840,3962,0,0.9782716049382716,0.9994954591321897,3964,0,0,0.9787654320987654,0,0,19.91959798994975,19.91959798994975,1,0.0,199,0.6909722222222222,89,0,0,0.02197530864197531,0,2615,6668,1.0007407407407407,2617 +matmul,1x64x60xf64,linalg_xdsl,4049,6606,6603,0.0,0,3840,3962,0,0.9785132131390467,0.9994954591321897,3964,0,0,0.979007162262287,0,0,20.432989690721648,20.432989690721648,1,0.0,194,0.7238805970149254,74,0,0,0.018276117559891333,0,2558,6610,0.9972832798221783,2560 matmul,1x64x64xf64,baseline,29270,31904,31901,0.0,0,4096,4162,0,0.14219337205329688,0.3351586406828797,12418,0,0,0.4242569183464298,0,0,1.0,1.0,1,0.0,12418,0.424416418879661,16841,0,0,0.5753672702425692,0,2635,31908,0.9996241885889989,2637 matmul,1x64x64xf64,linalg_xdsl,4322,6978,6975,0.0,0,4096,4226,0,0.977788061082832,0.9995269631031221,4228,0,0,0.978250809810273,0,0,19.943396226415093,19.943396226415093,1,0.0,212,0.6973684210526315,92,0,0,0.02128644146228598,0,2657,6982,0.999537251272559,2659 matmul,1x64x8xf64,baseline,3686,5841,5838,0.0,0,512,521,0,0.14134563212154097,0.33547971667739857,1553,0,0,0.42132392837764515,0,0,1.0,1.0,1,0.0,1553,0.4275881057268722,2079,0,0,0.564026044492675,0,2156,5845,0.9853499728703201,2158 matmul,1x64x8xf64,linalg_xdsl,592,2764,2761,0.0,0,512,530,0,0.8952702702702703,0.9962406015037594,532,0,0,0.8986486486486487,0,0,17.733333333333334,17.733333333333334,1,0.0,30,0.37037037037037035,51,0,0,0.08614864864864864,0,2173,2768,0.9847972972972974,2175 matmul,1x8x12xf64,baseline,567,2662,2659,0.0,0,84,97,0,0.1710758377425044,0.3222591362126246,301,0,0,0.5308641975308642,0,0,1.0,1.0,1,0.0,301,0.840782122905028,57,0,0,0.10052910052910052,0,2096,2666,0.6313932980599648,2098 -matmul,1x8x12xf64,linalg_xdsl,180,2276,2273,0.0,0,96,122,0,0.6777777777777778,0.9838709677419355,124,0,0,0.6888888888888889,0,0,2.8837209302325584,2.883720930232558,1,0.0,43,0.45263157894736844,52,0,0,0.28888888888888886,0,2097,2280,0.9777777777777777,2099 +matmul,1x8x12xf64,linalg_xdsl,176,2254,2251,0.0,0,96,122,0,0.6931818181818182,0.9838709677419355,124,0,0,0.7045454545454546,0,0,2.952380952380952,2.9523809523809526,1,0.0,42,0.46153846153846156,49,0,0,0.2784090909090909,0,2079,2258,0.9829545454545454,2081 matmul,1x8x16xf64,baseline,755,2842,2839,0.0,0,112,129,0,0.17086092715231788,0.32169576059850374,401,0,0,0.5311258278145695,0,0,1.0,1.0,1,0.0,401,0.8459915611814346,73,0,0,0.09668874172185431,0,2088,2846,0.6278145695364238,2090 matmul,1x8x16xf64,linalg_xdsl,222,2336,2333,0.0,0,128,162,0,0.7297297297297297,0.9878048780487805,164,0,0,0.7387387387387387,0,0,2.9285714285714284,2.9285714285714284,1,0.0,56,0.5045045045045045,55,0,0,0.24774774774774774,0,2115,2340,0.9864864864864865,2117 matmul,1x8x20xf64,baseline,935,3040,3037,0.0,0,140,161,0,0.17219251336898395,0.3213572854291417,501,0,0,0.5358288770053476,0,0,1.0,1.0,1,0.0,501,0.8491525423728814,89,0,0,0.09518716577540107,0,2106,3044,0.6310160427807487,2108 -matmul,1x8x20xf64,linalg_xdsl,265,2371,2368,0.0,0,160,202,0,0.7622641509433963,0.9901960784313726,204,0,0,0.769811320754717,0,0,2.9565217391304346,2.9565217391304346,1,0.0,69,0.5433070866141733,58,0,0,0.2188679245283019,0,2107,2375,0.9886792452830189,2109 +matmul,1x8x20xf64,linalg_xdsl,262,2364,2361,0.0,0,160,202,0,0.7709923664122137,0.9901960784313726,204,0,0,0.7786259541984732,0,0,3.0,3.0,1,0.0,68,0.5528455284552846,55,0,0,0.2099236641221374,0,2103,2368,0.9885496183206106,2105 matmul,1x8x24xf64,baseline,1130,3246,3243,0.0,0,168,193,0,0.17079646017699116,0.3211314475873544,601,0,0,0.531858407079646,0,0,1.0,1.0,1,0.0,601,0.8512747875354107,105,0,0,0.09292035398230089,0,2117,3250,0.624778761061947,2119 -matmul,1x8x24xf64,linalg_xdsl,311,2439,2436,0.0,0,192,242,0,0.7781350482315113,0.9918032786885246,244,0,0,0.7845659163987139,0,0,2.975609756097561,2.975609756097561,1,0.0,82,0.5734265734265734,61,0,0,0.19614147909967847,0,2129,2443,0.9807073954983924,2131 +matmul,1x8x24xf64,linalg_xdsl,310,2396,2393,0.0,0,192,242,0,0.7806451612903226,0.9918032786885246,244,0,0,0.7870967741935484,0,0,3.05,3.05,1,0.0,80,0.5925925925925926,55,0,0,0.1774193548387097,0,2087,2400,0.9645161290322581,2089 matmul,1x8x28xf64,baseline,1312,3438,3435,0.0,0,196,225,0,0.1714939024390244,0.3209700427960057,701,0,0,0.5342987804878049,0,0,1.0,1.0,1,0.0,701,0.8527980535279805,121,0,0,0.09222560975609756,0,2127,3442,0.6265243902439024,2129 -matmul,1x8x28xf64,linalg_xdsl,368,2497,2494,0.0,0,224,282,0,0.7663043478260869,0.9929577464788732,284,0,0,0.7717391304347826,0,0,2.9894736842105263,2.9894736842105263,1,0.0,95,0.5974842767295597,64,0,0,0.17391304347826086,0,2130,2501,0.9456521739130435,2132 +matmul,1x8x28xf64,linalg_xdsl,353,2490,2487,0.0,0,224,282,0,0.7988668555240793,0.9929577464788732,284,0,0,0.8045325779036827,0,0,3.0869565217391304,3.0869565217391304,1,0.0,92,0.6258503401360545,55,0,0,0.1558073654390935,0,2138,2494,0.9603399433427762,2140 matmul,1x8x32xf64,baseline,1495,3582,3579,0.0,0,224,257,0,0.17190635451505018,0.3208489388264669,801,0,0,0.5357859531772575,0,0,1.0,1.0,1,0.0,801,0.8539445628997868,137,0,0,0.09163879598662207,0,2088,3586,0.6274247491638796,2090 matmul,1x8x32xf64,linalg_xdsl,395,2553,2550,0.0,0,256,322,0,0.8151898734177215,0.9938271604938271,324,0,0,0.8202531645569621,0,0,3.0,3.0,1,0.0,108,0.6171428571428571,67,0,0,0.16962025316455695,0,2159,2557,0.989873417721519,2161 matmul,1x8x36xf64,baseline,1679,3771,3768,0.0,0,252,289,0,0.17212626563430614,0.32075471698113206,901,0,0,0.5366289458010721,0,0,1.0,1.0,1,0.0,901,0.8548387096774194,153,0,0,0.09112567004169149,0,2093,3775,0.6277546158427636,2095 -matmul,1x8x36xf64,linalg_xdsl,437,2600,2597,0.0,0,288,362,0,0.8283752860411899,0.9945054945054945,364,0,0,0.8329519450800915,0,0,3.008264462809917,3.0082644628099175,1,0.0,121,0.6335078534031413,70,0,0,0.16018306636155608,0,2164,2604,0.9931350114416476,2166 +matmul,1x8x36xf64,linalg_xdsl,440,2577,2574,0.0,0,288,362,0,0.8227272727272728,0.9945054945054945,364,0,0,0.8272727272727273,0,0,3.084745762711864,3.0847457627118646,1,0.0,118,0.659217877094972,61,0,0,0.13863636363636364,0,2138,2581,0.9659090909090909,2140 matmul,1x8x40xf64,baseline,1863,3960,3957,0.0,0,280,321,0,0.1723027375201288,0.3206793206793207,1001,0,0,0.5373054213633924,0,0,1.0,1.0,1,0.0,1001,0.8555555555555555,169,0,0,0.09071390230810521,0,2098,3964,0.6280193236714976,2100 -matmul,1x8x40xf64,linalg_xdsl,480,2630,2627,0.0,0,320,402,0,0.8375,0.995049504950495,404,0,0,0.8416666666666667,0,0,3.014925373134328,3.014925373134328,1,0.0,134,0.6442307692307693,74,0,0,0.15416666666666667,0,2151,2634,0.9958333333333333,2153 +matmul,1x8x40xf64,linalg_xdsl,482,2612,2609,0.0,0,320,402,0,0.8340248962655602,0.995049504950495,404,0,0,0.8381742738589212,0,0,3.0606060606060606,3.0606060606060606,1,0.0,132,0.66,68,0,0,0.14107883817427386,0,2131,2616,0.9792531120331951,2133 matmul,1x8x44xf64,baseline,2047,4149,4146,0.0,0,308,353,0,0.17244748412310698,0.3206176203451408,1101,0,0,0.5378602833414753,0,0,1.0,1.0,1,0.0,1101,0.8561430793157077,185,0,0,0.0903761602344895,0,2103,4153,0.6282364435759648,2105 matmul,1x8x44xf64,linalg_xdsl,522,2677,2674,0.0,0,352,442,0,0.8467432950191571,0.9954954954954955,444,0,0,0.8505747126436781,0,0,3.020408163265306,3.020408163265306,1,0.0,147,0.65625,77,0,0,0.1475095785440613,0,2156,2681,0.9980842911877394,2158 matmul,1x8x48xf64,baseline,2231,4338,4335,0.0,0,336,385,0,0.17256835499775885,0.3205661948376353,1201,0,0,0.5383236216943075,0,0,1.0,1.0,1,0.0,1201,0.8566333808844507,201,0,0,0.09009412819363515,0,2108,4342,0.6284177498879426,2110 -matmul,1x8x48xf64,linalg_xdsl,564,2724,2721,0.0,0,384,482,0,0.8546099290780141,0.9958677685950413,484,0,0,0.8581560283687943,0,0,3.0250000000000004,3.025,1,0.0,160,0.6666666666666666,80,0,0,0.14184397163120568,0,2161,2728,1.0,2163 +matmul,1x8x48xf64,linalg_xdsl,565,2677,2674,0.0,0,384,482,0,0.8530973451327434,0.9958677685950413,484,0,0,0.856637168141593,0,0,3.1025641025641026,3.1025641025641026,1,0.0,156,0.6964285714285714,68,0,0,0.12035398230088495,0,2113,2681,0.976991150442478,2115 matmul,1x8x4xf64,baseline,202,2269,2266,0.0,0,28,33,0,0.16336633663366337,0.32673267326732675,101,0,0,0.5,0,0,1.0,1.0,1,0.0,101,0.9439252336448598,6,0,0,0.0297029702970297,0,2068,2273,0.5297029702970297,2070 matmul,1x8x4xf64,linalg_xdsl,81,2175,2172,0.0,0,32,41,0,0.5061728395061729,0.9534883720930233,43,0,0,0.5308641975308642,0,0,2.6875,2.6875,1,0.0,16,0.34782608695652173,30,0,0,0.37037037037037035,0,2095,2179,0.9012345679012346,2097 matmul,1x8x52xf64,baseline,2415,4527,4524,0.0,0,364,417,0,0.17267080745341615,0.3205226748654881,1301,0,0,0.5387163561076604,0,0,1.0,1.0,1,0.0,1301,0.8570487483530962,217,0,0,0.08985507246376812,0,2113,4531,0.6285714285714286,2115 matmul,1x8x52xf64,linalg_xdsl,608,2768,2765,0.0,0,416,522,0,0.8585526315789473,0.9961832061068703,524,0,0,0.8618421052631579,0,0,3.028901734104046,3.0289017341040463,1,0.0,173,0.67578125,83,0,0,0.13651315789473684,0,2161,2772,0.9983552631578947,2163 matmul,1x8x56xf64,baseline,2599,4716,4713,0.0,0,392,449,0,0.17275875336667948,0.3204853675945753,1401,0,0,0.5390534821085032,0,0,1.0,1.0,1,0.0,1401,0.857405140758874,233,0,0,0.08964986533282032,0,2118,4720,0.6287033474413235,2120 -matmul,1x8x56xf64,linalg_xdsl,648,2813,2810,0.0,0,448,562,0,0.8672839506172839,0.9964539007092199,564,0,0,0.8703703703703703,0,0,3.032258064516129,3.032258064516129,1,0.0,186,0.6838235294117647,86,0,0,0.13271604938271606,0,2166,2817,1.0030864197530864,2168 +matmul,1x8x56xf64,linalg_xdsl,637,2780,2777,0.0,0,448,562,0,0.8822605965463108,0.9964539007092199,564,0,0,0.8854003139717426,0,0,3.1333333333333333,3.1333333333333333,1,0.0,180,0.7258064516129032,68,0,0,0.10675039246467818,0,2144,2784,0.9921507064364208,2146 matmul,1x8x60xf64,baseline,2783,4905,4902,0.0,0,420,481,0,0.17283507006827165,0.32045303131245834,1501,0,0,0.5393460294646065,0,0,1.0,1.0,1,0.0,1501,0.8577142857142858,249,0,0,0.08947179302910528,0,2123,4909,0.6288178224937118,2125 -matmul,1x8x60xf64,linalg_xdsl,690,2865,2862,0.0,0,480,602,0,0.8724637681159421,0.9966887417218543,604,0,0,0.8753623188405797,0,0,3.035175879396985,3.0351758793969847,1,0.0,199,0.6909722222222222,89,0,0,0.1289855072463768,0,2176,2869,1.0043478260869565,2178 +matmul,1x8x60xf64,linalg_xdsl,689,2816,2813,0.0,0,480,602,0,0.8737300435413643,0.9966887417218543,604,0,0,0.8766328011611031,0,0,3.11340206185567,3.11340206185567,1,0.0,194,0.7238805970149254,74,0,0,0.10740203193033382,0,2128,2820,0.9840348330914369,2130 matmul,1x8x64xf64,baseline,2972,5104,5101,0.0,0,448,513,0,0.17261103633916555,0.3204247345409119,1601,0,0,0.5386944818304172,0,0,1.0,1.0,1,0.0,1601,0.8579849946409432,265,0,0,0.08916554508748317,0,2133,5108,0.6278600269179004,2135 matmul,1x8x64xf64,linalg_xdsl,732,2923,2920,0.0,0,512,642,0,0.8770491803278688,0.9968944099378882,644,0,0,0.8797814207650273,0,0,3.0377358490566033,3.0377358490566038,1,0.0,212,0.6973684210526315,92,0,0,0.12568306010928962,0,2192,2927,1.005464480874317,2194 matmul,1x8x8xf64,baseline,381,2474,2471,0.0,0,56,65,0,0.17060367454068243,0.32338308457711445,201,0,0,0.5275590551181102,0,0,1.0,1.0,1,0.0,201,0.9710144927536232,6,0,0,0.015748031496062992,0,2094,2478,0.5433070866141732,2096 matmul,1x8x8xf64,linalg_xdsl,138,2231,2228,0.0,0,64,82,0,0.5942028985507246,0.9761904761904762,84,0,0,0.6086956521739131,0,0,2.8000000000000003,2.8,1,0.0,30,0.379746835443038,49,0,0,0.35507246376811596,0,2094,2235,0.963768115942029,2096 matmul,4x12x12xf64,baseline,3277,5403,5400,0.0,0,528,577,0,0.17607567897467197,0.32470455824423183,1777,0,0,0.5422642660970399,0,0,1.0,1.0,1,4.4,1777,0.8630403108305003,282,22,5,0.08605431797375648,5,2127,5407,0.6283185840707964,2129 -matmul,4x12x12xf64,linalg_xdsl,772,2875,2872,0.0,0,576,674,0,0.8730569948186528,0.9970414201183432,676,0,0,0.8756476683937824,0,0,4.2250000000000005,4.225,1,0.0,160,0.6477732793522267,87,0,0,0.11269430051813471,0,2104,2879,0.9883419689119171,2106 +matmul,4x12x12xf64,linalg_xdsl,755,2870,2867,0.0,0,576,674,0,0.8927152317880794,0.9970414201183432,676,0,0,0.895364238410596,0,0,4.333333333333333,4.333333333333333,1,0.0,156,0.6753246753246753,75,0,0,0.09933774834437085,0,2116,2874,0.9947019867549668,2118 matmul,4x12x16xf64,baseline,4344,6463,6460,0.0,0,704,769,0,0.17702578268876612,0.32460953989024904,2369,0,0,0.5453499079189686,0,0,1.0,1.0,1,4.166666666666667,2369,0.8715967623252392,349,25,6,0.08034069981583794,6,2120,6467,0.6256906077348066,2122 matmul,4x12x16xf64,linalg_xdsl,1004,3128,3125,0.0,0,768,898,0,0.8944223107569721,0.9977777777777778,900,0,0,0.896414342629482,0,0,4.245283018867924,4.245283018867925,1,0.0,212,0.6816720257234726,99,0,0,0.09860557768924302,0,2125,3132,0.9950199203187251,2127 matmul,4x12x20xf64,baseline,5423,7543,7540,0.0,0,880,961,0,0.17720818735017518,0.32455251604187774,2961,0,0,0.5460077447907062,0,0,1.0,1.0,1,4.166666666666667,2961,0.8775933609958506,413,25,6,0.07615710861146967,6,2121,7547,0.6221648534021759,2123 -matmul,4x12x20xf64,linalg_xdsl,1236,3332,3329,0.0,0,960,1122,0,0.9077669902912622,0.998220640569395,1124,0,0,0.9093851132686084,0,0,4.257575757575758,4.257575757575758,1,0.0,264,0.704,111,0,0,0.08980582524271845,0,2097,3336,0.9991909385113268,2099 +matmul,4x12x20xf64,linalg_xdsl,1220,3343,3340,0.0,0,960,1122,0,0.919672131147541,0.998220640569395,1124,0,0,0.921311475409836,0,0,4.323076923076923,4.323076923076923,1,0.0,260,0.724233983286908,99,0,0,0.08114754098360656,0,2124,3347,1.0024590163934426,2126 matmul,4x12x24xf64,baseline,6495,8628,8625,0.0,0,1056,1153,0,0.1775211701308699,0.32451449479313255,3553,0,0,0.547036181678214,0,0,1.0,1.0,1,4.166666666666667,3553,0.8816377171215881,477,25,6,0.07344110854503465,6,2134,8632,0.6204772902232486,2136 -matmul,4x12x24xf64,linalg_xdsl,1462,3595,3592,0.0,0,1152,1346,0,0.920656634746922,0.9985163204747775,1348,0,0,0.9220246238030095,0,0,4.265822784810126,4.265822784810126,1,0.0,316,0.7165532879818595,125,0,0,0.08549931600547196,0,2134,3599,1.0075239398084814,2136 +matmul,4x12x24xf64,linalg_xdsl,1445,3618,3615,0.0,0,1152,1346,0,0.9314878892733564,0.9985163204747775,1348,0,0,0.9328719723183391,0,0,4.376623376623376,4.376623376623376,1,0.0,308,0.7530562347188264,101,0,0,0.0698961937716263,0,2174,3622,1.0027681660899654,2176 matmul,4x12x28xf64,baseline,7567,9705,9702,0.0,0,1232,1345,0,0.17774547376767544,0.32448733413751507,4145,0,0,0.5477732258490815,0,0,1.0,1.0,1,4.166666666666667,4145,0.8845497225778916,541,25,6,0.07149464781287168,6,2139,9709,0.6192678736619532,2141 -matmul,4x12x28xf64,linalg_xdsl,1694,3832,3829,0.0,0,1344,1570,0,0.9268004722550177,0.9987277353689568,1572,0,0,0.9279811097992916,0,0,4.271739130434782,4.271739130434782,1,0.0,368,0.7287128712871287,137,0,0,0.0808736717827627,0,2139,3836,1.0088547815820543,2141 +matmul,4x12x28xf64,linalg_xdsl,1668,3815,3812,0.0,0,1344,1570,0,0.9412470023980816,0.9987277353689568,1572,0,0,0.9424460431654677,0,0,4.415730337078651,4.415730337078652,1,0.0,356,0.7789934354485777,101,0,0,0.0605515587529976,0,2148,3819,1.0029976019184652,2150 matmul,4x12x32xf64,baseline,8641,10758,10755,0.0,0,1408,1537,0,0.1778729313736836,0.3244669622123707,4737,0,0,0.5482004397639162,0,0,1.0,1.0,1,3.4285714285714284,4737,0.8857516828721017,611,24,7,0.07070940863326004,7,2118,10762,0.6189098483971762,2120 matmul,4x12x32xf64,linalg_xdsl,1926,4074,4071,0.0,0,1536,1794,0,0.9314641744548287,0.9988864142538976,1796,0,0,0.9325025960539979,0,0,4.276190476190476,4.276190476190476,1,0.0,420,0.7381370826010545,149,0,0,0.07736240913811007,0,2149,4078,1.0098650051921079,2151 matmul,4x12x36xf64,baseline,9713,11840,11837,0.0,0,1584,1729,0,0.17800885411304437,0.3244511165321824,5329,0,0,0.5486461443426336,0,0,1.0,1.0,1,3.4285714285714284,5329,0.8875749500333111,675,24,7,0.06949449191804798,7,2128,11844,0.6181406362606816,2130 -matmul,4x12x36xf64,linalg_xdsl,2158,4311,4308,0.0,0,1728,2018,0,0.9351251158480074,0.999009900990099,2020,0,0,0.9360518999073216,0,0,4.279661016949153,4.279661016949152,1,0.0,472,0.7456556082148499,161,0,0,0.07460611677479147,0,2154,4315,1.010658016682113,2156 +matmul,4x12x36xf64,linalg_xdsl,2133,4326,4323,0.0,0,1728,2018,0,0.9460853258321613,0.999009900990099,2020,0,0,0.947022972339428,0,0,4.391304347826087,4.391304347826087,1,0.0,460,0.7863247863247863,125,0,0,0.05860290670417253,0,2194,4330,1.0056258790436006,2196 matmul,4x12x40xf64,baseline,10786,12948,12945,0.0,0,1760,1921,0,0.17810124235119598,0.32443843945279516,5921,0,0,0.5489523456332283,0,0,1.0,1.0,1,4.166666666666667,5921,0.8898406973249173,733,25,6,0.0679584646764324,6,2163,12952,0.6169108103096607,2165 -matmul,4x12x40xf64,linalg_xdsl,2390,4554,4551,0.0,0,1920,2242,0,0.9380753138075314,0.9991087344028521,2244,0,0,0.9389121338912134,0,0,4.2824427480916025,4.282442748091603,1,0.0,524,0.7517934002869441,173,0,0,0.07238493723849372,0,2165,4558,1.0112970711297071,2167 +matmul,4x12x40xf64,linalg_xdsl,2373,4557,4554,0.0,0,1920,2242,0,0.944795617361989,0.9991087344028521,2244,0,0,0.9456384323640961,0,0,4.348837209302325,4.348837209302325,1,0.0,516,0.7759398496240602,149,0,0,0.06278971765697429,0,2185,4561,1.0084281500210703,2187 matmul,4x12x44xf64,baseline,11852,14006,14003,0.0,0,1936,2113,0,0.1782821464731691,0.324428066943037,6513,0,0,0.5495275059061762,0,0,1.0,1.0,1,3.7142857142857144,6513,0.8696755241020163,976,26,7,0.08234897063786703,7,2155,14010,0.6318764765440432,2157 matmul,4x12x44xf64,linalg_xdsl,2622,4796,4793,0.0,0,2112,2466,0,0.9405034324942791,0.9991896272285251,2468,0,0,0.9412662090007627,0,0,4.284722222222222,4.284722222222222,1,0.0,576,0.7568988173455979,185,0,0,0.07055682684973302,0,2175,4800,1.0118230358504958,2177 matmul,4x12x48xf64,baseline,12924,15083,15080,0.0,0,2112,2305,0,0.1783503559269576,0.32441942294159043,7105,0,0,0.5497523986381925,0,0,1.0,1.0,1,3.7142857142857144,7105,0.8706040926357064,1056,26,7,0.08170844939647168,7,2160,15087,0.6314608480346642,2162 -matmul,4x12x48xf64,linalg_xdsl,2854,5033,5030,0.0,0,2304,2690,0,0.9425367904695164,0.9992570579494799,2692,0,0,0.9432375613174492,0,0,4.286624203821655,4.286624203821656,1,0.0,628,0.7612121212121212,197,0,0,0.06902592852137351,0,2180,5037,1.0122634898388227,2182 +matmul,4x12x48xf64,linalg_xdsl,2821,5038,5035,0.0,0,2304,2690,0,0.9535625664657923,0.9992570579494799,2692,0,0,0.9542715349166963,0,0,4.398692810457517,4.398692810457517,1,0.0,612,0.8042049934296978,149,0,0,0.05281814959234314,0,2218,5042,1.0070896845090394,2220 matmul,4x12x4xf64,baseline,1088,3145,3142,0.0,0,176,193,0,0.17738970588235295,0.3254637436762226,593,0,0,0.5450367647058824,0,0,1.0,1.0,1,0.0,593,0.959546925566343,25,0,0,0.02297794117647059,0,2058,3149,0.5680147058823529,2060 matmul,4x12x4xf64,linalg_xdsl,290,2371,2368,0.0,0,192,226,0,0.7793103448275862,0.9912280701754386,228,0,0,0.7862068965517242,0,0,4.071428571428571,4.071428571428571,1,0.0,56,0.5233644859813084,51,0,0,0.17586206896551723,0,2082,2375,0.9620689655172414,2084 matmul,4x12x52xf64,baseline,13996,16165,16162,0.0,0,2288,2497,0,0.1784081166047442,0.32441210861374564,7697,0,0,0.5499428408116604,0,0,1.0,1.0,1,3.7142857142857144,7697,0.8713913732593683,1136,26,7,0.08116604744212633,7,2170,16169,0.6311088882537867,2172 matmul,4x12x52xf64,linalg_xdsl,3086,5275,5272,0.0,0,2496,2914,0,0.9442644199611148,0.9993141289437586,2916,0,0,0.9449125081011017,0,0,4.288235294117647,4.288235294117647,1,0.0,680,0.7649043869516311,209,0,0,0.06772521062864549,0,2190,5279,1.0126377187297473,2192 matmul,4x12x56xf64,baseline,15068,17247,17244,0.0,0,2464,2689,0,0.17845765861428192,0.32440583906381953,8289,0,0,0.5501061852933369,0,0,1.0,1.0,1,3.7142857142857144,8289,0.8720673329826407,1216,26,7,0.08070082293602336,7,2180,17251,0.6308070082293602,2182 -matmul,4x12x56xf64,linalg_xdsl,3318,5517,5514,0.0,0,2688,3138,0,0.945750452079566,0.9993630573248408,3140,0,0,0.9463532248342374,0,0,4.2896174863387975,4.2896174863387975,1,0.0,732,0.7681007345225603,221,0,0,0.06660638939119952,0,2200,5521,1.012959614225437,2202 +matmul,4x12x56xf64,linalg_xdsl,3268,5474,5471,0.0,0,2688,3138,0,0.9602203182374541,0.9993630573248408,3140,0,0,0.9608323133414932,0,0,4.435028248587571,4.435028248587571,1,0.0,708,0.8261376896149358,149,0,0,0.045593635250917995,0,2207,5478,1.0064259485924112,2209 matmul,4x12x60xf64,baseline,16140,18344,18341,0.0,0,2640,2881,0,0.1785006195786865,0.3244004053597568,8881,0,0,0.5502478314745973,0,0,1.0,1.0,1,3.7142857142857144,8881,0.8726540237791097,1296,26,7,0.08029739776951673,7,2205,18348,0.630545229244114,2207 -matmul,4x12x60xf64,linalg_xdsl,3550,5752,5749,0.0,0,2880,3362,0,0.9470422535211268,0.9994054696789536,3364,0,0,0.9476056338028169,0,0,4.290816326530613,4.290816326530612,1,0.0,784,0.7708947885939036,233,0,0,0.06563380281690141,0,2203,5756,1.0132394366197184,2205 +matmul,4x12x60xf64,linalg_xdsl,3509,5734,5731,0.0,0,2880,3362,0,0.9581077229980052,0.9994054696789536,3364,0,0,0.9586776859504132,0,0,4.403141361256545,4.403141361256544,1,0.0,764,0.8153681963713981,173,0,0,0.04930179538330009,0,2226,5738,1.0079794813337133,2228 matmul,4x12x64xf64,baseline,17212,19403,19400,0.0,0,2816,3073,0,0.17853822914245876,0.324395650797002,9473,0,0,0.550371833604462,0,0,1.0,1.0,1,3.7142857142857144,9473,0.873168033920177,1376,26,7,0.0799442249593307,7,2192,19407,0.6303160585637927,2194 matmul,4x12x64xf64,linalg_xdsl,3782,5996,5993,0.0,0,3072,3586,0,0.9481755684822845,0.9994425863991081,3588,0,0,0.9487043892120571,0,0,4.291866028708134,4.291866028708134,1,0.0,836,0.7733580018501388,245,0,0,0.06478053939714437,0,2215,6000,1.0134849286092016,2217 matmul,4x12x8xf64,baseline,2200,4304,4301,0.0,0,352,385,0,0.175,0.32489451476793246,1185,0,0,0.5386363636363637,0,0,1.0,1.0,1,4.166666666666667,1185,0.8428165007112376,221,25,6,0.10045454545454545,6,2105,4308,0.6390909090909092,2107 matmul,4x12x8xf64,linalg_xdsl,540,2649,2646,0.0,0,384,450,0,0.8333333333333334,0.995575221238938,452,0,0,0.837037037037037,0,0,4.185185185185185,4.185185185185185,1,0.0,108,0.5901639344262295,75,0,0,0.1388888888888889,0,2110,2653,0.9759259259259259,2112 matmul,4x16x12xf64,baseline,4288,6381,6378,0.0,0,720,769,0,0.17933768656716417,0.3268168295792605,2353,0,0,0.5487406716417911,0,0,1.0,1.0,1,3.7777777777777777,2353,0.8849191425347875,306,34,9,0.07136194029850747,9,2094,6385,0.6201026119402986,2096 -matmul,4x16x12xf64,linalg_xdsl,964,3050,3047,0.0,0,768,866,0,0.8983402489626556,0.9976958525345622,868,0,0,0.9004149377593361,0,0,5.425,5.425,1,0.0,160,0.6477732793522267,87,0,0,0.09024896265560166,0,2087,3054,0.9906639004149378,2089 +matmul,4x16x12xf64,linalg_xdsl,947,3081,3078,0.0,0,768,866,0,0.914466737064414,0.9976958525345622,868,0,0,0.9165786694825766,0,0,5.564102564102564,5.564102564102564,1,0.0,156,0.6753246753246753,75,0,0,0.0791974656810982,0,2135,3085,0.9957761351636748,2137 matmul,4x16x16xf64,baseline,5696,7799,7796,0.0,0,960,1025,0,0.17995084269662923,0.326745298055467,3137,0,0,0.5507373595505618,0,0,1.0,1.0,1,3.7777777777777777,3137,0.8944967208440262,370,34,9,0.06495786516853932,9,2104,7803,0.6156952247191011,2106 matmul,4x16x16xf64,linalg_xdsl,1260,3356,3353,0.0,0,1024,1154,0,0.9158730158730158,0.9982698961937716,1156,0,0,0.9174603174603174,0,0,5.452830188679246,5.452830188679245,1,0.0,212,0.6816720257234726,99,0,0,0.07857142857142857,0,2097,3360,0.996031746031746,2099 matmul,4x16x20xf64,baseline,7104,9237,9234,0.0,0,1200,1281,0,0.18032094594594594,0.32670237184391737,3921,0,0,0.5519425675675675,0,0,1.0,1.0,1,3.7777777777777777,3921,0.9003444316877153,434,34,9,0.06109234234234234,9,2134,9241,0.6130349099099099,2136 -matmul,4x16x20xf64,linalg_xdsl,1550,3683,3680,0.0,0,1280,1442,0,0.9303225806451613,0.9986149584487535,1444,0,0,0.9316129032258065,0,0,5.46969696969697,5.46969696969697,1,0.0,264,0.7002652519893899,113,0,0,0.07290322580645162,0,2134,3687,1.0045161290322582,2136 +matmul,4x16x20xf64,linalg_xdsl,1541,3695,3692,0.0,0,1280,1442,0,0.9357560025957171,0.9986149584487535,1444,0,0,0.9370538611291369,0,0,5.553846153846154,5.553846153846154,1,0.0,260,0.7202216066481995,101,0,0,0.06554185593770279,0,2155,3699,1.0025957170668396,2157 matmul,4x16x24xf64,baseline,8520,10684,10681,0.0,0,1440,1537,0,0.18039906103286385,0.32667375132837406,4705,0,0,0.5522300469483568,0,0,1.0,1.0,1,3.3,4705,0.903244384718756,504,33,10,0.059154929577464786,10,2165,10688,0.6113849765258216,2167 -matmul,4x16x24xf64,linalg_xdsl,1846,3989,3986,0.0,0,1536,1730,0,0.9371614301191766,0.9988452655889145,1732,0,0,0.9382448537378115,0,0,5.481012658227848,5.481012658227848,1,0.0,316,0.7165532879818595,125,0,0,0.06771397616468039,0,2144,3993,1.005958829902492,2146 +matmul,4x16x24xf64,linalg_xdsl,1829,4012,4009,0.0,0,1536,1730,0,0.9458720612356479,0.9988452655889145,1732,0,0,0.946965554948059,0,0,5.623376623376624,5.623376623376624,1,0.0,308,0.7530562347188264,101,0,0,0.05522143247676326,0,2184,4016,1.0021869874248224,2186 matmul,4x16x28xf64,baseline,9928,12064,12061,0.0,0,1680,1793,0,0.1806003223207091,0.32665330661322645,5489,0,0,0.552880741337631,0,0,1.0,1.0,1,3.3,5489,0.9062242034010236,568,33,10,0.057211925866236905,10,2137,12068,0.6100926672038679,2139 -matmul,4x16x28xf64,linalg_xdsl,2142,4275,4272,0.0,0,1792,2018,0,0.942110177404295,0.999009900990099,2020,0,0,0.9430438842203548,0,0,5.489130434782608,5.489130434782608,1,0.0,368,0.7287128712871287,137,0,0,0.06395891690009337,0,2134,4279,1.0070028011204482,2136 +matmul,4x16x28xf64,linalg_xdsl,2116,4269,4266,0.0,0,1792,2018,0,0.9536862003780718,0.999009900990099,2020,0,0,0.9546313799621928,0,0,5.674157303370786,5.674157303370786,1,0.0,356,0.7789934354485777,101,0,0,0.04773156899810964,0,2154,4273,1.0023629489603025,2156 matmul,4x16x32xf64,baseline,11329,13518,13515,0.0,0,1920,2049,0,0.18086327125077237,0.3266379722620756,6273,0,0,0.553711713302145,0,0,1.0,1.0,1,3.3,6273,0.8923186344238976,757,33,10,0.0668196663430135,10,2190,13522,0.6205313796451585,2192 matmul,4x16x32xf64,linalg_xdsl,2437,4586,4583,0.0,0,2048,2306,0,0.9462453836684448,0.9991334488734835,2308,0,0,0.9470660648338121,0,0,5.495238095238095,5.495238095238095,1,0.0,420,0.7381370826010545,149,0,0,0.06114074681986048,0,2150,4590,1.0082068116536727,2152 matmul,4x16x36xf64,baseline,12743,14934,14931,0.0,0,2160,2305,0,0.18088362238091502,0.32662604506164095,7057,0,0,0.5537942399748882,0,0,1.0,1.0,1,3.3,7057,0.8939701038763618,837,33,10,0.065683120144393,10,2192,14938,0.6194773601192812,2194 -matmul,4x16x36xf64,linalg_xdsl,2734,4908,4905,0.0,0,2304,2594,0,0.9487929773226043,0.9992295839753467,2596,0,0,0.9495245062179956,0,0,5.5,5.5,1,0.0,472,0.7456556082148499,161,0,0,0.05888807607900512,0,2175,4912,1.0084125822970007,2177 +matmul,4x16x36xf64,linalg_xdsl,2709,4921,4918,0.0,0,2304,2594,0,0.9575489110372831,0.9992295839753467,2596,0,0,0.9582871908453304,0,0,5.643478260869565,5.643478260869565,1,0.0,460,0.7863247863247863,125,0,0,0.04614248800295312,0,2213,4925,1.0044296788482836,2215 matmul,4x16x40xf64,baseline,14159,16341,16338,0.0,0,2400,2561,0,0.1808743555335829,0.3266165029970667,7841,0,0,0.5537820467547143,0,0,1.0,1.0,1,3.5833333333333335,7841,0.878641864634693,1083,43,12,0.07648845257433434,12,2183,16345,0.6302704993290487,2185 -matmul,4x16x40xf64,linalg_xdsl,3030,5214,5211,0.0,0,2560,2882,0,0.9511551155115512,0.9993065187239945,2884,0,0,0.9518151815181518,0,0,5.5038167938931295,5.5038167938931295,1,0.0,524,0.7517934002869441,173,0,0,0.057095709570957096,0,2185,5218,1.008910891089109,2187 +matmul,4x16x40xf64,linalg_xdsl,3013,5217,5214,0.0,0,2560,2882,0,0.9565217391304348,0.9993065187239945,2884,0,0,0.9571855293727182,0,0,5.589147286821706,5.589147286821706,1,0.0,516,0.7759398496240602,149,0,0,0.04945237305011616,0,2205,5221,1.0066379024228342,2207 matmul,4x16x44xf64,baseline,15568,17741,17738,0.0,0,2640,2817,0,0.180948098663926,0.32660869565217393,8625,0,0,0.5540210688591983,0,0,1.0,1.0,1,3.5833333333333335,8625,0.8796532381438041,1180,43,12,0.07579650565262076,12,2174,17745,0.6298175745118191,2176 matmul,4x16x44xf64,linalg_xdsl,3326,5523,5520,0.0,0,2816,3170,0,0.9530968129885748,0.9993694829760403,3172,0,0,0.9536981358989778,0,0,5.506944444444445,5.506944444444445,1,0.0,576,0.7568988173455979,185,0,0,0.05562236921226699,0,2198,5527,1.0093205051112448,2200 matmul,4x16x48xf64,baseline,16976,19197,19194,0.0,0,2880,3073,0,0.18102026390197926,0.32660218939313423,9409,0,0,0.5542530631479736,0,0,1.0,1.0,1,3.5833333333333335,9409,0.8805802526906878,1276,43,12,0.07516493873704053,12,2222,19201,0.6294180018850142,2224 -matmul,4x16x48xf64,linalg_xdsl,3622,5831,5828,0.0,0,3072,3458,0,0.9547211485367201,0.999421965317919,3460,0,0,0.9552733296521259,0,0,5.509554140127389,5.509554140127388,1,0.0,628,0.7612121212121212,197,0,0,0.05438983986747653,0,2210,5835,1.0096631695196023,2212 +matmul,4x16x48xf64,linalg_xdsl,3589,5836,5833,0.0,0,3072,3458,0,0.963499582056283,0.999421965317919,3460,0,0,0.9640568403455001,0,0,5.65359477124183,5.65359477124183,1,0.0,612,0.8042049934296978,149,0,0,0.041515742546670384,0,2248,5840,1.0055725828921704,2250 matmul,4x16x4xf64,baseline,1424,3481,3478,0.0,0,240,257,0,0.18047752808988765,0.3273885350318471,785,0,0,0.5512640449438202,0,0,1.0,1.0,1,0.0,785,0.9691358024691358,25,0,0,0.0175561797752809,0,2058,3485,0.5688202247191011,2060 matmul,4x16x4xf64,linalg_xdsl,354,2440,2437,0.0,0,256,290,0,0.8192090395480226,0.9931506849315068,292,0,0,0.8248587570621468,0,0,5.214285714285714,5.214285714285714,1,0.0,56,0.5233644859813084,51,0,0,0.1440677966101695,0,2087,2444,0.9689265536723164,2089 matmul,4x16x52xf64,baseline,18379,20598,20595,0.0,0,3120,3329,0,0.18113063822841285,0.32659668399882275,10193,0,0,0.5546003591055009,0,0,1.0,1.0,1,3.5833333333333335,10193,0.8655740489130435,1583,43,12,0.08613091027803471,12,2220,20602,0.6407312693835356,2222 matmul,4x16x52xf64,linalg_xdsl,3918,6137,6134,0.0,0,3328,3746,0,0.9561000510464522,0.9994663820704376,3748,0,0,0.956610515569168,0,0,5.511764705882353,5.511764705882353,1,0.0,680,0.7649043869516311,209,0,0,0.05334354262378765,0,2220,6141,1.0099540581929556,2222 matmul,4x16x56xf64,baseline,19787,22016,22013,0.0,0,3360,3585,0,0.1811795623389094,0.32659196501776444,10977,0,0,0.554758174559054,0,0,1.0,1.0,1,3.5833333333333335,10977,0.8662405303030303,1695,43,12,0.08566230353262243,12,2230,22020,0.6404204780916763,2232 -matmul,4x16x56xf64,linalg_xdsl,4214,6443,6440,0.0,0,3584,4034,0,0.9572852396772663,0.9995044598612488,4036,0,0,0.9577598481252966,0,0,5.513661202185792,5.5136612021857925,1,0.0,732,0.7681007345225603,221,0,0,0.05244423350735643,0,2230,6447,1.010204081632653,2232 +matmul,4x16x56xf64,linalg_xdsl,4164,6400,6397,0.0,0,3584,4034,0,0.9687800192122958,0.9995044598612488,4036,0,0,0.9692603266090298,0,0,5.700564971751413,5.700564971751413,1,0.0,708,0.8261376896149358,149,0,0,0.035782901056676274,0,2237,6404,1.0050432276657062,2239 matmul,4x16x60xf64,baseline,21195,23413,23410,0.0,0,3600,3841,0,0.18122198631752773,0.32658787518068194,11761,0,0,0.554895022410946,0,0,1.0,1.0,1,3.5833333333333335,11761,0.8668189858490566,1807,43,12,0.08525595659353621,12,2219,23417,0.6401509790044823,2221 -matmul,4x16x60xf64,linalg_xdsl,4510,6728,6725,0.0,0,3840,4322,0,0.9583148558758315,0.9995374653098983,4324,0,0,0.9587583148558758,0,0,5.515306122448979,5.51530612244898,1,0.0,784,0.7708947885939036,233,0,0,0.0516629711751663,0,2219,6732,1.0104212860310422,2221 +matmul,4x16x60xf64,linalg_xdsl,4475,6743,6740,0.0,0,3840,4322,0,0.9658100558659218,0.9995374653098983,4324,0,0,0.9662569832402235,0,0,5.659685863874345,5.659685863874346,1,0.0,764,0.8153681963713981,173,0,0,0.03865921787709497,0,2269,6747,1.0049162011173185,2271 matmul,4x16x64xf64,baseline,22605,24874,24871,0.0,0,3840,4097,0,0.18124308781243087,0.32658429653248305,12545,0,0,0.5549657155496571,0,0,1.0,1.0,1,3.5384615384615383,12545,0.8520681926237859,2178,46,13,0.09635036496350365,13,2270,24878,0.6513160805131608,2272 matmul,4x16x64xf64,linalg_xdsl,4805,7034,7031,0.0,0,4096,4610,0,0.959417273673257,0.9995663486556808,4612,0,0,0.9598335067637878,0,0,5.516746411483254,5.516746411483253,1,0.0,836,0.7733580018501388,245,0,0,0.05098855359001041,0,2230,7038,1.010822060353798,2232 matmul,4x16x8xf64,baseline,2880,4951,4948,0.0,0,480,513,0,0.178125,0.32695984703632885,1569,0,0,0.5447916666666667,0,0,1.0,1.0,1,3.7777777777777777,1569,0.8663721700717836,242,34,9,0.08402777777777778,9,2072,4955,0.6288194444444445,2074 matmul,4x16x8xf64,linalg_xdsl,668,2782,2779,0.0,0,512,578,0,0.8652694610778443,0.996551724137931,580,0,0,0.8682634730538922,0,0,5.37037037037037,5.37037037037037,1,0.0,108,0.5901639344262295,75,0,0,0.1122754491017964,0,2115,2786,0.9805389221556886,2117 matmul,4x20x12xf64,baseline,5342,7465,7462,0.0,0,912,961,0,0.1798951703481842,0.3280983270740867,2929,0,0,0.5482965181579933,0,0,1.0,1.0,1,3.5384615384615383,2929,0.8976402083971805,334,46,13,0.06252339947585174,13,2124,7469,0.610819917633845,2126 -matmul,4x20x12xf64,linalg_xdsl,1156,3252,3249,0.0,0,960,1058,0,0.9152249134948097,0.9981132075471698,1060,0,0,0.916955017301038,0,0,6.625,6.625,1,0.0,160,0.6477732793522267,87,0,0,0.07525951557093426,0,2097,3256,0.9922145328719723,2099 +matmul,4x20x12xf64,linalg_xdsl,1139,3278,3275,0.0,0,960,1058,0,0.9288849868305531,0.9981132075471698,1060,0,0,0.9306409130816505,0,0,6.794871794871795,6.794871794871795,1,0.0,156,0.6753246753246753,75,0,0,0.06584723441615452,0,2140,3282,0.996488147497805,2142 matmul,4x20x16xf64,baseline,7102,9237,9234,0.0,0,1216,1281,0,0.18037172627428893,0.32804097311139563,3905,0,0,0.5498451140523796,0,0,1.0,1.0,1,3.230769230769231,3905,0.9060324825986079,405,42,13,0.05702618980568854,13,2136,9241,0.6068713038580681,2138 matmul,4x20x16xf64,linalg_xdsl,1510,3643,3640,0.0,0,1280,1410,0,0.9337748344370861,0.9985835694050992,1412,0,0,0.9350993377483444,0,0,6.660377358490566,6.660377358490566,1,0.0,212,0.6773162939297125,101,0,0,0.06688741721854305,0,2134,3647,1.0019867549668875,2136 matmul,4x20x20xf64,baseline,8825,10983,10980,0.0,0,1520,1601,0,0.18141643059490084,0.3280065560335997,4881,0,0,0.5530878186968838,0,0,1.0,1.0,1,3.5384615384615383,4881,0.9142161453455704,458,46,13,0.05189801699716714,13,2159,10987,0.604985835694051,2161 -matmul,4x20x20xf64,linalg_xdsl,1870,3998,3995,0.0,0,1600,1762,0,0.9422459893048128,0.9988662131519275,1764,0,0,0.9433155080213904,0,0,6.681818181818181,6.681818181818182,1,0.0,264,0.7002652519893899,113,0,0,0.06042780748663101,0,2129,4002,1.0037433155080215,2131 +matmul,4x20x20xf64,linalg_xdsl,1861,3992,3989,0.0,0,1600,1762,0,0.9468027941966685,0.9988662131519275,1764,0,0,0.9478774852229984,0,0,6.7846153846153845,6.7846153846153845,1,0.0,260,0.7202216066481995,101,0,0,0.05427189682966147,0,2132,3996,1.00214938205266,2134 matmul,4x20x24xf64,baseline,10574,12740,12737,0.0,0,1824,1921,0,0.18167202572347266,0.32798360935632576,5857,0,0,0.5539058066956686,0,0,1.0,1.0,1,3.5384615384615383,5857,0.9175936080213066,526,46,13,0.04974465670512578,13,2167,12744,0.6036504634007943,2169 -matmul,4x20x24xf64,linalg_xdsl,2230,4389,4386,0.0,0,1920,2114,0,0.9479820627802691,0.999054820415879,2116,0,0,0.9488789237668162,0,0,6.69620253164557,6.69620253164557,1,0.0,316,0.7165532879818595,125,0,0,0.05605381165919283,0,2160,4393,1.004932735426009,2162 +matmul,4x20x24xf64,linalg_xdsl,2213,4410,4407,0.0,0,1920,2114,0,0.9552643470402169,0.999054820415879,2116,0,0,0.956168097605061,0,0,6.87012987012987,6.87012987012987,1,0.0,308,0.7530562347188264,101,0,0,0.045639403524627205,0,2198,4414,1.0018075011296883,2200 matmul,4x20x28xf64,baseline,12331,14503,14500,0.0,0,2128,2241,0,0.1817370853945341,0.32796721791306893,6833,0,0,0.5541318627848512,0,0,1.0,1.0,1,3.230769230769231,6833,0.9063536278020957,706,42,13,0.0572540750952883,13,2173,14507,0.6113859378801395,2175 -matmul,4x20x28xf64,linalg_xdsl,2590,4764,4761,0.0,0,2240,2466,0,0.9521235521235522,0.9991896272285251,2468,0,0,0.9528957528957529,0,0,6.706521739130435,6.706521739130435,1,0.0,368,0.7287128712871287,137,0,0,0.05289575289575289,0,2175,4768,1.005791505791506,2177 +matmul,4x20x28xf64,linalg_xdsl,2564,4745,4742,0.0,0,2240,2466,0,0.9617784711388455,0.9991896272285251,2468,0,0,0.9625585023400937,0,0,6.932584269662921,6.932584269662922,1,0.0,356,0.7789934354485777,101,0,0,0.03939157566302652,0,2182,4749,1.00195007800312,2184 matmul,4x20x32xf64,baseline,14092,16255,16252,0.0,0,2432,2561,0,0.18173431734317344,0.32795492380586505,7809,0,0,0.5541441952881068,0,0,1.0,1.0,1,3.619047619047619,7809,0.8936827649347677,929,76,21,0.06592392847005393,18,2164,16259,0.6200681237581607,2166 matmul,4x20x32xf64,linalg_xdsl,2950,5134,5131,0.0,0,2560,2818,0,0.9552542372881356,0.999290780141844,2820,0,0,0.9559322033898305,0,0,6.714285714285714,6.714285714285714,1,0.0,420,0.7381370826010545,149,0,0,0.05050847457627119,0,2185,5138,1.0064406779661017,2187 matmul,4x20x36xf64,baseline,15843,18059,18056,0.0,0,2736,2881,0,0.18184687243577605,0.3279453614114969,8785,0,0,0.554503566243767,0,0,1.0,1.0,1,3.619047619047619,8785,0.895423504229946,1026,76,21,0.06476046203370574,18,2217,18063,0.6192640282774727,2219 -matmul,4x20x36xf64,linalg_xdsl,3310,5507,5504,0.0,0,2880,3170,0,0.9577039274924471,0.9993694829760403,3172,0,0,0.9583081570996979,0,0,6.720338983050848,6.720338983050848,1,0.0,472,0.7456556082148499,161,0,0,0.048640483383685804,0,2198,5511,1.0069486404833836,2200 +matmul,4x20x36xf64,linalg_xdsl,3285,5505,5502,0.0,0,2880,3170,0,0.9649923896499238,0.9993694829760403,3172,0,0,0.9656012176560121,0,0,6.895652173913043,6.895652173913043,1,0.0,460,0.7863247863247863,125,0,0,0.0380517503805175,0,2221,5509,1.0036529680365296,2223 matmul,4x20x40xf64,baseline,17578,19756,19753,0.0,0,3040,3201,0,0.1821026282853567,0.3279377113000717,9761,0,0,0.5552963932187962,0,0,1.0,1.0,1,3.176470588235294,9761,0.9108809257185517,955,54,17,0.05432927523040164,14,2179,19760,0.6096256684491979,2181 -matmul,4x20x40xf64,linalg_xdsl,3670,5879,5876,0.0,0,3200,3522,0,0.9596730245231607,0.9994324631101021,3524,0,0,0.9602179836512261,0,0,6.7251908396946565,6.7251908396946565,1,0.0,524,0.7517934002869441,173,0,0,0.04713896457765668,0,2210,5883,1.0073569482288829,2212 +matmul,4x20x40xf64,linalg_xdsl,3653,5882,5879,0.0,0,3200,3522,0,0.9641390637831919,0.9994324631101021,3524,0,0,0.9646865589926088,0,0,6.829457364341085,6.829457364341085,1,0.0,516,0.7759398496240602,149,0,0,0.04078839310156036,0,2230,5886,1.0054749520941693,2232 matmul,4x20x44xf64,baseline,19330,21574,21571,0.0,0,3344,3521,0,0.18215209518882566,0.32793145198845114,10737,0,0,0.5554578375581997,0,0,1.0,1.0,1,3.619047619047619,10737,0.8848689632437778,1397,76,21,0.07227108122090016,18,2245,21578,0.6277289187790999,2247 matmul,4x20x44xf64,linalg_xdsl,4030,6254,6251,0.0,0,3520,3874,0,0.9612903225806452,0.999484004127967,3876,0,0,0.961786600496278,0,0,6.729166666666667,6.729166666666667,1,0.0,576,0.7568988173455979,185,0,0,0.04590570719602978,0,2225,6258,1.0076923076923077,2227 matmul,4x20x48xf64,baseline,21074,23328,23325,0.0,0,3648,3841,0,0.18226250355888773,0.327926235806369,11713,0,0,0.5558033595900161,0,0,1.0,1.0,1,3.619047619047619,11713,0.8858720314627136,1509,76,21,0.07160482110657683,18,2255,23332,0.627408180696593,2257 -matmul,4x20x48xf64,linalg_xdsl,4390,6624,6621,0.0,0,3840,4226,0,0.9626423690205012,0.9995269631031221,4228,0,0,0.9630979498861048,0,0,6.732484076433121,6.732484076433121,1,0.0,628,0.7612121212121212,197,0,0,0.044874715261959,0,2235,6628,1.0079726651480638,2237 +matmul,4x20x48xf64,linalg_xdsl,4357,6629,6626,0.0,0,3840,4226,0,0.9699334404406702,0.9995269631031221,4228,0,0,0.9703924718843241,0,0,6.908496732026144,6.908496732026144,1,0.0,612,0.8042049934296978,149,0,0,0.03419784255221483,0,2273,6633,1.004590314436539,2275 matmul,4x20x4xf64,baseline,1852,3914,3911,0.0,0,304,321,0,0.17332613390928725,0.3285568065506653,977,0,0,0.5275377969762419,0,0,1.0,1.0,1,3.5384615384615383,977,0.8258664412510567,206,46,13,0.11123110151187905,13,2063,3918,0.638768898488121,2065 matmul,4x20x4xf64,linalg_xdsl,418,2509,2506,0.0,0,320,354,0,0.84688995215311,0.9943820224719101,356,0,0,0.8516746411483254,0,0,6.357142857142857,6.357142857142857,1,0.0,56,0.5233644859813084,51,0,0,0.12200956937799043,0,2092,2513,0.9736842105263158,2094 matmul,4x20x52xf64,baseline,22895,25156,25153,0.0,0,3952,4161,0,0.1817427385892116,0.327921822050595,12689,0,0,0.5542258134963965,0,0,1.0,1.0,1,3.0452488687782804,12689,0.8254618787405673,2683,1346,442,0.11718715876829001,31,2262,25160,0.6714129722646865,2264 matmul,4x20x52xf64,linalg_xdsl,4750,6999,6996,0.0,0,4160,4578,0,0.9637894736842105,0.9995633187772925,4580,0,0,0.9642105263157895,0,0,6.735294117647059,6.735294117647059,1,0.0,680,0.7649043869516311,209,0,0,0.044,0,2250,7003,1.0082105263157894,2252 matmul,4x20x56xf64,baseline,24639,26910,26907,0.0,0,4256,4481,0,0.18186614716506352,0.3279180387852177,13665,0,0,0.5546085474248144,0,0,1.0,1.0,1,3.042194092827004,13665,0.8261789600967352,2875,1442,474,0.1166849303949024,31,2272,26914,0.6712934778197167,2274 -matmul,4x20x56xf64,linalg_xdsl,5110,7369,7366,0.0,0,4480,4930,0,0.9647749510763209,0.9995944849959448,4932,0,0,0.9651663405088062,0,0,6.7377049180327875,6.737704918032787,1,0.0,732,0.7681007345225603,221,0,0,0.04324853228962818,0,2260,7373,1.0084148727984343,2262 +matmul,4x20x56xf64,linalg_xdsl,5060,7326,7323,0.0,0,4480,4930,0,0.974308300395257,0.9995944849959448,4932,0,0,0.974703557312253,0,0,6.966101694915254,6.966101694915254,1,0.0,708,0.8261376896149358,149,0,0,0.029446640316205534,0,2267,7330,1.0041501976284586,2269 matmul,4x20x60xf64,baseline,26383,28626,28623,0.0,0,4560,4801,0,0.181973240344161,0.32791475992077046,14641,0,0,0.5549406814994504,0,0,1.0,1.0,1,3.039525691699605,14641,0.8268014456742715,3067,1538,506,0.11624909979911306,31,2244,28630,0.6711897812985634,2246 -matmul,4x20x60xf64,linalg_xdsl,5470,7742,7739,0.0,0,4800,5282,0,0.9656307129798903,0.9996214988644966,5284,0,0,0.9659963436928702,0,0,6.7397959183673475,6.739795918367347,1,0.0,784,0.7708947885939036,233,0,0,0.04259597806215722,0,2273,7746,1.0085923217550274,2275 +matmul,4x20x60xf64,linalg_xdsl,5429,7724,7721,0.0,0,4800,5282,0,0.9729231902744521,0.9996214988644966,5284,0,0,0.9732915822435071,0,0,6.9162303664921465,6.9162303664921465,1,0.0,764,0.8153681963713981,173,0,0,0.03186590532326395,0,2296,7728,1.005157487566771,2298 matmul,4x20x64xf64,baseline,28147,30439,30436,0.0,0,4864,5121,0,0.18193768430028068,0.3279118908881347,15617,0,0,0.554837105197712,0,0,1.0,1.0,1,3.26425855513308,15617,0.784182776801406,4298,3434,1052,0.15269833374782393,41,2293,30443,0.7075354389455359,2295 matmul,4x20x64xf64,linalg_xdsl,5830,8114,8111,0.0,0,5120,5634,0,0.9663807890222984,0.9996451383960255,5636,0,0,0.9667238421955403,0,0,6.741626794258373,6.741626794258373,1,0.0,836,0.7733580018501388,245,0,0,0.04202401372212693,0,2285,8118,1.0087478559176672,2287 matmul,4x20x8xf64,baseline,3598,5715,5712,0.0,0,608,641,0,0.17815453029460812,0.32821300563236044,1953,0,0,0.5428015564202334,0,0,1.0,1.0,1,3.5384615384615383,1953,0.8785425101214575,270,46,13,0.07504168982768204,13,2118,5719,0.6178432462479154,2120 matmul,4x20x8xf64,linalg_xdsl,796,2915,2912,0.0,0,640,706,0,0.8869346733668342,0.9971751412429378,708,0,0,0.8894472361809045,0,0,6.555555555555556,6.555555555555555,1,0.0,108,0.5901639344262295,75,0,0,0.0942211055276382,0,2120,2919,0.9836683417085427,2122 matmul,4x24x12xf64,baseline,6405,8507,8504,0.0,0,1104,1153,0,0.18001561280249806,0.32895863052781743,3505,0,0,0.5472287275565965,0,0,1.0,1.0,1,3.619047619047619,3505,0.8945890760592139,413,76,21,0.06448087431693988,18,2103,8511,0.6117096018735364,2105 -matmul,4x24x12xf64,linalg_xdsl,1342,3470,3467,0.0,0,1152,1250,0,0.9314456035767511,0.9984025559105432,1252,0,0,0.9329359165424739,0,0,7.824999999999999,7.825,1,0.0,160,0.642570281124498,89,0,0,0.06631892697466468,0,2129,3474,0.9992548435171386,2131 +matmul,4x24x12xf64,linalg_xdsl,1333,3501,3498,0.0,0,1152,1250,0,0.9377344336084021,0.9984025559105432,1252,0,0,0.9392348087021756,0,0,8.025641025641026,8.025641025641026,1,0.0,156,0.6695278969957081,77,0,0,0.05776444111027757,0,2169,3505,0.9969992498124531,2171 matmul,4x24x16xf64,baseline,8490,10610,10607,0.0,0,1472,1537,0,0.18103651354534747,0.3289107639631928,4673,0,0,0.5504122497055359,0,0,1.0,1.0,1,3.36,4673,0.9036936762715142,498,84,25,0.058657243816254416,19,2121,10614,0.6090694935217903,2123 matmul,4x24x16xf64,linalg_xdsl,1766,3909,3906,0.0,0,1536,1666,0,0.9433748584371461,0.9988009592326139,1668,0,0,0.9445073612684032,0,0,7.867924528301886,7.867924528301887,1,0.0,212,0.6773162939297125,101,0,0,0.05719139297848245,0,2144,3913,1.0016987542468856,2146 matmul,4x24x20xf64,baseline,10570,12709,12706,0.0,0,1840,1921,0,0.18174077578051087,0.3288820407464475,5841,0,0,0.5526017029328287,0,0,1.0,1.0,1,3.36,5841,0.9099548216233058,578,84,25,0.054683065279091767,19,2140,12713,0.6072847682119205,2142 -matmul,4x24x20xf64,linalg_xdsl,2190,4349,4346,0.0,0,1920,2082,0,0.9506849315068493,0.9990403071017274,2084,0,0,0.9515981735159817,0,0,7.8939393939393945,7.893939393939394,1,0.0,264,0.7002652519893899,113,0,0,0.051598173515981734,0,2160,4353,1.0031963470319636,2162 +matmul,4x24x20xf64,linalg_xdsl,2181,4360,4357,0.0,0,1920,2082,0,0.9546079779917469,0.9990403071017274,2084,0,0,0.9555249885373682,0,0,8.015384615384615,8.015384615384615,1,0.0,260,0.7202216066481995,101,0,0,0.04630903255387437,0,2180,4364,1.0018340210912426,2182 matmul,4x24x24xf64,baseline,12726,14873,14870,0.0,0,2208,2305,0,0.18112525538268112,0.3288628905692681,7009,0,0,0.5507622190790508,0,0,1.0,1.0,1,3.067524115755627,7009,0.8394011976047904,1341,954,311,0.10537482319660538,32,2148,14877,0.6561370422756562,2150 -matmul,4x24x24xf64,linalg_xdsl,2613,4767,4764,0.0,0,2304,2498,0,0.9559892843474933,0.9992,2500,0,0,0.9567546880979717,0,0,7.9113924050632916,7.9113924050632916,1,0.0,316,0.7165532879818595,125,0,0,0.04783773440489859,0,2155,4771,1.0045924225028704,2157 +matmul,4x24x24xf64,linalg_xdsl,2603,4805,4802,0.0,0,2304,2498,0,0.9596619285439877,0.9992,2500,0,0,0.9604302727621975,0,0,8.116883116883118,8.116883116883116,1,0.0,308,0.7530562347188264,101,0,0,0.03880138301959278,0,2203,4809,0.9992316557817903,2205 matmul,4x24x28xf64,baseline,14800,16966,16963,0.0,0,2576,2689,0,0.1816891891891892,0.3288492112021524,8177,0,0,0.5525,0,0,1.0,1.0,1,3.0612813370473537,8177,0.8418614228353752,1536,1099,359,0.10378378378378378,32,2167,16970,0.6562837837837838,2169 -matmul,4x24x28xf64,linalg_xdsl,3038,5225,5222,0.0,0,2688,2914,0,0.9591836734693877,0.9993141289437586,2916,0,0,0.9598420013166556,0,0,7.923913043478261,7.923913043478261,1,0.0,368,0.7287128712871287,137,0,0,0.04509545753785385,0,2188,5229,1.0049374588545095,2190 +matmul,4x24x28xf64,linalg_xdsl,3019,5210,5207,0.0,0,2688,2914,0,0.965220271613117,0.9993141289437586,2916,0,0,0.96588274263001,0,0,8.191011235955056,8.191011235955056,1,0.0,356,0.7789934354485777,101,0,0,0.03345478635309705,0,2192,5214,0.999337528983107,2194 matmul,4x24x32xf64,baseline,16809,19011,19008,0.0,0,2944,3073,0,0.18281872806234756,0.32848743987172635,9355,0,0,0.5565470878695936,0,0,1.0,1.0,1,3.1379310344827585,9355,0.9075475358944509,953,91,29,0.05669581771669939,23,2203,19015,0.613242905586293,2205 matmul,4x24x32xf64,linalg_xdsl,3462,5666,5663,0.0,0,3072,3330,0,0.9618717504332756,0.9993997599039616,3332,0,0,0.9624494511842865,0,0,7.933333333333334,7.933333333333334,1,0.0,420,0.7381370826010545,149,0,0,0.04303870595031774,0,2205,5670,1.0054881571346042,2207 matmul,4x24x36xf64,baseline,19069,21267,21264,0.0,0,3312,3457,0,0.18128900309402696,0.32851848332224654,10523,0,0,0.5518380617756569,0,0,1.0,1.0,1,3.839080459770115,10523,0.886670037074486,1345,668,174,0.07053332634118202,28,2199,21271,0.6223713881168389,2201 -matmul,4x24x36xf64,linalg_xdsl,3886,6105,6102,0.0,0,3456,3746,0,0.963973237261966,0.9994663820704376,3748,0,0,0.9644879053010808,0,0,7.9406779661016955,7.940677966101695,1,0.0,472,0.7456556082148499,161,0,0,0.041430777148739065,0,2220,6109,1.0059186824498199,2222 +matmul,4x24x36xf64,linalg_xdsl,3861,6118,6115,0.0,0,3456,3746,0,0.9702149702149702,0.9994663820704376,3748,0,0,0.9707329707329707,0,0,8.147826086956522,8.147826086956522,1,0.0,460,0.7863247863247863,125,0,0,0.03237503237503238,0,2258,6122,1.003108003108003,2260 matmul,4x24x40xf64,baseline,22109,24363,24360,0.0,0,3680,3841,0,0.17373015514044055,0.3285433239243863,11691,0,0,0.5287891808765661,0,0,1.0,1.0,1,3.9314285714285715,11691,0.866641957005189,1799,1376,350,0.08136957799990954,32,2255,24367,0.6101587588764756,2257 -matmul,4x24x40xf64,linalg_xdsl,4310,6544,6541,0.0,0,3840,4162,0,0.965661252900232,0.9995196926032661,4164,0,0,0.9661252900232019,0,0,7.946564885496183,7.9465648854961835,1,0.0,524,0.7517934002869441,173,0,0,0.04013921113689095,0,2235,6548,1.0062645011600928,2237 +matmul,4x24x40xf64,linalg_xdsl,4293,6547,6544,0.0,0,3840,4162,0,0.9694852084789192,0.9995196926032661,4164,0,0,0.9699510831586303,0,0,8.069767441860463,8.069767441860465,1,0.0,516,0.7759398496240602,149,0,0,0.03470766363848125,0,2255,6551,1.0046587467971115,2257 matmul,4x24x44xf64,baseline,23509,25778,25775,0.0,0,4048,4225,0,0.17971840571695946,0.3288193633745817,12849,0,0,0.5465566378833638,0,0,1.0,1.0,1,3.190388170055453,12849,0.8089781527419253,3034,3452,1082,0.12905695691011954,47,2270,25782,0.6756135947934834,2272 matmul,4x24x44xf64,linalg_xdsl,4734,6983,6980,0.0,0,4224,4578,0,0.9670468948035488,0.9995633187772925,4580,0,0,0.9674693705111956,0,0,7.951388888888889,7.951388888888889,1,0.0,576,0.7568988173455979,185,0,0,0.03907900295732995,0,2250,6987,1.0065483734685257,2252 matmul,4x24x48xf64,baseline,25628,27909,27906,0.0,0,4416,4609,0,0.17984235991883876,0.3288150103445816,14017,0,0,0.5469408459497425,0,0,1.0,1.0,1,3.1884550084889645,14017,0.8098567136584238,3291,3756,1178,0.12841423443109098,47,2282,27913,0.6753550803808335,2284 -matmul,4x24x48xf64,linalg_xdsl,5158,7422,7419,0.0,0,4608,4994,0,0.9682047305157038,0.999599679743795,4996,0,0,0.9685924777045366,0,0,7.955414012738853,7.955414012738854,1,0.0,628,0.7612121212121212,197,0,0,0.03819309810003878,0,2265,7426,1.0067855758045754,2267 +matmul,4x24x48xf64,linalg_xdsl,5125,7427,7424,0.0,0,4608,4994,0,0.9744390243902439,0.999599679743795,4996,0,0,0.9748292682926829,0,0,8.163398692810457,8.163398692810457,1,0.0,612,0.8042049934296978,149,0,0,0.02907317073170732,0,2303,7431,1.0039024390243902,2305 matmul,4x24x4xf64,baseline,2229,4287,4284,0.0,0,368,385,0,0.1727231942575146,0.32934131736526945,1169,0,0,0.5244504262000897,0,0,1.0,1.0,1,3.619047619047619,1169,0.8220815752461322,253,76,21,0.11350381336922387,18,2059,4291,0.6379542395693136,2061 matmul,4x24x4xf64,linalg_xdsl,482,2578,2575,0.0,0,384,418,0,0.8672199170124482,0.9952380952380953,420,0,0,0.8713692946058091,0,0,7.5,7.5,1,0.0,56,0.5233644859813084,51,0,0,0.10580912863070539,0,2097,2582,0.9771784232365145,2099 matmul,4x24x52xf64,baseline,28804,31092,31089,0.0,0,4784,4993,0,0.1733439800027774,0.32881132696740206,15185,0,0,0.5271837244827108,0,0,1.0,1.0,1,3.1251972645975803,15185,0.7591361295805629,4818,5941,1901,0.16726843493959173,62,2289,31096,0.6944521594223025,2291 matmul,4x24x52xf64,linalg_xdsl,5582,7859,7856,0.0,0,4992,5410,0,0.9691866714439269,0.999630450849963,5412,0,0,0.9695449659620208,0,0,7.958823529411765,7.958823529411765,1,0.0,680,0.7649043869516311,209,0,0,0.03744177714080975,0,2278,7863,1.0069867431028305,2280 matmul,4x24x56xf64,baseline,30995,33296,33293,0.0,0,5152,5377,0,0.1734795934828198,0.32880816975478505,16353,0,0,0.5276012260041942,0,0,1.0,1.0,1,3.1242053789731052,16353,0.7597565508269838,5171,6389,2045,0.16683336021939021,62,2302,33300,0.6944345862235844,2304 -matmul,4x24x56xf64,linalg_xdsl,6006,8300,8297,0.0,0,5376,5826,0,0.97002997002997,0.9996568291008923,5828,0,0,0.9703629703629704,0,0,7.961748633879781,7.961748633879782,1,0.0,732,0.7681007345225603,221,0,0,0.0367965367965368,0,2295,8304,1.0071595071595072,2297 +matmul,4x24x56xf64,linalg_xdsl,5956,8257,8254,0.0,0,5376,5826,0,0.9781732706514439,0.9996568291008923,5828,0,0,0.9785090664875755,0,0,8.231638418079097,8.231638418079097,1,0.0,708,0.8261376896149358,149,0,0,0.025016789791806583,0,2302,8261,1.003525856279382,2304 matmul,4x24x60xf64,baseline,33187,35490,35487,0.0,0,5520,5761,0,0.1735920691837165,0.3288054334798242,17521,0,0,0.5279476903606835,0,0,1.0,1.0,1,3.1233439926907263,17521,0.7603280680437424,5523,6837,2189,0.16642058637418267,62,2304,35494,0.6943682767348661,2306 -matmul,4x24x60xf64,linalg_xdsl,6430,8713,8710,0.0,0,5760,6242,0,0.9707620528771385,0.9996796925048046,6244,0,0,0.9710730948678071,0,0,7.964285714285714,7.964285714285714,1,0.0,784,0.7708947885939036,233,0,0,0.03623639191290824,0,2284,8717,1.0073094867807153,2286 +matmul,4x24x60xf64,linalg_xdsl,6395,8728,8725,0.0,0,5760,6242,0,0.9760750586395621,0.9996796925048046,6244,0,0,0.9763878029710712,0,0,8.172774869109949,8.172774869109947,1,0.0,764,0.8153681963713981,173,0,0,0.027052384675527757,0,2334,8732,1.003440187646599,2336 matmul,4x24x64xf64,baseline,36914,39202,39199,0.0,0,5888,6145,0,0.16646800671831824,0.3288030392209321,18689,0,0,0.5062848783659316,0,0,1.0,1.0,1,3.4054054054054053,18689,0.7450863134393813,6394,8820,2590,0.17321341496451212,67,2289,39206,0.6794982933304438,2291 matmul,4x24x64xf64,linalg_xdsl,6853,9152,9149,0.0,0,6144,6658,0,0.9715453086239603,0.9996996996996997,6660,0,0,0.9718371516124326,0,0,7.966507177033493,7.966507177033493,1,0.0,836,0.7733580018501388,245,0,0,0.03575076608784474,0,2300,9156,1.0075879177002773,2302 matmul,4x24x8xf64,baseline,4325,6450,6447,0.0,0,736,769,0,0.17780346820809248,0.3290543431750107,2337,0,0,0.5403468208092486,0,0,1.0,1.0,1,3.619047619047619,2337,0.8752808988764045,333,76,21,0.0769942196531792,18,2126,6454,0.6173410404624278,2128 matmul,4x24x8xf64,linalg_xdsl,924,3010,3007,0.0,0,768,834,0,0.9025974025974026,0.9976076555023924,836,0,0,0.9047619047619048,0,0,7.7407407407407405,7.7407407407407405,1,0.0,108,0.5901639344262295,75,0,0,0.08116883116883117,0,2087,3014,0.9859307359307359,2089 matmul,4x28x12xf64,baseline,7498,9658,9655,0.0,0,1296,1345,0,0.17938116831154974,0.32957608429306545,4081,0,0,0.5442784742598026,0,0,1.0,1.0,1,3.2490421455938696,4081,0.8555555555555555,689,848,261,0.09189117097892771,38,2161,9662,0.6361696452387303,2163 -matmul,4x28x12xf64,linalg_xdsl,1534,3672,3669,0.0,0,1344,1442,0,0.940026075619296,0.9986149584487535,1444,0,0,0.9413298565840938,0,0,9.024999999999999,9.025,1,0.0,160,0.642570281124498,89,0,0,0.058018252933507174,0,2139,3676,0.999348109517601,2141 +matmul,4x28x12xf64,linalg_xdsl,1525,3703,3700,0.0,0,1344,1442,0,0.9455737704918032,0.9986149584487535,1444,0,0,0.9468852459016394,0,0,9.256410256410255,9.256410256410257,1,0.0,156,0.6695278969957081,77,0,0,0.050491803278688525,0,2179,3707,0.9973770491803279,2181 matmul,4x28x16xf64,baseline,9914,12088,12085,0.0,0,1728,1793,0,0.18085535606213435,0.3295350119463334,5441,0,0,0.548819850716159,0,0,1.0,1.0,1,3.2375366568914954,5441,0.8650238473767885,849,1104,341,0.0856364736735929,38,2175,12092,0.6344563243897519,2177 matmul,4x28x16xf64,linalg_xdsl,2022,4176,4173,0.0,0,1792,1922,0,0.950544015825915,0.998960498960499,1924,0,0,0.9515331355093967,0,0,9.075471698113207,9.075471698113208,1,0.0,212,0.6773162939297125,101,0,0,0.049950544015825916,0,2155,4180,1.0014836795252227,2157 matmul,4x28x20xf64,baseline,12845,15036,15033,0.0,0,2160,2241,0,0.17446477228493576,0.329510366122629,6801,0,0,0.529466718567536,0,0,1.0,1.0,1,3.449399656946827,6801,0.8349907918968692,1344,2011,583,0.10463215258855586,48,2192,15040,0.6340988711560919,2194 -matmul,4x28x20xf64,linalg_xdsl,2510,4684,4681,0.0,0,2240,2402,0,0.9569721115537848,0.9991680532445923,2404,0,0,0.9577689243027888,0,0,9.106060606060606,9.106060606060606,1,0.0,264,0.7002652519893899,113,0,0,0.0450199203187251,0,2175,4688,1.0027888446215139,2177 +matmul,4x28x20xf64,linalg_xdsl,2501,4695,4692,0.0,0,2240,2402,0,0.9604158336665334,0.9991680532445923,2404,0,0,0.9612155137944822,0,0,9.246153846153845,9.246153846153845,1,0.0,260,0.7202216066481995,101,0,0,0.040383846461415435,0,2195,4699,1.0015993602558977,2197 matmul,4x28x24xf64,baseline,15357,17576,17573,0.0,0,2592,2689,0,0.17509930324933254,0.3294939345668423,8161,0,0,0.5314188969199714,0,0,1.0,1.0,1,3.446043165467626,8161,0.8388323568712098,1568,2395,695,0.10210327537930586,48,2220,17580,0.6335221722992772,2222 -matmul,4x28x24xf64,linalg_xdsl,2998,5185,5182,0.0,0,2688,2882,0,0.9613075383589059,0.9993065187239945,2884,0,0,0.961974649766511,0,0,9.126582278481012,9.126582278481013,1,0.0,316,0.7165532879818595,125,0,0,0.04169446297531688,0,2188,5189,1.003669112741828,2190 +matmul,4x28x24xf64,linalg_xdsl,2981,5191,5188,0.0,0,2688,2882,0,0.966789667896679,0.9993065187239945,2884,0,0,0.967460583696746,0,0,9.363636363636363,9.363636363636363,1,0.0,308,0.7530562347188264,101,0,0,0.033881247903388124,0,2211,5195,1.0013418316001341,2213 matmul,4x28x28xf64,baseline,17874,20094,20091,0.0,0,3024,3137,0,0.17550632203200178,0.3294821972481882,9521,0,0,0.5326731565402261,0,0,1.0,1.0,1,3.442379182156134,9521,0.8417469719741845,1790,2778,807,0.10014546268322704,48,2221,20098,0.6328186192234531,2223 -matmul,4x28x28xf64,linalg_xdsl,3485,5674,5671,0.0,0,3136,3362,0,0.9647058823529412,0.9994054696789536,3364,0,0,0.9652797704447633,0,0,9.141304347826086,9.141304347826088,1,0.0,368,0.7287128712871287,137,0,0,0.03931133428981349,0,2190,5678,1.0045911047345768,2192 +matmul,4x28x28xf64,linalg_xdsl,3460,5667,5664,0.0,0,3136,3362,0,0.9716763005780347,0.9994054696789536,3364,0,0,0.9722543352601156,0,0,9.44943820224719,9.44943820224719,1,0.0,356,0.7789934354485777,101,0,0,0.029190751445086704,0,2208,5671,1.0014450867052023,2210 matmul,4x28x32xf64,baseline,21742,23973,23970,0.0,0,3456,3585,0,0.1648882347530126,0.3289292595650977,10899,0,0,0.5012878300064392,0,0,1.0,1.0,1,3.81077694235589,10899,0.8270602519350433,2279,3041,798,0.10482016373838653,48,2232,23977,0.6061079937448257,2234 matmul,4x28x32xf64,linalg_xdsl,3974,6198,6195,0.0,0,3584,3842,0,0.9667840966280825,0.9994797086368367,3844,0,0,0.9672873678912934,0,0,9.152380952380952,9.152380952380952,1,0.0,420,0.7381370826010545,149,0,0,0.03749370910920986,0,2225,6202,1.0047810770005032,2227 matmul,4x28x36xf64,baseline,24439,26675,26672,0.0,0,3888,4033,0,0.16502311878554768,0.32898278815564075,12259,0,0,0.5016162690781129,0,0,1.0,1.0,1,3.8131991051454137,12259,0.8206587227205784,2679,3409,894,0.10961986988010966,48,2237,26679,0.6112361389582225,2239 -matmul,4x28x36xf64,linalg_xdsl,4462,6701,6698,0.0,0,4032,4322,0,0.968623935454953,0.9995374653098983,4324,0,0,0.9690721649484536,0,0,9.161016949152543,9.161016949152541,1,0.0,472,0.7456556082148499,161,0,0,0.03608247422680412,0,2240,6705,1.0051546391752577,2242 +matmul,4x28x36xf64,linalg_xdsl,4437,6714,6711,0.0,0,4032,4322,0,0.9740815866576515,0.9995374653098983,4324,0,0,0.9745323416723011,0,0,9.4,9.4,1,0.0,460,0.7863247863247863,125,0,0,0.028172188415596124,0,2278,6718,1.0027045300878972,2280 matmul,4x28x40xf64,baseline,26559,28816,28813,0.0,0,4320,4481,0,0.16871870175834933,0.32946106903904127,13601,0,0,0.5121051244399262,0,0,1.0,1.0,1,3.5079950799507995,13601,0.797665826051258,3450,5704,1626,0.12989946910651756,63,2258,28820,0.6420045935464438,2260 -matmul,4x28x40xf64,linalg_xdsl,4950,7204,7201,0.0,0,4480,4802,0,0.9701010101010101,0.9995836802664446,4804,0,0,0.9705050505050505,0,0,9.16793893129771,9.16793893129771,1,0.0,524,0.7517934002869441,173,0,0,0.03494949494949495,0,2255,7208,1.0054545454545454,2257 +matmul,4x28x40xf64,linalg_xdsl,4933,7207,7204,0.0,0,4480,4802,0,0.973444151631867,0.9995836802664446,4804,0,0,0.9738495844313805,0,0,9.310077519379846,9.310077519379846,1,0.0,516,0.7759398496240602,149,0,0,0.030204743563754306,0,2275,7211,1.0040543279951348,2277 matmul,4x28x44xf64,baseline,30074,32341,32338,0.0,0,4752,4929,0,0.1638957238810933,0.329456587126529,14961,0,0,0.4974729001795571,0,0,1.0,1.0,1,3.315062580923608,14961,0.7551865125435364,4850,7681,2317,0.16126887012036975,78,2268,32345,0.6587417702999269,2270 matmul,4x28x44xf64,linalg_xdsl,5438,7710,7707,0.0,0,4928,5282,0,0.9713129827142332,0.9996214988644966,5284,0,0,0.9716807649871276,0,0,9.173611111111112,9.17361111111111,1,0.0,576,0.7568988173455979,185,0,0,0.0340198602427363,0,2273,7714,1.005700625229864,2275 matmul,4x28x48xf64,baseline,32784,35071,35068,0.0,0,5184,5377,0,0.16401293313811616,0.32945285215366704,16321,0,0,0.4978343094192289,0,0,1.0,1.0,1,3.3144554455445543,16321,0.7560218639985177,5267,8369,2525,0.16065763787213275,78,2288,35075,0.6584919472913616,2290 -matmul,4x28x48xf64,linalg_xdsl,5926,8215,8212,0.0,0,5376,5762,0,0.9723253459331759,0.9996530187369882,5764,0,0,0.9726628417144786,0,0,9.178343949044587,9.178343949044587,1,0.0,628,0.7612121212121212,197,0,0,0.03324333445831927,0,2290,8219,1.0059061761727979,2292 +matmul,4x28x48xf64,linalg_xdsl,5893,8220,8217,0.0,0,5376,5762,0,0.9777702358730698,0.9996530187369882,5764,0,0,0.9781096215849313,0,0,9.418300653594772,9.418300653594772,1,0.0,612,0.8042049934296978,149,0,0,0.025284235533684033,0,2328,8224,1.0033938571186154,2330 matmul,4x28x4xf64,baseline,2661,4780,4777,0.0,0,432,449,0,0.1687335588124765,0.3299044819985305,1361,0,0,0.5114618564449455,0,0,1.0,1.0,1,3.3267326732673266,1361,0.7867052023121387,369,336,101,0.1386696730552424,38,2120,4784,0.6501315295001878,2122 matmul,4x28x4xf64,linalg_xdsl,546,2642,2639,0.0,0,448,482,0,0.8827838827838828,0.9958677685950413,484,0,0,0.8864468864468864,0,0,8.642857142857144,8.642857142857142,1,0.0,56,0.5233644859813084,51,0,0,0.09340659340659341,0,2097,2646,0.9798534798534798,2099 matmul,4x28x52xf64,baseline,37580,39864,39861,0.0,0,5616,5825,0,0.15500266098988824,0.3294496917595159,17681,0,0,0.47048962213943585,0,0,1.0,1.0,1,3.4035476718403546,17681,0.7300768023783962,6537,10745,3157,0.17394890899414583,88,2285,39868,0.6444385311335816,2287 matmul,4x28x52xf64,linalg_xdsl,6414,8718,8715,0.0,0,5824,6242,0,0.9731836607421266,0.9996796925048046,6244,0,0,0.9734954786404739,0,0,9.182352941176472,9.18235294117647,1,0.0,680,0.7649043869516311,209,0,0,0.032584970377299655,0,2305,8722,1.0060804490177735,2307 matmul,4x28x56xf64,baseline,40444,42748,42745,0.0,0,6048,6273,0,0.15510335278409654,0.32944698282653223,19041,0,0,0.4707991296607655,0,0,1.0,1.0,1,3.4032970267883424,19041,0.7307160948653005,7017,11561,3397,0.17349915933142124,88,2305,42752,0.6442982889921867,2307 -matmul,4x28x56xf64,linalg_xdsl,6902,9226,9223,0.0,0,6272,6722,0,0.9739206027238482,0.9997025580011898,6724,0,0,0.9742103738046943,0,0,9.185792349726775,9.185792349726777,1,0.0,732,0.7681007345225603,221,0,0,0.03201970443349754,0,2325,9230,1.0062300782381919,2327 +matmul,4x28x56xf64,linalg_xdsl,6852,9183,9180,0.0,0,6272,6722,0,0.9810274372446001,0.9997025580011898,6724,0,0,0.9813193228254524,0,0,9.497175141242938,9.497175141242938,1,0.0,708,0.8261376896149358,149,0,0,0.021745475773496788,0,2332,9187,1.0030647985989491,2334 matmul,4x28x60xf64,baseline,43776,46092,46089,0.0,0,6480,6721,0,0.15353161549707603,0.32944463506690846,20401,0,0,0.466031615497076,0,0,1.0,1.0,1,3.338190816607094,20401,0.731297272108112,7496,12141,3637,0.17123538011695907,88,2317,46096,0.6372669956140351,2319 -matmul,4x28x60xf64,linalg_xdsl,7390,9727,9724,0.0,0,6720,7202,0,0.9745602165087957,0.9997223764575236,7204,0,0,0.974830852503383,0,0,9.188775510204081,9.188775510204081,1,0.0,784,0.7708947885939036,233,0,0,0.031529093369418136,0,2338,9731,1.0063599458728012,2340 +matmul,4x28x60xf64,linalg_xdsl,7349,9709,9706,0.0,0,6720,7202,0,0.9799972785412981,0.9997223764575236,7204,0,0,0.9802694244114846,0,0,9.429319371727749,9.429319371727749,1,0.0,764,0.8153681963713981,173,0,0,0.023540617771125323,0,2361,9713,1.00381004218261,2363 matmul,4x28x64xf64,baseline,46207,48560,48557,0.0,0,6912,7169,0,0.1551496526500314,0.32944258076375166,21761,0,0,0.470945960568745,0,0,1.0,1.0,1,3.299044151115157,21761,0.7070080249520777,9018,14496,4394,0.19516523470469843,98,2354,48564,0.6661111952734434,2356 matmul,4x28x64xf64,linalg_xdsl,7878,10232,10229,0.0,0,7168,7682,0,0.9751205889819751,0.9997397188964081,7684,0,0,0.9753744605229754,0,0,9.191387559808613,9.191387559808613,1,0.0,836,0.7733580018501388,245,0,0,0.0310992637725311,0,2355,10236,1.0064737242955064,2357 matmul,4x28x8xf64,baseline,5082,7244,7241,0.0,0,864,897,0,0.17650531286894924,0.3296582138919515,2721,0,0,0.5354191263282172,0,0,1.0,1.0,1,3.270718232044199,2721,0.8372307692307692,529,592,181,0.10409287682014955,38,2163,7248,0.6395120031483668,2165 matmul,4x28x8xf64,linalg_xdsl,1052,3148,3145,0.0,0,896,962,0,0.9144486692015209,0.9979253112033195,964,0,0,0.9163498098859315,0,0,8.925925925925926,8.925925925925926,1,0.0,108,0.5901639344262295,75,0,0,0.07129277566539924,0,2097,3152,0.9876425855513308,2099 matmul,4x32x12xf64,baseline,10822,12943,12940,0.0,0,1532,1582,0,0.1461836998706339,0.33645257337303275,4702,0,0,0.43448530770652377,0,0,1.0,1.0,1,3.5555555555555554,4702,0.44670340110203305,5824,32,9,0.538163001293661,9,2122,12947,0.9726483090001847,2124 -matmul,4x32x12xf64,linalg_xdsl,1726,3849,3846,0.0,0,1536,1634,0,0.9466975666280417,0.9987775061124694,1636,0,0,0.947856315179606,0,0,10.225000000000001,10.225,1,0.0,160,0.642570281124498,89,0,0,0.051564310544611816,0,2124,3853,0.9994206257242179,2126 +matmul,4x32x12xf64,linalg_xdsl,1723,3896,3893,0.0,0,1536,1634,0,0.9483459082994776,0.9987775061124694,1636,0,0,0.9495066744051074,0,0,10.487179487179487,10.487179487179487,1,0.0,156,0.6695278969957081,77,0,0,0.04468949506674405,0,2174,3900,0.9941961694718514,2176 matmul,4x32x16xf64,baseline,14581,16745,16742,0.0,0,2044,2110,0,0.14470886770454702,0.3365231259968102,6270,0,0,0.43001165900829846,0,0,1.0,1.0,1,3.25,6270,0.43910637999859936,8009,39,12,0.5492764556614773,12,2165,16749,0.9792881146697758,2167 matmul,4x32x16xf64,linalg_xdsl,2277,4426,4423,0.0,0,2048,2178,0,0.9565217391304348,0.9990825688073395,2180,0,0,0.9574000878348704,0,0,10.283018867924527,10.283018867924529,1,0.0,212,0.6773162939297125,101,0,0,0.04435660957400088,0,2150,4430,1.0017566974088712,2152 matmul,4x32x20xf64,baseline,17480,19638,19635,0.0,0,2540,2624,0,0.15011441647597254,0.33537832310838445,7824,0,0,0.4475972540045767,0,0,1.0,1.0,1,0.0,7824,0.48686994399502176,8246,0,0,0.4717391304347826,0,2159,19642,0.9193363844393593,2161 -matmul,4x32x20xf64,linalg_xdsl,2830,5012,5009,0.0,0,2560,2722,0,0.9618374558303887,0.9992657856093979,2724,0,0,0.9625441696113074,0,0,10.318181818181818,10.318181818181818,1,0.0,264,0.7002652519893899,113,0,0,0.03992932862190813,0,2183,5016,1.0024734982332155,2185 +matmul,4x32x20xf64,linalg_xdsl,2827,5028,5025,0.0,0,2560,2722,0,0.9628581535196321,0.9992657856093979,2724,0,0,0.9635656172621153,0,0,10.476923076923077,10.476923076923077,1,0.0,260,0.7202216066481995,101,0,0,0.03572691899540149,0,2202,5032,0.9992925362575168,2204 matmul,4x32x24xf64,baseline,20955,23159,23156,0.0,0,3048,3148,0,0.15022667621092817,0.33532168726033235,9388,0,0,0.44800763540921024,0,0,1.0,1.0,1,0.0,9388,0.48708104181799317,9886,0,0,0.47177284657599616,0,2205,23163,0.9197804819852065,2207 -matmul,4x32x24xf64,linalg_xdsl,3382,5586,5583,0.0,0,3072,3266,0,0.9657007687758723,0.9993880048959608,3268,0,0,0.9662921348314607,0,0,10.341772151898734,10.341772151898734,1,0.0,316,0.7165532879818595,125,0,0,0.03696037847427558,0,2205,5590,1.0032525133057364,2207 +matmul,4x32x24xf64,linalg_xdsl,3365,5607,5604,0.0,0,3072,3266,0,0.9705794947994056,0.9993880048959608,3268,0,0,0.9711738484398217,0,0,10.61038961038961,10.61038961038961,1,0.0,308,0.7530562347188264,101,0,0,0.030014858841010402,0,2243,5611,1.001188707280832,2245 matmul,4x32x28xf64,baseline,24448,26666,26663,0.0,0,3556,3672,0,0.15019633507853403,0.3352812271731191,10952,0,0,0.4479712041884817,0,0,1.0,1.0,1,0.0,10952,0.486366462385647,11566,0,0,0.4730857329842932,0,2219,26670,0.9210569371727748,2221 -matmul,4x32x28xf64,linalg_xdsl,3934,6132,6129,0.0,0,3584,3810,0,0.9684799186578547,0.9994753410283316,3812,0,0,0.9689883070665989,0,0,10.358695652173912,10.358695652173912,1,0.0,368,0.7287128712871287,137,0,0,0.034824605998983224,0,2199,6136,1.0038129130655822,2201 +matmul,4x32x28xf64,linalg_xdsl,3908,6126,6123,0.0,0,3584,3810,0,0.9749232343909928,0.9994753410283316,3812,0,0,0.9754350051177073,0,0,10.707865168539325,10.707865168539326,1,0.0,356,0.7789934354485777,101,0,0,0.02584442169907881,0,2219,6130,1.0012794268167862,2221 matmul,4x32x32xf64,baseline,27936,30186,30183,0.0,0,4064,4196,0,0.1502004581901489,0.33525087887503996,12516,0,0,0.4480240549828179,0,0,1.0,1.0,1,0.0,12516,0.48581298761790165,13247,0,0,0.4741910080183276,0,2251,30190,0.9222150630011454,2253 matmul,4x32x32xf64,linalg_xdsl,4485,6701,6698,0.0,0,4096,4354,0,0.9707915273132665,0.9995408631772268,4356,0,0,0.9712374581939799,0,0,10.371428571428572,10.371428571428572,1,0.0,420,0.7381370826010545,149,0,0,0.03322185061315496,0,2217,6705,1.0044593088071347,2219 matmul,4x32x36xf64,baseline,31411,33682,33679,0.0,0,4572,4720,0,0.15026583044156505,0.3352272727272727,14080,0,0,0.44825061284263473,0,0,1.0,1.0,1,0.0,14080,0.4852160727824109,14938,0,0,0.4755658845627328,0,2272,33686,0.9238164974053675,2274 -matmul,4x32x36xf64,linalg_xdsl,5038,7295,7292,0.0,0,4608,4898,0,0.9722111949186185,0.9995918367346939,4900,0,0,0.9726081778483525,0,0,10.38135593220339,10.38135593220339,1,0.0,472,0.7456556082148499,161,0,0,0.03195712584358872,0,2258,7299,1.0045653036919413,2260 +matmul,4x32x36xf64,linalg_xdsl,5013,7293,7290,0.0,0,4608,4898,0,0.9770596449231996,0.9995918367346939,4900,0,0,0.9774586076201875,0,0,10.652173913043478,10.652173913043478,1,0.0,460,0.7863247863247863,125,0,0,0.02493516856173948,0,2281,7297,1.002393776181927,2283 matmul,4x32x40xf64,baseline,34908,37187,37184,0.0,0,5080,5244,0,0.15022344448264008,0.3352083866018921,15644,0,0,0.44814942133608343,0,0,1.0,1.0,1,0.0,15644,0.48337659127425536,16720,0,0,0.47897330124899734,0,2280,37191,0.9271227225850808,2282 -matmul,4x32x40xf64,linalg_xdsl,5590,7869,7866,0.0,0,5120,5442,0,0.9735241502683363,0.9996326230712711,5444,0,0,0.9738819320214669,0,0,10.389312977099236,10.389312977099237,1,0.0,524,0.7517934002869441,173,0,0,0.030948121645796065,0,2280,7873,1.004830053667263,2282 +matmul,4x32x40xf64,linalg_xdsl,5573,7872,7869,0.0,0,5120,5442,0,0.9764938094383635,0.9996326230712711,5444,0,0,0.9768526825767091,0,0,10.550387596899226,10.550387596899224,1,0.0,516,0.7759398496240602,149,0,0,0.026736048806746814,0,2300,7876,1.003588731383456,2302 matmul,4x32x44xf64,baseline,38413,40718,40715,0.0,0,5588,5768,0,0.15015749876343945,0.33519293351929336,17208,0,0,0.44797334235805586,0,0,1.0,1.0,1,3.0,17208,0.48208432553578934,18487,6,2,0.48126936193476166,2,2306,40722,0.9292427042928175,2308 matmul,4x32x44xf64,linalg_xdsl,6142,8415,8412,0.0,0,5632,5986,0,0.9746011071312276,0.9996659986639946,5988,0,0,0.9749267339628785,0,0,10.395833333333334,10.395833333333334,1,0.0,576,0.7568988173455979,185,0,0,0.030120481927710843,0,2274,8419,1.0050472158905894,2276 matmul,4x32x48xf64,baseline,41897,44222,44219,0.0,0,6096,6292,0,0.15017781702747213,0.33518005540166207,18772,0,0,0.4480511731150202,0,0,1.0,1.0,1,3.0,18772,0.48213689482470784,20163,6,2,0.4812516409289448,2,2326,44226,0.929302814043965,2328 -matmul,4x32x48xf64,linalg_xdsl,6693,8992,8989,0.0,0,6144,6530,0,0.9756461975197968,0.9996938150642989,6532,0,0,0.9759450171821306,0,0,10.401273885350317,10.401273885350319,1,0.0,628,0.7612121212121212,197,0,0,0.029433736739877484,0,2300,8996,1.005378753922008,2302 +matmul,4x32x48xf64,linalg_xdsl,6667,9014,9011,0.0,0,6144,6530,0,0.9794510274486276,0.9996938150642989,6532,0,0,0.9797510124493776,0,0,10.673202614379084,10.673202614379084,1,0.0,612,0.8042049934296978,149,0,0,0.022348882555872206,0,2348,9018,1.0020998950052498,2350 matmul,4x32x4xf64,baseline,3302,5430,5427,0.0,0,508,526,0,0.15929739551786795,0.33588761174968074,1566,0,0,0.4742580254391278,0,0,1.0,1.0,1,0.0,1566,0.489375,1634,0,0,0.49485160508782555,0,2129,5434,0.9691096305269533,2131 matmul,4x32x4xf64,linalg_xdsl,608,2695,2692,0.0,0,512,546,0,0.8980263157894737,0.9963503649635036,548,0,0,0.9013157894736842,0,0,9.785714285714286,9.785714285714286,1,0.0,56,0.5185185185185185,52,0,0,0.08552631578947369,0,2088,2699,0.9868421052631579,2090 matmul,4x32x52xf64,baseline,45385,47693,47690,0.0,0,6604,6816,0,0.1501817781205244,0.3351691581431943,20336,0,0,0.44807755866475707,0,0,1.0,1.0,1,3.6,20336,0.4802682851947193,22007,18,5,0.48489589071279054,5,2309,47697,0.9329734493775477,2311 matmul,4x32x52xf64,linalg_xdsl,7246,9578,9575,0.0,0,6656,7074,0,0.9762627656638145,0.9997173544375353,7076,0,0,0.9765387800165609,0,0,10.405882352941177,10.405882352941177,1,0.0,680,0.7649043869516311,209,0,0,0.028843499861992822,0,2333,9582,1.0053822798785537,2335 matmul,4x32x56xf64,baseline,48869,51235,51232,0.0,0,7112,7340,0,0.15019746669667888,0.33515981735159817,21900,0,0,0.44813685567537703,0,0,1.0,1.0,1,3.6,21900,0.48031582410352014,23695,18,5,0.4848677075446602,5,2367,51239,0.9330045632200372,2369 -matmul,4x32x56xf64,linalg_xdsl,7798,10152,10149,0.0,0,7168,7618,0,0.976917158245704,0.9997375328083989,7620,0,0,0.9771736342651962,0,0,10.40983606557377,10.40983606557377,1,0.0,732,0.7681007345225603,221,0,0,0.028340600153885613,0,2355,10156,1.0055142344190817,2357 +matmul,4x32x56xf64,linalg_xdsl,7748,10109,10106,0.0,0,7168,7618,0,0.9832214765100671,0.9997375328083989,7620,0,0,0.9834796076406814,0,0,10.76271186440678,10.76271186440678,1,0.0,708,0.8261376896149358,149,0,0,0.019230769230769232,0,2362,10113,1.0027103768714507,2364 matmul,4x32x60xf64,baseline,52357,54737,54734,0.0,0,7620,7864,0,0.1501995912676433,0.33515172178656666,23464,0,0,0.44815401951983497,0,0,1.0,1.0,1,3.6,23464,0.4803471994759253,25384,18,5,0.4848253337662586,5,2381,54741,0.9329793532860935,2383 -matmul,4x32x60xf64,linalg_xdsl,8350,10698,10695,0.0,0,7680,8162,0,0.9774850299401198,0.9997550220480157,8164,0,0,0.9777245508982036,0,0,10.41326530612245,10.41326530612245,1,0.0,784,0.7708947885939036,233,0,0,0.027904191616766466,0,2349,10702,1.0056287425149701,2351 +matmul,4x32x60xf64,linalg_xdsl,8315,10713,10710,0.0,0,7680,8162,0,0.9815995189416716,0.9997550220480157,8164,0,0,0.9818400481058328,0,0,10.68586387434555,10.68586387434555,1,0.0,764,0.8153681963713981,173,0,0,0.020805772699939867,0,2399,10717,1.0026458208057727,2401 matmul,4x32x64xf64,baseline,55841,58234,58231,0.0,0,8128,8388,0,0.15021220966673232,0.3351446380054339,25028,0,0,0.4482011425296825,0,0,1.0,1.0,1,3.375,25028,0.4785376952639529,27273,27,8,0.4884045772819255,8,2394,58238,0.936605719811608,2396 matmul,4x32x64xf64,linalg_xdsl,8901,11270,11267,0.0,0,8192,8706,0,0.97809234917425,0.9997703261368857,8708,0,0,0.9783170430288731,0,0,10.416267942583731,10.416267942583731,1,0.0,836,0.7733580018501388,245,0,0,0.027524997191326818,0,2370,11274,1.0058420402202,2372 matmul,4x32x8xf64,baseline,7141,9291,9288,0.0,0,1020,1054,0,0.14759837557765018,0.3363114231014678,3134,0,0,0.43887410726788967,0,0,1.0,1.0,1,4.0,3134,0.45479611086924976,3757,12,3,0.5261167903654951,3,2151,9295,0.9649908976333847,2153 matmul,4x32x8xf64,linalg_xdsl,1172,3269,3266,0.0,0,1024,1090,0,0.9300341296928327,0.9981684981684982,1092,0,0,0.931740614334471,0,0,10.111111111111112,10.11111111111111,1,0.0,108,0.5901639344262295,75,0,0,0.06399317406143344,0,2098,3273,0.9957337883959044,2100 matmul,4x36x12xf64,baseline,12455,14589,14586,0.0,0,1728,1778,0,0.1427539140907266,0.33661491859144266,5282,0,0,0.4240867121637896,0,0,1.0,1.0,1,3.7142857142857144,5282,0.4266903627110429,7097,26,7,0.569811320754717,7,2135,14593,0.9938980329185065,2137 -matmul,4x36x12xf64,linalg_xdsl,1918,4072,4069,0.0,0,1728,1826,0,0.9520333680917622,0.9989059080962801,1828,0,0,0.9530761209593326,0,0,11.424999999999999,11.425,1,0.0,160,0.642570281124498,89,0,0,0.04640250260688217,0,2155,4076,0.9994786235662148,2157 +matmul,4x36x12xf64,linalg_xdsl,1909,4101,4098,0.0,0,1728,1826,0,0.9565217391304348,0.9989059080962801,1828,0,0,0.9575694080670508,0,0,11.717948717948717,11.717948717948717,1,0.0,156,0.6695278969957081,77,0,0,0.04033525405971713,0,2193,4105,0.997904662126768,2195 matmul,4x36x16xf64,baseline,16678,18850,18847,0.0,0,2304,2370,0,0.14210336970859816,0.33655211587617156,7042,0,0,0.42223288164048445,0,0,1.0,1.0,1,3.3,7042,0.4248310810810811,9534,33,10,0.5716512771315505,10,2173,18854,0.993884158772035,2175 matmul,4x36x16xf64,linalg_xdsl,2534,4708,4705,0.0,0,2304,2434,0,0.9605367008681925,0.9991789819376026,2436,0,0,0.9613259668508287,0,0,11.490566037735851,11.49056603773585,1,0.0,212,0.6773162939297125,101,0,0,0.039857932123125495,0,2175,4712,1.001183898973954,2177 matmul,4x36x20xf64,baseline,20955,23184,23181,0.0,0,2880,2965,0,0.1414936769267478,0.336740488358887,8805,0,0,0.42018611309949894,0,0,1.0,1.0,1,0.0,8805,0.4211105265675068,12104,0,0,0.577618706752565,0,2230,23188,0.9978048198520639,2232 -matmul,4x36x20xf64,linalg_xdsl,3150,5347,5344,0.0,0,2880,3042,0,0.9657142857142857,0.9993429697766097,3044,0,0,0.9663492063492064,0,0,11.530303030303031,11.530303030303031,1,0.0,264,0.7002652519893899,113,0,0,0.035873015873015876,0,2198,5351,1.0022222222222223,2200 +matmul,4x36x20xf64,linalg_xdsl,3147,5363,5360,0.0,0,2880,3042,0,0.9666348903717826,0.9993429697766097,3044,0,0,0.967270416269463,0,0,11.707692307692307,11.707692307692307,1,0.0,260,0.7202216066481995,101,0,0,0.03209405783285669,0,2217,5367,0.9993644741023197,2219 matmul,4x36x24xf64,baseline,25131,27367,27364,0.0,0,3456,3557,0,0.14153833910309976,0.33667770941788927,10565,0,0,0.4203971190959373,0,0,1.0,1.0,1,0.0,10565,0.4211680287024118,14520,0,0,0.5777724722454339,0,2237,27371,0.9981695913413713,2239 -matmul,4x36x24xf64,linalg_xdsl,3766,5985,5982,0.0,0,3456,3650,0,0.969198088157196,0.9994523548740416,3652,0,0,0.9697291556027615,0,0,11.556962025316457,11.556962025316455,1,0.0,316,0.7165532879818595,125,0,0,0.03319171534784918,0,2220,5989,1.0029208709506108,2222 +matmul,4x36x24xf64,linalg_xdsl,3749,6006,6003,0.0,0,3456,3650,0,0.973592958122166,0.9994523548740416,3652,0,0,0.9741264337156575,0,0,11.857142857142858,11.857142857142858,1,0.0,308,0.7530562347188264,101,0,0,0.026940517471325687,0,2258,6010,1.0010669511869832,2260 matmul,4x36x28xf64,baseline,29307,31563,31560,0.0,0,4032,4149,0,0.14157027331354283,0.33663286004056797,12325,0,0,0.42054799194731635,0,0,1.0,1.0,1,0.0,12325,0.42120911793855303,16936,0,0,0.5778824171699594,0,2257,31567,0.9984304091172758,2259 -matmul,4x36x28xf64,linalg_xdsl,4382,6621,6618,0.0,0,4032,4258,0,0.971702418986764,0.9995305164319249,4260,0,0,0.9721588315837517,0,0,11.576086956521738,11.576086956521738,1,0.0,368,0.7287128712871287,137,0,0,0.031264262893655866,0,2240,6625,1.0034230944774076,2242 +matmul,4x36x28xf64,linalg_xdsl,4356,6602,6599,0.0,0,4032,4258,0,0.9775022956841138,0.9995305164319249,4260,0,0,0.977961432506887,0,0,11.96629213483146,11.96629213483146,1,0.0,356,0.7789934354485777,101,0,0,0.023186409550045913,0,2247,6606,1.0011478420569329,2249 matmul,4x36x32xf64,baseline,33483,35772,35769,0.0,0,4608,4741,0,0.1415942418540752,0.33659921902733403,14085,0,0,0.42066123107248454,0,0,1.0,1.0,1,0.0,14085,0.4212399437748602,19352,0,0,0.5779649374309351,0,2290,35776,0.9986261685034197,2292 matmul,4x36x32xf64,linalg_xdsl,4998,7255,7252,0.0,0,4608,4866,0,0.9735894357743097,0.9995891536565324,4868,0,0,0.9739895958383353,0,0,11.59047619047619,11.59047619047619,1,0.0,420,0.7381370826010545,149,0,0,0.029811924769907964,0,2258,7259,1.0038015206082433,2260 matmul,4x36x36xf64,baseline,37653,39957,39954,0.0,0,5184,5333,0,0.14163546065386556,0.33657305143578414,15845,0,0,0.42081640241149443,0,0,1.0,1.0,1,0.0,15845,0.4212639247068833,21768,0,0,0.5781212652378297,0,2305,39961,0.9989376676493241,2307 -matmul,4x36x36xf64,linalg_xdsl,5614,7878,7875,0.0,0,5184,5474,0,0.9750623441396509,0.9996347699050402,5476,0,0,0.9754185963662273,0,0,11.601694915254237,11.601694915254237,1,0.0,472,0.7456556082148499,161,0,0,0.028678304239401497,0,2265,7882,1.0040969006056288,2267 +matmul,4x36x36xf64,linalg_xdsl,5596,7908,7905,0.0,0,5184,5474,0,0.9781987133666905,0.9996347699050402,5476,0,0,0.9785561115082202,0,0,11.904347826086957,11.904347826086957,1,0.0,460,0.7863247863247863,125,0,0,0.022337383845604002,0,2313,7912,1.0008934953538242,2315 matmul,4x36x40xf64,baseline,41835,44156,44153,0.0,0,5760,5925,0,0.14162782359268555,0.33655211587617156,17605,0,0,0.42081988765387834,0,0,1.0,1.0,1,0.0,17605,0.4212831127808753,24184,0,0,0.5780805545595793,0,2322,44160,0.9989004422134576,2324 -matmul,4x36x40xf64,linalg_xdsl,6230,8534,8531,0.0,0,5760,6082,0,0.9762439807383627,0.9996712689020382,6084,0,0,0.9765650080256821,0,0,11.610687022900763,11.610687022900763,1,0.0,524,0.7517934002869441,173,0,0,0.027768860353130018,0,2305,8538,1.0043338683788121,2307 +matmul,4x36x40xf64,linalg_xdsl,6213,8537,8534,0.0,0,5760,6082,0,0.9789151778528891,0.9996712689020382,6084,0,0,0.9792370835345244,0,0,11.790697674418604,11.790697674418604,1,0.0,516,0.7759398496240602,149,0,0,0.023981973281828425,0,2325,8541,1.0032190568163528,2327 matmul,4x36x44xf64,baseline,46011,48352,48349,0.0,0,6336,6517,0,0.14164004259850904,0.3365349857991221,19365,0,0,0.4208776162222077,0,0,1.0,1.0,1,0.0,19365,0.42129881431523986,26600,0,0,0.5781226228510573,0,2342,48356,0.9990002390732651,2344 matmul,4x36x44xf64,linalg_xdsl,6846,9170,9167,0.0,0,6336,6690,0,0.9772129710780018,0.9997011356843993,6692,0,0,0.9775051124744376,0,0,11.618055555555555,11.618055555555555,1,0.0,576,0.7568988173455979,185,0,0,0.027023079170318435,0,2325,9174,1.0045281916447562,2327 matmul,4x36x48xf64,baseline,50187,52561,52558,0.0,0,6912,7109,0,0.14165022814673123,0.3365207100591716,21125,0,0,0.42092573774084924,0,0,1.0,1.0,1,0.0,21125,0.42131190044075706,29016,0,0,0.5781576902385079,0,2375,52565,0.9990834279793572,2377 -matmul,4x36x48xf64,linalg_xdsl,7462,9804,9801,0.0,0,6912,7298,0,0.978021978021978,0.9997260273972602,7300,0,0,0.9782900026802466,0,0,11.624203821656051,11.624203821656051,1,0.0,628,0.7612121212121212,197,0,0,0.02640042883945323,0,2343,9808,1.0046904315196998,2345 +matmul,4x36x48xf64,linalg_xdsl,7429,9794,9791,0.0,0,6912,7298,0,0.9823664019383497,0.9997260273972602,7300,0,0,0.9826356171759322,0,0,11.928104575163399,11.928104575163399,1,0.0,612,0.8042049934296978,149,0,0,0.020056535199892315,0,2366,9798,1.0026921523758245,2368 matmul,4x36x4xf64,baseline,4120,6212,6209,0.0,0,575,592,0,0.1436893203883495,0.33636363636363636,1760,0,0,0.42718446601941745,0,0,1.0,1.0,1,0.0,1760,0.4427672955974843,2215,0,0,0.537621359223301,0,2093,6216,0.9648058252427185,2095 matmul,4x36x4xf64,linalg_xdsl,672,2764,2761,0.0,0,576,610,0,0.9077380952380952,0.9967320261437909,612,0,0,0.9107142857142857,0,0,10.928571428571427,10.928571428571429,1,0.0,56,0.5185185185185185,52,0,0,0.07738095238095238,0,2093,2768,0.9880952380952381,2095 matmul,4x36x52xf64,baseline,54363,56744,56741,0.0,0,7488,7701,0,0.14165884884940125,0.336508630107057,22885,0,0,0.4209664661626474,0,0,1.0,1.0,1,0.0,22885,0.42132297439107463,31432,0,0,0.578187370086272,0,2382,56748,0.9991538362489194,2384 matmul,4x36x52xf64,linalg_xdsl,8078,10442,10439,0.0,0,7488,7906,0,0.9787076008913097,0.9997470915528579,7908,0,0,0.9789551869274573,0,0,11.629411764705882,11.629411764705882,1,0.0,680,0.7649043869516311,209,0,0,0.025872740777420154,0,2365,10446,1.0048279277048775,2367 matmul,4x36x56xf64,baseline,58539,60940,60937,0.0,0,8064,8293,0,0.1416662396009498,0.3364982755122743,24645,0,0,0.42100138369292267,0,0,1.0,1.0,1,0.0,24645,0.4213324671328193,33848,0,0,0.5782128153880319,0,2402,60944,0.9992141990809547,2404 -matmul,4x36x56xf64,linalg_xdsl,8694,11078,11075,0.0,0,8064,8514,0,0.979296066252588,0.9997651479567872,8516,0,0,0.9795261099608926,0,0,11.633879781420767,11.633879781420765,1,0.0,732,0.7681007345225603,221,0,0,0.025419829767655854,0,2385,11082,1.0049459397285485,2387 +matmul,4x36x56xf64,linalg_xdsl,8644,11035,11032,0.0,0,8064,8514,0,0.9849606663581675,0.9997651479567872,8516,0,0,0.985192040721888,0,0,12.028248587570621,12.028248587570621,1,0.0,708,0.8261376896149358,149,0,0,0.017237390097177233,0,2392,11039,1.0024294308190653,2394 matmul,4x36x60xf64,baseline,62715,65149,65146,0.0,0,8640,8885,0,0.14167264609742486,0.33648930126869914,26405,0,0,0.4210316511201467,0,0,1.0,1.0,1,0.0,26405,0.42134069476136526,36264,0,0,0.5782348720401818,0,2435,65153,0.9992665231603284,2437 -matmul,4x36x60xf64,linalg_xdsl,9310,11712,11709,0.0,0,8640,9122,0,0.9798066595059076,0.9997807978956598,9124,0,0,0.9800214822771214,0,0,11.637755102040817,11.637755102040817,1,0.0,784,0.7708947885939036,233,0,0,0.02502685284640172,0,2403,11716,1.005048335123523,2405 +matmul,4x36x60xf64,linalg_xdsl,9269,11694,11691,0.0,0,8640,9122,0,0.9841406840004315,0.9997807978956598,9124,0,0,0.9843564570072284,0,0,11.942408376963352,11.942408376963352,1,0.0,764,0.8153681963713981,173,0,0,0.0186643650879275,0,2426,11698,1.003020822095156,2428 matmul,4x36x64xf64,baseline,66891,69337,69334,0.0,0,9216,9477,0,0.1416782526797327,0.3364814486064264,28165,0,0,0.4210581393610501,0,0,1.0,1.0,1,0.0,28165,0.42134789438252673,38680,0,0,0.5782541747021274,0,2447,69341,0.9993123140631774,2449 matmul,4x36x64xf64,linalg_xdsl,9926,12355,12352,0.0,0,9216,9730,0,0.9802538787023978,0.9997944923962186,9732,0,0,0.9804553697360467,0,0,11.641148325358852,11.641148325358852,1,0.0,836,0.7733580018501388,245,0,0,0.02468265162200282,0,2430,12359,1.0051380213580496,2432 matmul,4x36x8xf64,baseline,8352,10485,10482,0.0,0,1152,1186,0,0.14200191570881227,0.336740488358887,3522,0,0,0.42169540229885055,0,0,1.0,1.0,1,3.0,3522,0.4245419479267117,4774,6,2,0.5715996168582376,2,2134,10489,0.9932950191570882,2136 matmul,4x36x8xf64,linalg_xdsl,1302,3435,3432,0.0,0,1152,1218,0,0.9354838709677419,0.9983606557377049,1220,0,0,0.9370199692780338,0,0,11.296296296296298,11.296296296296296,1,0.0,108,0.5837837837837838,77,0,0,0.05913978494623656,0,2134,3439,0.9961597542242704,2136 matmul,4x40x12xf64,baseline,13799,15943,15940,0.0,0,1920,1970,0,0.1427639684035075,0.3362922499146466,5858,0,0,0.4245235161968259,0,0,1.0,1.0,1,3.7142857142857144,5858,0.42687459010420464,7865,26,7,0.5699688383216175,7,2145,15947,0.9944923545184434,2147 -matmul,4x40x12xf64,linalg_xdsl,2110,4274,4271,0.0,0,1920,2018,0,0.9563981042654028,0.999009900990099,2020,0,0,0.957345971563981,0,0,12.625,12.625,1,0.0,160,0.642570281124498,89,0,0,0.042180094786729856,0,2165,4278,0.999526066350711,2167 +matmul,4x40x12xf64,linalg_xdsl,2101,4303,4300,0.0,0,1920,2018,0,0.9604950023798191,0.999009900990099,2020,0,0,0.9614469300333175,0,0,12.948717948717949,12.948717948717949,1,0.0,156,0.6695278969957081,77,0,0,0.03664921465968586,0,2203,4307,0.9980961446930033,2205 matmul,4x40x16xf64,baseline,18470,20673,20670,0.0,0,2560,2626,0,0.14217650243638333,0.33623559539052494,7810,0,0,0.42284786139685976,0,0,1.0,1.0,1,3.3,7810,0.4251959930313589,10558,33,10,0.571629669734705,10,2204,20677,0.9944775311315648,2206 matmul,4x40x16xf64,linalg_xdsl,2790,4972,4969,0.0,0,2560,2690,0,0.96415770609319,0.9992570579494799,2692,0,0,0.9648745519713262,0,0,12.69811320754717,12.69811320754717,1,0.0,212,0.6773162939297125,101,0,0,0.03620071684587814,0,2183,4976,1.0010752688172044,2185 matmul,4x40x20xf64,baseline,23195,25421,25418,0.0,0,3200,3285,0,0.141625350291011,0.33640552995391704,9765,0,0,0.4209959042897176,0,0,1.0,1.0,1,0.0,9765,0.4218324765648624,13384,0,0,0.57702090967881,0,2227,25425,0.9980168139685277,2229 -matmul,4x40x20xf64,linalg_xdsl,3472,5681,5678,0.0,0,3200,3362,0,0.9683179723502304,0.9994054696789536,3364,0,0,0.9688940092165899,0,0,12.742424242424242,12.742424242424242,1,0.0,264,0.7002652519893899,113,0,0,0.032546082949308754,0,2210,5685,1.0014400921658986,2212 +matmul,4x40x20xf64,linalg_xdsl,3461,5690,5687,0.0,0,3200,3362,0,0.9713955504189541,0.9994054696789536,3364,0,0,0.971973418087258,0,0,12.938461538461539,12.938461538461539,1,0.0,260,0.7202216066481995,101,0,0,0.029182317249349898,0,2230,5694,1.0011557353366078,2232 matmul,4x40x24xf64,baseline,27819,30070,30067,0.0,0,3840,3941,0,0.14166576800028757,0.3363488947682854,11717,0,0,0.4211869585535066,0,0,1.0,1.0,1,0.0,11717,0.42188456414503295,16056,0,0,0.5771594953089615,0,2252,30074,0.998346453862468,2254 -matmul,4x40x24xf64,linalg_xdsl,4150,6384,6381,0.0,0,3840,4034,0,0.9720481927710843,0.9995044598612488,4036,0,0,0.9725301204819277,0,0,12.772151898734176,12.772151898734178,1,0.0,316,0.7165532879818595,125,0,0,0.030120481927710843,0,2235,6388,1.0026506024096384,2237 +matmul,4x40x24xf64,linalg_xdsl,4133,6405,6402,0.0,0,3840,4034,0,0.9760464553593031,0.9995044598612488,4036,0,0,0.9765303653520445,0,0,13.103896103896103,13.103896103896103,1,0.0,308,0.7530562347188264,101,0,0,0.02443745463343818,0,2273,6409,1.0009678199854828,2275 matmul,4x40x28xf64,baseline,32443,34727,34724,0.0,0,4480,4597,0,0.1416946644884875,0.33630843514521913,13669,0,0,0.42132355207594857,0,0,1.0,1.0,1,0.0,13669,0.42192178288113097,18728,0,0,0.5772585765804642,0,2285,34731,0.9985821286564127,2287 -matmul,4x40x28xf64,linalg_xdsl,4830,7082,7079,0.0,0,4480,4706,0,0.9743271221532092,0.9995751911639762,4708,0,0,0.9747412008281573,0,0,12.793478260869565,12.793478260869565,1,0.0,368,0.7287128712871287,137,0,0,0.02836438923395445,0,2253,7086,1.0031055900621118,2255 +matmul,4x40x28xf64,linalg_xdsl,4811,7067,7064,0.0,0,4480,4706,0,0.9781750155892746,0.9995751911639762,4708,0,0,0.9785907295780503,0,0,13.224719101123595,13.224719101123595,1,0.0,356,0.7789934354485777,101,0,0,0.020993556433173976,0,2257,7071,0.9995842860112243,2259 matmul,4x40x32xf64,baseline,37067,39363,39360,0.0,0,5120,5253,0,0.14171635147165942,0.3362780871903207,15621,0,0,0.4214260663123533,0,0,1.0,1.0,1,0.0,15621,0.42194970422192807,21400,0,0,0.5773329376534384,0,2297,39367,0.9987590039657916,2299 matmul,4x40x32xf64,linalg_xdsl,5510,7789,7786,0.0,0,5120,5378,0,0.976043557168784,0.9996282527881041,5380,0,0,0.9764065335753176,0,0,12.80952380952381,12.80952380952381,1,0.0,420,0.7381370826010545,149,0,0,0.027041742286751363,0,2280,7793,1.0034482758620689,2282 matmul,4x40x36xf64,baseline,41691,44012,44009,0.0,0,5760,5909,0,0.14173322779496775,0.33625448130654984,17573,0,0,0.42150584058909596,0,0,1.0,1.0,1,0.0,17573,0.42197142514107333,24072,0,0,0.5773908037705979,0,2322,44016,0.9988966443596938,2324 -matmul,4x40x36xf64,linalg_xdsl,6190,8494,8491,0.0,0,5760,6050,0,0.9773828756058158,0.9996695307336417,6052,0,0,0.9777059773828756,0,0,12.822033898305085,12.822033898305085,1,0.0,472,0.7456556082148499,161,0,0,0.026009693053311793,0,2305,8498,1.0037156704361874,2307 +matmul,4x40x36xf64,linalg_xdsl,6165,8507,8504,0.0,0,5760,6050,0,0.981346309813463,0.9996695307336417,6052,0,0,0.9816707218167072,0,0,13.156521739130435,13.156521739130435,1,0.0,460,0.7863247863247863,125,0,0,0.0202757502027575,0,2343,8511,1.0019464720194646,2345 matmul,4x40x40xf64,baseline,46309,48658,48655,0.0,0,6400,6565,0,0.1417650996566542,0.33623559539052494,19525,0,0,0.4216243062903539,0,0,1.0,1.0,1,0.0,19525,0.4219888045991917,26744,0,0,0.5775119307262088,0,2350,48662,0.9991362370165626,2352 -matmul,4x40x40xf64,linalg_xdsl,6869,9173,9170,0.0,0,6400,6722,0,0.9785995050225651,0.9997025580011898,6724,0,0,0.9788906682195371,0,0,12.83206106870229,12.83206106870229,1,0.0,524,0.7517934002869441,173,0,0,0.025185616538069586,0,2305,9177,1.0040762847576066,2307 +matmul,4x40x40xf64,linalg_xdsl,6853,9159,9156,0.0,0,6400,6722,0,0.9808842842550708,0.9997025580011898,6724,0,0,0.981176127243543,0,0,13.031007751937983,13.031007751937985,1,0.0,516,0.7759398496240602,149,0,0,0.021742302641179045,0,2307,9163,1.002918429884722,2309 matmul,4x40x44xf64,baseline,50939,53318,53315,0.0,0,7040,7221,0,0.1417577887276939,0.3362201424779997,21477,0,0,0.421621939967412,0,0,1.0,1.0,1,0.0,21477,0.42200302595641837,29416,0,0,0.5774750191405407,0,2380,53322,0.9990969591079526,2382 matmul,4x40x44xf64,linalg_xdsl,7550,9897,9894,0.0,0,7040,7394,0,0.9793377483443708,0.9997295835586804,7396,0,0,0.9796026490066225,0,0,12.840277777777779,12.840277777777779,1,0.0,576,0.7568988173455979,185,0,0,0.024503311258278145,0,2348,9901,1.0041059602649007,2350 matmul,4x40x48xf64,baseline,55563,57949,57946,0.0,0,7680,7877,0,0.14176700322156832,0.33620726450125915,23429,0,0,0.42166549682342563,0,0,1.0,1.0,1,0.0,23429,0.42201487832555795,32088,0,0,0.5775066141137087,0,2387,57953,0.9991721109371343,2389 -matmul,4x40x48xf64,linalg_xdsl,8230,10599,10596,0.0,0,7680,8066,0,0.9800729040097206,0.9997521070897373,8068,0,0,0.9803159173754556,0,0,12.847133757961782,12.847133757961783,1,0.0,628,0.7612121212121212,197,0,0,0.02393681652490887,0,2370,10603,1.0042527339003646,2372 +matmul,4x40x48xf64,linalg_xdsl,8197,10604,10601,0.0,0,7680,8066,0,0.9840185433695254,0.9997521070897373,8068,0,0,0.9842625350738075,0,0,13.183006535947712,13.183006535947712,1,0.0,612,0.8042049934296978,149,0,0,0.018177381969013053,0,2408,10608,1.0024399170428204,2410 matmul,4x40x4xf64,baseline,4643,6760,6757,0.0,0,640,657,0,0.14150333835881973,0.33640552995391704,1953,0,0,0.4206332112858066,0,0,1.0,1.0,1,0.0,1953,0.42725880551301687,2618,0,0,0.563859573551583,0,2118,6764,0.9844927848373897,2120 matmul,4x40x4xf64,linalg_xdsl,736,2833,2830,0.0,0,640,674,0,0.9157608695652174,0.9970414201183432,676,0,0,0.9184782608695652,0,0,12.071428571428573,12.071428571428571,1,0.0,56,0.5185185185185185,52,0,0,0.07065217391304347,0,2098,2837,0.9891304347826086,2100 matmul,4x40x52xf64,baseline,60187,62598,62595,0.0,0,8320,8533,0,0.14177480186751293,0.33619636736141206,25381,0,0,0.4217023609749614,0,0,1.0,1.0,1,0.0,25381,0.42202490813255517,34760,0,0,0.5775333543788526,0,2412,62602,0.999235715353814,2414 matmul,4x40x52xf64,linalg_xdsl,8916,11310,11307,0.0,0,8320,8738,0,0.9800358905338717,0.9997711670480549,8740,0,0,0.9802602063705698,0,0,12.852941176470589,12.852941176470589,1,0.0,680,0.7649043869516311,209,0,0,0.02344100493494841,0,2395,11314,1.0037012113055181,2397 matmul,4x40x56xf64,baseline,64811,67260,67257,0.0,0,8960,9189,0,0.14178148771041954,0.336187026671057,27333,0,0,0.42173396491336346,0,0,1.0,1.0,1,0.0,27333,0.42203350575156334,37432,0,0,0.5775562790267085,0,2450,67264,0.9992902439400719,2452 -matmul,4x40x56xf64,linalg_xdsl,9590,12007,12004,0.0,0,8960,9410,0,0.9812304483837331,0.9997875053123672,9412,0,0,0.9814389989572472,0,0,12.857923497267759,12.857923497267759,1,0.0,732,0.7681007345225603,221,0,0,0.023044838373305527,0,2418,12011,1.0044838373305527,2420 +matmul,4x40x56xf64,linalg_xdsl,9547,11968,11965,0.0,0,8960,9410,0,0.9856499423902797,0.9997875053123672,9412,0,0,0.9858594322823924,0,0,13.293785310734464,13.293785310734464,1,0.0,708,0.8261376896149358,149,0,0,0.015606996962396565,0,2422,11972,1.001466429244789,2424 matmul,4x40x60xf64,baseline,69429,71888,71885,0.0,0,9600,9845,0,0.14179953621685462,0.3361789311934437,29285,0,0,0.42179780783246196,0,0,1.0,1.0,1,0.0,29285,0.4220409575004684,40104,0,0,0.5776260640366417,0,2460,71892,0.9994238718691038,2462 -matmul,4x40x60xf64,linalg_xdsl,10270,12688,12685,0.0,0,9600,10082,0,0.9816942551119766,0.9998016660055533,10084,0,0,0.9818889970788705,0,0,12.862244897959185,12.862244897959183,1,0.0,784,0.7708947885939036,233,0,0,0.022687439143135344,0,2419,12692,1.0045764362220058,2421 +matmul,4x40x60xf64,linalg_xdsl,10235,12703,12700,0.0,0,9600,10082,0,0.9850512945774303,0.9998016660055533,10084,0,0,0.9852467024914509,0,0,13.198952879581153,13.198952879581151,1,0.0,764,0.8153681963713981,173,0,0,0.016902784562774793,0,2469,12707,1.0021494870542256,2471 matmul,4x40x64xf64,baseline,74053,76537,76534,0.0,0,10240,10501,0,0.1418038431933885,0.3361718474885552,31237,0,0,0.42181950764992643,0,0,1.0,1.0,1,0.0,31237,0.4220474781457312,42776,0,0,0.5776403386763534,0,2485,76541,0.9994598463262798,2487 matmul,4x40x64xf64,linalg_xdsl,10949,13393,13390,0.0,0,10240,10754,0,0.9821901543519956,0.9998140572703608,10756,0,0,0.9823728194355649,0,0,12.866028708133971,12.866028708133971,1,0.0,836,0.7733580018501388,245,0,0,0.022376472737236277,0,2445,13397,1.0047492921728012,2447 matmul,4x40x8xf64,baseline,9248,11386,11383,0.0,0,1280,1314,0,0.1420847750865052,0.33640552995391704,3906,0,0,0.42236159169550175,0,0,1.0,1.0,1,3.0,3906,0.42493472584856395,5286,6,2,0.571583044982699,2,2139,11390,0.9939446366782008,2141 matmul,4x40x8xf64,linalg_xdsl,1430,3568,3565,0.0,0,1280,1346,0,0.9412587412587412,0.9985163204747775,1348,0,0,0.9426573426573427,0,0,12.481481481481483,12.481481481481481,1,0.0,108,0.5837837837837838,77,0,0,0.05384615384615385,0,2139,3572,0.9965034965034966,2141 matmul,4x44x12xf64,baseline,15143,17297,17294,0.0,0,2112,2162,0,0.14277223799775474,0.33602735467827166,6434,0,0,0.42488278412467806,0,0,1.0,1.0,1,3.7142857142857144,6434,0.4270259507533019,8633,26,7,0.5700983952981575,7,2155,17301,0.9949811794228356,2157 -matmul,4x44x12xf64,linalg_xdsl,2302,4476,4473,0.0,0,2112,2210,0,0.9600347523892268,0.9990958408679927,2212,0,0,0.9609035621198957,0,0,13.825000000000001,13.825,1,0.0,160,0.642570281124498,89,0,0,0.03866203301476977,0,2175,4480,0.9995655951346655,2177 +matmul,4x44x12xf64,linalg_xdsl,2293,4505,4502,0.0,0,2112,2210,0,0.963802878325338,0.9990958408679927,2212,0,0,0.9646750981247274,0,0,14.179487179487179,14.179487179487179,1,0.0,156,0.6695278969957081,77,0,0,0.033580462276493674,0,2213,4509,0.9982555604012211,2215 matmul,4x44x16xf64,baseline,20262,22470,22467,0.0,0,2816,2882,0,0.14223669923995658,0.3359757519235253,8578,0,0,0.42335406179054386,0,0,1.0,1.0,1,3.3,8578,0.42549603174603173,11582,33,10,0.5716118843154674,10,2209,22474,0.9949659461060112,2211 matmul,4x44x16xf64,linalg_xdsl,3046,5243,5240,0.0,0,2816,2946,0,0.9671700590938936,0.9993215739484396,2948,0,0,0.9678266579120157,0,0,13.905660377358492,13.90566037735849,1,0.0,212,0.6773162939297125,101,0,0,0.03315824031516743,0,2198,5247,1.0009848982271832,2200 matmul,4x44x20xf64,baseline,25435,27676,27673,0.0,0,3520,3605,0,0.1417338313347749,0.3361305361305361,10725,0,0,0.4216630627088657,0,0,1.0,1.0,1,0.0,10725,0.42242703533026116,14664,0,0,0.5765284057401219,0,2242,27680,0.9981914684489877,2244 -matmul,4x44x20xf64,linalg_xdsl,3790,6014,6011,0.0,0,3520,3682,0,0.9715039577836412,0.999457111834962,3684,0,0,0.9720316622691293,0,0,13.954545454545455,13.954545454545455,1,0.0,264,0.7002652519893899,113,0,0,0.029815303430079154,0,2225,6018,1.0018469656992084,2227 +matmul,4x44x20xf64,linalg_xdsl,3781,6025,6022,0.0,0,3520,3682,0,0.9738164506744248,0.999457111834962,3684,0,0,0.9743454112668606,0,0,14.169230769230769,14.169230769230769,1,0.0,260,0.7202216066481995,101,0,0,0.026712509918011107,0,2245,6029,1.0010579211848718,2247 matmul,4x44x24xf64,baseline,30507,32773,32770,0.0,0,4224,4325,0,0.1417707411413774,0.33607894941331884,12869,0,0,0.42183761104008916,0,0,1.0,1.0,1,0.0,12869,0.4224746397032271,17592,0,0,0.5766545383026846,0,2267,32777,0.9984921493427739,2269 -matmul,4x44x24xf64,linalg_xdsl,4534,6783,6780,0.0,0,4224,4418,0,0.9744155271283634,0.9995475113122172,4420,0,0,0.9748566387295986,0,0,13.987341772151899,13.987341772151899,1,0.0,316,0.7165532879818595,125,0,0,0.02756947507719453,0,2250,6787,1.0024261138067931,2252 +matmul,4x44x24xf64,linalg_xdsl,4517,6804,6801,0.0,0,4224,4418,0,0.9780827983174674,0.9995475113122172,4420,0,0,0.9785255700686296,0,0,14.35064935064935,14.35064935064935,1,0.0,308,0.7530562347188264,101,0,0,0.02235997343369493,0,2288,6808,1.0008855435023245,2290 matmul,4x44x28xf64,baseline,35579,37883,37880,0.0,0,4928,5045,0,0.14179712751904214,0.3360420968493972,15013,0,0,0.42196239354675513,0,0,1.0,1.0,1,0.0,15013,0.42250865392733516,20520,0,0,0.5767447089575312,0,2305,37887,0.9987071025042863,2307 -matmul,4x44x28xf64,linalg_xdsl,5278,7550,7547,0.0,0,4928,5154,0,0.9765062523683213,0.9996121024049651,5156,0,0,0.9768851837817355,0,0,14.01086956521739,14.01086956521739,1,0.0,368,0.7287128712871287,137,0,0,0.025956801818870785,0,2273,7554,1.0028419856006063,2275 +matmul,4x44x28xf64,linalg_xdsl,5259,7535,7532,0.0,0,4928,5154,0,0.980034227039361,0.9996121024049651,5156,0,0,0.9804145274767065,0,0,14.48314606741573,14.48314606741573,1,0.0,356,0.7789934354485777,101,0,0,0.019205172085947898,0,2277,7539,0.9996196995626544,2279 matmul,4x44x32xf64,baseline,40651,42967,42964,0.0,0,5632,5765,0,0.1418169294728297,0.33601445474150493,17157,0,0,0.4220560379818455,0,0,1.0,1.0,1,0.0,17157,0.42253417066863685,23448,0,0,0.5768123785392734,0,2317,42971,0.9988684165211188,2319 matmul,4x44x32xf64,linalg_xdsl,6022,8321,8318,0.0,0,5632,5890,0,0.9780803719694454,0.9996605566870332,5892,0,0,0.9784124875456659,0,0,14.028571428571428,14.028571428571428,1,0.0,420,0.7381370826010545,149,0,0,0.024742610428429093,0,2300,8325,1.003155097974095,2302 matmul,4x44x36xf64,baseline,45723,48064,48061,0.0,0,6336,6485,0,0.14183233821052862,0.3359929537329672,19301,0,0,0.4221289066771647,0,0,1.0,1.0,1,0.0,19301,0.4225540206230707,26376,0,0,0.5768650351026835,0,2342,48068,0.9989939417798481,2344 -matmul,4x44x36xf64,linalg_xdsl,6766,9090,9087,0.0,0,6336,6626,0,0.9793083062370677,0.9996982498491249,6628,0,0,0.9796039018622524,0,0,14.042372881355933,14.042372881355933,1,0.0,472,0.7456556082148499,161,0,0,0.023795447827372154,0,2325,9094,1.0033993496896245,2327 +matmul,4x44x36xf64,linalg_xdsl,6741,9103,9100,0.0,0,6336,6626,0,0.9829402165850764,0.9996982498491249,6628,0,0,0.9832369084705533,0,0,14.408695652173913,14.408695652173913,1,0.0,460,0.7863247863247863,125,0,0,0.018543242842308263,0,2363,9107,1.0017801513128617,2365 matmul,4x44x40xf64,baseline,50795,53174,53171,0.0,0,7040,7205,0,0.14184466975095975,0.3359757519235253,21445,0,0,0.422187223151885,0,0,1.0,1.0,1,0.0,21445,0.42256990285522866,29304,0,0,0.5769071759031401,0,2380,53178,0.9990943990550252,2382 -matmul,4x44x40xf64,linalg_xdsl,7510,9857,9854,0.0,0,7040,7362,0,0.9802929427430093,0.9997284084736556,7364,0,0,0.9805592543275633,0,0,14.053435114503817,14.053435114503817,1,0.0,524,0.7517934002869441,173,0,0,0.02303595206391478,0,2348,9861,1.0035952063914781,2350 +matmul,4x44x40xf64,linalg_xdsl,7499,9865,9862,0.0,0,7040,7362,0,0.9817308974529937,0.9997284084736556,7364,0,0,0.9819975996799574,0,0,14.271317829457363,14.271317829457365,1,0.0,516,0.7759398496240602,149,0,0,0.01986931590878784,0,2367,9869,1.0018669155887452,2369 matmul,4x44x44xf64,baseline,55861,58255,58252,0.0,0,7744,7925,0,0.1418699987468896,0.3359616770528636,23589,0,0,0.42228030289468504,0,0,1.0,1.0,1,0.0,23589,0.42258289890901274,32232,0,0,0.5770036340201572,0,2395,58259,0.9992839369148423,2397 matmul,4x44x44xf64,linalg_xdsl,8253,10607,10604,0.0,0,7744,8098,0,0.9812189506845995,0.9997530864197531,8100,0,0,0.9814612868047983,0,0,14.0625,14.0625,1,0.0,576,0.7568988173455979,185,0,0,0.022416091118381196,0,2355,10611,1.0038773779231795,2357 matmul,4x44x48xf64,baseline,60939,63355,63352,0.0,0,8448,8645,0,0.1418631746500599,0.3359499475381805,25733,0,0,0.42227473375014357,0,0,1.0,1.0,1,0.0,25733,0.4225937299853842,35160,0,0,0.5769704130359868,0,2417,63359,0.9992451467861304,2419 -matmul,4x44x48xf64,linalg_xdsl,8998,11397,11394,0.0,0,8448,8834,0,0.9817737274949989,0.9997736532367587,8836,0,0,0.9819959991109135,0,0,14.070063694267516,14.070063694267516,1,0.0,628,0.7612121212121212,197,0,0,0.0218937541675928,0,2400,11401,1.0038897532785063,2402 +matmul,4x44x48xf64,linalg_xdsl,8965,11402,11399,0.0,0,8448,8834,0,0.9853876185164528,0.9997736532367587,8836,0,0,0.9856107083100948,0,0,14.437908496732026,14.437908496732026,1,0.0,612,0.8042049934296978,149,0,0,0.016620189626324597,0,2438,11406,1.0022308979364194,2440 matmul,4x44x4xf64,baseline,5091,7213,7210,0.0,0,704,721,0,0.14162247102730308,0.3361305361305361,2145,0,0,0.4213317619328226,0,0,1.0,1.0,1,0.0,2145,0.4273759713090257,2874,0,0,0.5645256334708308,0,2123,7217,0.9858573954036535,2125 matmul,4x44x4xf64,linalg_xdsl,800,2902,2899,0.0,0,704,738,0,0.9225,0.9972972972972973,740,0,0,0.925,0,0,13.214285714285714,13.214285714285714,1,0.0,56,0.5185185185185185,52,0,0,0.065,0,2103,2906,0.99,2105 matmul,4x44x52xf64,baseline,66011,68465,68462,0.0,0,9152,9365,0,0.1418702943448819,0.33594002224055675,27877,0,0,0.4223084031449304,0,0,1.0,1.0,1,0.0,27877,0.42260289547487306,38088,0,0,0.576994743300359,0,2455,68469,0.9993031464452895,2457 matmul,4x44x52xf64,linalg_xdsl,9742,12164,12161,0.0,0,9152,9570,0,0.9823444877848491,0.9997910572503134,9572,0,0,0.9825497844385137,0,0,14.076470588235296,14.076470588235294,1,0.0,680,0.7649043869516311,209,0,0,0.02145350030794498,0,2423,12168,1.0040032847464586,2425 matmul,4x44x56xf64,baseline,71083,73549,73546,0.0,0,9856,10085,0,0.14187639801358976,0.33593151460644216,30021,0,0,0.4223372677011381,0,0,1.0,1.0,1,0.0,30021,0.4226107521432493,41016,0,0,0.57701560147996,0,2467,73553,0.9993528691810981,2469 -matmul,4x44x56xf64,linalg_xdsl,10486,12935,12932,0.0,0,9856,10306,0,0.9828342551974061,0.9998059759410167,10308,0,0,0.9830249856952127,0,0,14.081967213114753,14.081967213114755,1,0.0,732,0.7681007345225603,221,0,0,0.02107572000762922,0,2450,12939,1.004100705702842,2452 +matmul,4x44x56xf64,linalg_xdsl,10436,12892,12889,0.0,0,9856,10306,0,0.9875431199693369,0.9998059759410167,10308,0,0,0.987734764277501,0,0,14.559322033898304,14.559322033898304,1,0.0,708,0.8261376896149358,149,0,0,0.01427750095822154,0,2457,12896,1.0020122652357224,2459 matmul,4x44x60xf64,baseline,76155,78659,78656,0.0,0,10560,10805,0,0.14188168866128292,0.3359241411472097,32165,0,0,0.4223622874400893,0,0,1.0,1.0,1,0.0,32165,0.4226175616549948,43944,0,0,0.5770336813078589,0,2505,78663,0.9993959687479482,2507 -matmul,4x44x60xf64,linalg_xdsl,11230,13702,13699,0.0,0,10560,11042,0,0.9832591273374889,0.9998189061934082,11044,0,0,0.9834372217275156,0,0,14.08673469387755,14.08673469387755,1,0.0,784,0.7708947885939036,233,0,0,0.0207479964381122,0,2473,13706,1.0041852181656277,2475 +matmul,4x44x60xf64,linalg_xdsl,11189,13684,13681,0.0,0,10560,11042,0,0.9868620967021181,0.9998189061934082,11044,0,0,0.9870408436857628,0,0,14.455497382198953,14.455497382198953,1,0.0,764,0.8153681963713981,173,0,0,0.015461614085262311,0,2496,13688,1.002502457771025,2498 matmul,4x44x64xf64,baseline,81227,83743,83740,0.0,0,11264,11525,0,0.14188631858864664,0.3359176892360605,34309,0,0,0.422384182599382,0,0,1.0,1.0,1,0.0,34309,0.42262352028183936,46872,0,0,0.5770495032439952,0,2517,83747,0.9994336858433772,2519 matmul,4x44x64xf64,linalg_xdsl,11974,14473,14470,0.0,0,11264,11778,0,0.9836312009353599,0.999830220713073,11780,0,0,0.983798229497244,0,0,14.090909090909092,14.090909090909092,1,0.0,836,0.7733580018501388,245,0,0,0.020460998830800065,0,2500,14477,1.004259228328044,2502 matmul,4x44x8xf64,baseline,10147,12294,12291,0.0,0,1408,1442,0,0.14211096875923918,0.3361305361305361,4290,0,0,0.4227850596235341,0,0,1.0,1.0,1,3.0,4290,0.4252577319587629,5798,6,2,0.5714004139154429,2,2148,12298,0.994185473538977,2150 matmul,4x44x8xf64,linalg_xdsl,1558,3707,3704,0.0,0,1408,1474,0,0.9460847240051348,0.9986449864498645,1476,0,0,0.9473684210526315,0,0,13.666666666666666,13.666666666666666,1,0.0,108,0.5837837837837838,77,0,0,0.04942233632862644,0,2150,3711,0.996790757381258,2152 matmul,4x48x12xf64,baseline,16487,18666,18663,0.0,0,2304,2354,0,0.14277915933765997,0.33580599144079887,7010,0,0,0.4251834778916722,0,0,1.0,1.0,1,3.7142857142857144,7010,0.4271525196514533,9401,26,7,0.5702068296233396,7,2180,18670,0.9953903075150118,2182 -matmul,4x48x12xf64,linalg_xdsl,2494,4671,4668,0.0,0,2304,2402,0,0.9631114675220529,0.9991680532445923,2404,0,0,0.9639133921411387,0,0,15.024999999999999,15.025,1,0.0,160,0.642570281124498,89,0,0,0.035685645549318364,0,2178,4675,0.9995990376904571,2180 +matmul,4x48x12xf64,linalg_xdsl,2485,4685,4682,0.0,0,2304,2402,0,0.9665995975855131,0.9991680532445923,2404,0,0,0.9674044265593561,0,0,15.41025641025641,15.41025641025641,1,0.0,156,0.6695278969957081,77,0,0,0.030985915492957747,0,2201,4689,0.9983903420523138,2203 matmul,4x48x16xf64,baseline,22054,24261,24258,0.0,0,3072,3138,0,0.14228711344880748,0.33575861331050716,9346,0,0,0.423777999455881,0,0,1.0,1.0,1,3.3,9346,0.42574708454810495,12606,33,10,0.5715969892083069,10,2208,24265,0.9953749886641879,2210 matmul,4x48x16xf64,linalg_xdsl,3302,5511,5508,0.0,0,3072,3202,0,0.9697153240460327,0.9993757802746567,3204,0,0,0.970321017565112,0,0,15.11320754716981,15.11320754716981,1,0.0,212,0.6773162939297125,101,0,0,0.030587522713506964,0,2210,5515,1.000908540278619,2212 matmul,4x48x20xf64,baseline,27675,29926,29923,0.0,0,3840,3925,0,0.14182475158084915,0.33590072742832694,11685,0,0,0.4222222222222222,0,0,1.0,1.0,1,0.0,11685,0.4229251873031959,15944,0,0,0.5761156278229449,0,2252,29930,0.9983378500451672,2254 -matmul,4x48x20xf64,linalg_xdsl,4110,6344,6341,0.0,0,3840,4002,0,0.9737226277372263,0.9995004995004995,4004,0,0,0.9742092457420924,0,0,15.166666666666666,15.166666666666666,1,0.0,264,0.7002652519893899,113,0,0,0.027493917274939172,0,2235,6348,1.0017031630170317,2237 +matmul,4x48x20xf64,linalg_xdsl,4101,6355,6352,0.0,0,3840,4002,0,0.9758595464520848,0.9995004995004995,4004,0,0,0.9763472323823458,0,0,15.4,15.4,1,0.0,260,0.7202216066481995,101,0,0,0.024628139478176055,0,2255,6359,1.0009753718605219,2257 matmul,4x48x24xf64,baseline,33195,35489,35486,0.0,0,4608,4709,0,0.14185871366169603,0.3358533628129235,14021,0,0,0.4223828889893056,0,0,1.0,1.0,1,0.0,14021,0.42296901867326314,19128,0,0,0.5762313601446001,0,2295,35493,0.9986142491339056,2297 -matmul,4x48x24xf64,linalg_xdsl,4918,7180,7177,0.0,0,4608,4802,0,0.9764131760878406,0.9995836802664446,4804,0,0,0.9768198454656364,0,0,15.202531645569621,15.20253164556962,1,0.0,316,0.7165532879818595,125,0,0,0.02541683611224075,0,2263,7184,1.0022366815778772,2265 +matmul,4x48x24xf64,linalg_xdsl,4901,7186,7183,0.0,0,4608,4802,0,0.9798000408079983,0.9995836802664446,4804,0,0,0.9802081207916752,0,0,15.5974025974026,15.597402597402597,1,0.0,308,0.7530562347188264,101,0,0,0.020608039175678432,0,2286,7190,1.0008161599673535,2288 matmul,4x48x28xf64,baseline,38709,41018,41015,0.0,0,5376,5493,0,0.1419049833372084,0.3358195268080944,16357,0,0,0.42256322818982667,0,0,1.0,1.0,1,0.0,16357,0.4230003361866094,22312,0,0,0.5764034203931903,0,2310,41022,0.9989666485830169,2312 -matmul,4x48x28xf64,linalg_xdsl,5726,7994,7991,0.0,0,5376,5602,0,0.9783443939923158,0.9996431120628123,5604,0,0,0.9786936779601816,0,0,15.228260869565217,15.228260869565217,1,0.0,368,0.7287128712871287,137,0,0,0.023925951798812434,0,2269,7998,1.002619629758994,2271 +matmul,4x48x28xf64,linalg_xdsl,5700,7988,7985,0.0,0,5376,5602,0,0.9828070175438597,0.9996431120628123,5604,0,0,0.9831578947368421,0,0,15.741573033707866,15.741573033707866,1,0.0,356,0.7789934354485777,101,0,0,0.017719298245614034,0,2289,7992,1.0008771929824563,2291 matmul,4x48x32xf64,baseline,44229,46568,46565,0.0,0,6144,6277,0,0.14192045942707274,0.3357941475418606,18693,0,0,0.422641253476226,0,0,1.0,1.0,1,0.0,18693,0.4230238294598203,25496,0,0,0.576454362522327,0,2340,46572,0.9990956159985529,2342 matmul,4x48x32xf64,linalg_xdsl,6533,8832,8829,0.0,0,6144,6402,0,0.9799479565283943,0.9996876951905059,6404,0,0,0.9802540945966631,0,0,15.247619047619047,15.247619047619047,1,0.0,420,0.7381370826010545,149,0,0,0.022807286086024798,0,2300,8836,1.003061380682688,2302 matmul,4x48x36xf64,baseline,49755,52129,52126,0.0,0,6912,7061,0,0.14191538538840318,0.33577440677160114,21029,0,0,0.4226509898502663,0,0,1.0,1.0,1,0.0,21029,0.42304210505139916,28680,0,0,0.5764244799517636,0,2375,52133,0.9990754698020299,2377 -matmul,4x48x36xf64,linalg_xdsl,7342,9684,9681,0.0,0,6912,7202,0,0.9809316262598747,0.9997223764575236,7204,0,0,0.9812040315990194,0,0,15.26271186440678,15.26271186440678,1,0.0,472,0.7456556082148499,161,0,0,0.021928629801144104,0,2343,9688,1.0031326614001634,2345 +matmul,4x48x36xf64,linalg_xdsl,7317,9682,9679,0.0,0,6912,7202,0,0.984283176165095,0.9997223764575236,7204,0,0,0.984556512231789,0,0,15.660869565217391,15.660869565217391,1,0.0,460,0.7863247863247863,125,0,0,0.017083504168375018,0,2366,9686,1.001640016400164,2368 matmul,4x48x40xf64,baseline,55275,57661,57658,0.0,0,7680,7845,0,0.14192672998643147,0.33575861331050716,23365,0,0,0.42270465852555406,0,0,1.0,1.0,1,0.0,23365,0.4230567274439153,31864,0,0,0.5764631388511986,0,2387,57665,0.9991677973767527,2389 -matmul,4x48x40xf64,linalg_xdsl,8150,10519,10516,0.0,0,7680,8002,0,0.981840490797546,0.9997501249375312,8004,0,0,0.9820858895705521,0,0,15.274809160305344,15.274809160305344,1,0.0,524,0.7517934002869441,173,0,0,0.021226993865030675,0,2370,10523,1.0033128834355827,2372 +matmul,4x48x40xf64,linalg_xdsl,8133,10522,10519,0.0,0,7680,8002,0,0.9838927824910857,0.9997501249375312,8004,0,0,0.9841386942087791,0,0,15.511627906976743,15.511627906976743,1,0.0,516,0.7759398496240602,149,0,0,0.01832042296815443,0,2390,10526,1.0024591171769335,2392 matmul,4x48x44xf64,baseline,60795,63224,63221,0.0,0,8448,8629,0,0.14193601447487458,0.3357456908291506,25701,0,0,0.42274858129780407,0,0,1.0,1.0,1,0.0,25701,0.4230686924887653,35048,0,0,0.5764947775310469,0,2430,63228,0.999243358828851,2432 matmul,4x48x44xf64,linalg_xdsl,8958,11355,11352,0.0,0,8448,8802,0,0.9825853985264568,0.9997728305315765,8804,0,0,0.9828086626479124,0,0,15.284722222222223,15.284722222222221,1,0.0,576,0.7568988173455979,185,0,0,0.020651931234650592,0,2398,11359,1.0034605938825631,2400 matmul,4x48x48xf64,baseline,66309,68758,68755,0.0,0,9216,9413,0,0.1419565971436758,0.3357349217105967,28037,0,0,0.42282344779743325,0,0,1.0,1.0,1,0.0,28037,0.42307866423214474,38232,0,0,0.5765733158394788,0,2450,68762,0.9993967636369121,2452 -matmul,4x48x48xf64,linalg_xdsl,9765,12174,12171,0.0,0,9216,9602,0,0.9833077316948284,0.9997917534360683,9604,0,0,0.9835125448028674,0,0,15.29299363057325,15.292993630573248,1,0.0,628,0.7612121212121212,197,0,0,0.020174091141833078,0,2410,12178,1.0036866359447005,2412 +matmul,4x48x48xf64,linalg_xdsl,9739,12196,12193,0.0,0,9216,9602,0,0.9859328473149194,0.9997917534360683,9604,0,0,0.9861382072081323,0,0,15.69281045751634,15.69281045751634,1,0.0,612,0.8042049934296978,149,0,0,0.015299312044357737,0,2458,12200,1.00143751925249,2460 matmul,4x48x4xf64,baseline,5539,7666,7663,0.0,0,768,785,0,0.14172233255100197,0.33590072742832694,2337,0,0,0.4219173135945116,0,0,1.0,1.0,1,0.0,2337,0.42747393451618804,3130,0,0,0.5650839501715111,0,2128,7670,0.9870012637660228,2130 matmul,4x48x4xf64,linalg_xdsl,864,2971,2968,0.0,0,768,802,0,0.9282407407407407,0.9975124378109452,804,0,0,0.9305555555555556,0,0,14.357142857142858,14.357142857142858,1,0.0,56,0.5185185185185185,52,0,0,0.06018518518518518,0,2108,2975,0.9907407407407408,2110 matmul,4x48x52xf64,baseline,71835,74306,74303,0.0,0,9984,10197,0,0.14195030277719775,0.33572580910677247,30373,0,0,0.42281617595879445,0,0,1.0,1.0,1,0.0,30373,0.4230871024808815,41416,0,0,0.5765434676689636,0,2472,74310,0.9993596436277581,2474 matmul,4x48x52xf64,linalg_xdsl,10574,13028,13025,0.0,0,9984,10402,0,0.9837336864006052,0.9998077662437524,10404,0,0,0.9839228295819936,0,0,15.299999999999999,15.3,1,0.0,680,0.7649043869516311,209,0,0,0.019765462455078493,0,2455,13032,1.0036882920370722,2457 matmul,4x48x56xf64,baseline,77355,79864,79861,0.0,0,10752,10981,0,0.14195591752310774,0.3357179981044972,32709,0,0,0.4228427380259841,0,0,1.0,1.0,1,0.0,32709,0.4230943357177043,44600,0,0,0.5765626009954108,0,2510,79868,0.9994053390213948,2512 -matmul,4x48x56xf64,linalg_xdsl,11382,13859,13856,0.0,0,10752,11202,0,0.9841855561412757,0.99982149232417,11204,0,0,0.9843612721841504,0,0,15.306010928961749,15.306010928961749,1,0.0,732,0.7681007345225603,221,0,0,0.019416622737655948,0,2478,13863,1.0037778949218064,2480 +matmul,4x48x56xf64,linalg_xdsl,11339,13820,13817,0.0,0,10752,11202,0,0.9879178058029808,0.99982149232417,11204,0,0,0.9880941882000176,0,0,15.824858757062147,15.824858757062147,1,0.0,708,0.8261376896149358,149,0,0,0.013140488579239792,0,2482,13824,1.0012346767792575,2484 matmul,4x48x60xf64,baseline,82869,85393,85390,0.0,0,11520,11765,0,0.14197106276170823,0.3357112284206021,35045,0,0,0.42289637862168,0,0,1.0,1.0,1,0.0,35045,0.42310060486061646,47784,0,0,0.5766209318321689,0,2525,85397,0.9995173104538488,2527 -matmul,4x48x60xf64,linalg_xdsl,12190,14673,14670,0.0,0,11520,12002,0,0.984577522559475,0.9998333888703765,12004,0,0,0.9847415914684168,0,0,15.311224489795919,15.311224489795919,1,0.0,784,0.7708947885939036,233,0,0,0.01911402789171452,0,2484,14677,1.0038556193601313,2486 +matmul,4x48x60xf64,linalg_xdsl,12155,14688,14685,0.0,0,11520,12002,0,0.9874125874125874,0.9998333888703765,12004,0,0,0.9875771287535994,0,0,15.712041884816754,15.712041884816754,1,0.0,764,0.8153681963713981,173,0,0,0.01423282599753188,0,2534,14692,1.0018099547511312,2536 matmul,4x48x64xf64,baseline,88389,90943,90940,0.0,0,12288,12549,0,0.14197468010725317,0.33570530483400657,37381,0,0,0.42291461607213565,0,0,1.0,1.0,1,0.0,37381,0.4231060906178904,50968,0,0,0.5766328389279209,0,2555,90947,0.9995474550000566,2557 matmul,4x48x64xf64,linalg_xdsl,12997,15511,15508,0.0,0,12288,12802,0,0.9849965376625375,0.999843798812871,12804,0,0,0.9851504193275371,0,0,15.31578947368421,15.31578947368421,1,0.0,836,0.7733580018501388,245,0,0,0.018850503962452875,0,2515,15515,1.00400092328999,2517 matmul,4x48x8xf64,baseline,11043,13195,13192,0.0,0,1536,1570,0,0.1421715113646654,0.33590072742832694,4674,0,0,0.4232545503939147,0,0,1.0,1.0,1,3.0,4674,0.42552804078659867,6310,6,2,0.5714026985420628,2,2153,13199,0.9946572489359775,2155 matmul,4x48x8xf64,linalg_xdsl,1686,3840,3837,0.0,0,1536,1602,0,0.9501779359430605,0.9987531172069826,1604,0,0,0.9513641755634639,0,0,14.851851851851853,14.851851851851851,1,0.0,108,0.5837837837837838,77,0,0,0.045670225385527875,0,2155,3844,0.9970344009489918,2157 matmul,4x4x12xf64,baseline,1231,3319,3316,0.0,0,144,193,0,0.15678310316815597,0.3088,625,0,0,0.5077173030056864,0,0,1.0,1.0,1,0.0,625,0.7485029940119761,210,0,0,0.17059301380991065,0,2089,3323,0.6783103168155971,2091 -matmul,4x4x12xf64,linalg_xdsl,388,2476,2473,0.0,0,192,290,0,0.7474226804123711,0.9931506849315068,292,0,0,0.7525773195876289,0,0,1.825,1.825,1,0.0,160,0.6477732793522267,87,0,0,0.22422680412371135,0,2089,2480,0.9768041237113402,2091 +matmul,4x4x12xf64,linalg_xdsl,371,2471,2468,0.0,0,192,290,0,0.7816711590296496,0.9931506849315068,292,0,0,0.7870619946091644,0,0,1.8717948717948718,1.8717948717948718,1,0.0,156,0.6753246753246753,75,0,0,0.20215633423180593,0,2101,2475,0.9892183288409703,2103 matmul,4x4x16xf64,baseline,1631,3724,3721,0.0,0,192,257,0,0.15757204169221337,0.3085234093637455,833,0,0,0.5107296137339056,0,0,1.0,1.0,1,0.0,833,0.7524841915085817,274,0,0,0.16799509503372165,0,2094,3728,0.6787247087676272,2096 matmul,4x4x16xf64,linalg_xdsl,492,2585,2582,0.0,0,256,386,0,0.7845528455284553,0.9948453608247423,388,0,0,0.7886178861788617,0,0,1.8301886792452828,1.830188679245283,1,0.0,212,0.6816720257234726,99,0,0,0.20121951219512196,0,2094,2589,0.9898373983739837,2096 matmul,4x4x20xf64,baseline,2031,4129,4126,0.0,0,240,321,0,0.15805022156573117,0.30835734870317005,1041,0,0,0.5125553914327917,0,0,1.0,1.0,1,0.0,1041,0.7548948513415519,338,0,0,0.16642048252092564,0,2099,4133,0.6789758739537174,2101 -matmul,4x4x20xf64,linalg_xdsl,596,2694,2691,0.0,0,320,482,0,0.8087248322147651,0.9958677685950413,484,0,0,0.8120805369127517,0,0,1.8333333333333333,1.8333333333333333,1,0.0,264,0.704,111,0,0,0.18624161073825504,0,2099,2698,0.9983221476510068,2101 +matmul,4x4x20xf64,linalg_xdsl,580,2654,2651,0.0,0,320,482,0,0.8310344827586207,0.9958677685950413,484,0,0,0.8344827586206897,0,0,1.8615384615384616,1.8615384615384616,1,0.0,260,0.724233983286908,99,0,0,0.1706896551724138,0,2075,2658,1.0051724137931035,2077 matmul,4x4x24xf64,baseline,2431,4534,4531,0.0,0,288,385,0,0.1583710407239819,0.3082465972778223,1249,0,0,0.513780337309749,0,0,1.0,1.0,1,0.0,1249,0.756511205330103,402,0,0,0.1653640477169889,0,2104,4538,0.6791443850267379,2106 -matmul,4x4x24xf64,linalg_xdsl,700,2803,2800,0.0,0,384,578,0,0.8257142857142857,0.996551724137931,580,0,0,0.8285714285714286,0,0,1.8354430379746836,1.8354430379746836,1,0.0,316,0.7198177676537585,123,0,0,0.1757142857142857,0,2104,2807,1.0042857142857144,2106 +matmul,4x4x24xf64,linalg_xdsl,675,2790,2787,0.0,0,384,578,0,0.8562962962962963,0.996551724137931,580,0,0,0.8592592592592593,0,0,1.8831168831168832,1.8831168831168832,1,0.0,308,0.7567567567567568,99,0,0,0.14666666666666667,0,2116,2794,1.005925925925926,2118 matmul,4x4x28xf64,baseline,2831,4934,4931,0.0,0,336,449,0,0.1586012009890498,0.3081674673987646,1457,0,0,0.5146591310490992,0,0,1.0,1.0,1,0.0,1457,0.7576703068122725,466,0,0,0.16460614623807843,0,2104,4938,0.6792652772871777,2106 -matmul,4x4x28xf64,linalg_xdsl,804,2907,2904,0.0,0,448,674,0,0.8383084577114428,0.9970414201183432,676,0,0,0.8407960199004975,0,0,1.8369565217391306,1.8369565217391304,1,0.0,368,0.731610337972167,135,0,0,0.16791044776119404,0,2104,2911,1.0087064676616915,2106 +matmul,4x4x28xf64,linalg_xdsl,777,2902,2899,0.0,0,448,674,0,0.8674388674388674,0.9970414201183432,676,0,0,0.87001287001287,0,0,1.8988764044943822,1.898876404494382,1,0.0,356,0.7824175824175824,99,0,0,0.1274131274131274,0,2126,2906,0.9974259974259974,2128 matmul,4x4x32xf64,baseline,3231,5339,5336,0.0,0,384,513,0,0.15877437325905291,0.3081081081081081,1665,0,0,0.5153203342618384,0,0,1.0,1.0,1,0.0,1665,0.7585421412300684,530,0,0,0.16403590219746209,0,2109,5343,0.6793562364593005,2111 matmul,4x4x32xf64,linalg_xdsl,908,3016,3013,0.0,0,512,770,0,0.8480176211453745,0.9974093264248705,772,0,0,0.8502202643171806,0,0,1.838095238095238,1.838095238095238,1,0.0,420,0.7407407407407407,147,0,0,0.1618942731277533,0,2109,3020,1.0121145374449338,2111 matmul,4x4x36xf64,baseline,3631,5744,5741,0.0,0,432,577,0,0.15890939135224455,0.30806193272824345,1873,0,0,0.5158358578903883,0,0,1.0,1.0,1,0.0,1873,0.7592217267936765,594,0,0,0.16359129716331589,0,2114,5748,0.6794271550537042,2116 -matmul,4x4x36xf64,linalg_xdsl,1012,3125,3122,0.0,0,576,866,0,0.8557312252964426,0.9976958525345622,868,0,0,0.857707509881423,0,0,1.8389830508474576,1.8389830508474576,1,0.0,472,0.7480190174326465,159,0,0,0.15711462450592886,0,2114,3129,1.0148221343873518,2116 +matmul,4x4x36xf64,linalg_xdsl,979,3104,3101,0.0,0,576,866,0,0.8845760980592441,0.9976958525345622,868,0,0,0.8866189989785496,0,0,1.8869565217391306,1.8869565217391304,1,0.0,460,0.7890222984562607,123,0,0,0.12563840653728295,0,2126,3108,1.0122574055158324,2128 matmul,4x4x40xf64,baseline,4031,6149,6146,0.0,0,480,641,0,0.15901761349541058,0.30802498798654493,2081,0,0,0.5162490697097495,0,0,1.0,1.0,1,0.0,2081,0.759766338079591,658,0,0,0.16323492929794095,0,2119,6153,0.6794839990076904,2121 -matmul,4x4x40xf64,linalg_xdsl,1116,3234,3231,0.0,0,640,962,0,0.8620071684587813,0.9979253112033195,964,0,0,0.8637992831541219,0,0,1.8396946564885495,1.8396946564885497,1,0.0,524,0.753956834532374,171,0,0,0.1532258064516129,0,2119,3238,1.017025089605735,2121 +matmul,4x4x40xf64,linalg_xdsl,1092,3186,3183,0.0,0,640,962,0,0.8809523809523809,0.9979253112033195,964,0,0,0.8827838827838828,0,0,1.8682170542635659,1.8682170542635659,1,0.0,516,0.7782805429864253,147,0,0,0.1346153846153846,0,2095,3190,1.0173992673992673,2097 matmul,4x4x44xf64,baseline,4431,6554,6551,0.0,0,528,705,0,0.15910629654705485,0.30799475753604194,2289,0,0,0.5165876777251185,0,0,1.0,1.0,1,0.0,2289,0.7602125539687812,722,0,0,0.16294290227939517,0,2124,6558,0.6795305800045137,2126 matmul,4x4x44xf64,linalg_xdsl,1220,3343,3340,0.0,0,704,1058,0,0.8672131147540983,0.9981132075471698,1060,0,0,0.8688524590163934,0,0,1.840277777777778,1.8402777777777777,1,0.0,576,0.758893280632411,183,0,0,0.15,0,2124,3347,1.0188524590163934,2126 matmul,4x4x48xf64,baseline,4831,6959,6956,0.0,0,576,769,0,0.1591802939350031,0.3079695634761714,2497,0,0,0.5168702132063755,0,0,1.0,1.0,1,0.0,2497,0.7605848309473043,786,0,0,0.1626992341130201,0,2129,6963,0.6795694473193956,2131 -matmul,4x4x48xf64,linalg_xdsl,1324,3452,3449,0.0,0,768,1154,0,0.8716012084592145,0.9982698961937716,1156,0,0,0.8731117824773413,0,0,1.8407643312101911,1.8407643312101911,1,0.0,628,0.7630619684082625,195,0,0,0.1472809667673716,0,2129,3456,1.020392749244713,2131 +matmul,4x4x48xf64,linalg_xdsl,1283,3423,3420,0.0,0,768,1154,0,0.8994544037412315,0.9982698961937716,1156,0,0,0.9010132501948558,0,0,1.8888888888888888,1.8888888888888888,1,0.0,612,0.8063241106719368,147,0,0,0.11457521434138737,0,2141,3427,1.0155884645362432,2143 matmul,4x4x4xf64,baseline,419,2461,2458,0.0,0,48,65,0,0.15513126491646778,0.31100478468899523,209,0,0,0.4988066825775656,0,0,1.0,1.0,1,0.0,209,0.9720930232558139,6,0,0,0.014319809069212411,0,2043,2465,0.513126491646778,2045 matmul,4x4x4xf64,linalg_xdsl,162,2260,2257,0.0,0,64,98,0,0.6049382716049383,0.98,100,0,0,0.6172839506172839,0,0,1.7857142857142858,1.7857142857142858,1,0.0,56,0.5233644859813084,51,0,0,0.3148148148148148,0,2099,2264,0.9320987654320987,2101 matmul,4x4x52xf64,baseline,5231,7364,7361,0.0,0,624,833,0,0.1592429745746511,0.3079482439926063,2705,0,0,0.5171095392850316,0,0,1.0,1.0,1,0.0,2705,0.7609001406469761,850,0,0,0.1624928311986236,0,2134,7368,0.6796023704836551,2136 matmul,4x4x52xf64,linalg_xdsl,1428,3561,3558,0.0,0,832,1250,0,0.8753501400560224,0.9984025559105432,1252,0,0,0.876750700280112,0,0,1.8411764705882352,1.8411764705882352,1,0.0,680,0.7666290868094702,207,0,0,0.14495798319327732,0,2134,3565,1.0217086834733893,2136 matmul,4x4x56xf64,baseline,5631,7764,7761,0.0,0,672,897,0,0.15929675013319125,0.3079299691040165,2913,0,0,0.5173148641449121,0,0,1.0,1.0,1,0.0,2913,0.7611706297360857,914,0,0,0.16231575208666313,0,2134,7768,0.6796306162315753,2136 -matmul,4x4x56xf64,linalg_xdsl,1532,3665,3662,0.0,0,896,1346,0,0.8785900783289817,0.9985163204747775,1348,0,0,0.8798955613577023,0,0,1.8415300546448086,1.8415300546448088,1,0.0,732,0.7697160883280757,219,0,0,0.1429503916449086,0,2134,3669,1.0228459530026108,2136 +matmul,4x4x56xf64,linalg_xdsl,1481,3636,3633,0.0,0,896,1346,0,0.9088453747467927,0.9985163204747775,1348,0,0,0.9101958136394328,0,0,1.903954802259887,1.9039548022598871,1,0.0,708,0.8280701754385965,147,0,0,0.09925725860904794,0,2156,3640,1.0094530722484807,2158 matmul,4x4x60xf64,baseline,6031,8185,8182,0.0,0,720,961,0,0.15934339247222684,0.30791413008651075,3121,0,0,0.5174929530757751,0,0,1.0,1.0,1,0.0,3121,0.7614052207855575,978,0,0,0.16216216216216217,0,2155,8189,0.6796551152379373,2157 -matmul,4x4x60xf64,linalg_xdsl,1636,3790,3787,0.0,0,960,1442,0,0.8814180929095354,0.9986149584487535,1444,0,0,0.882640586797066,0,0,1.8418367346938775,1.8418367346938775,1,0.0,784,0.7724137931034483,231,0,0,0.14119804400977995,0,2155,3794,1.023838630806846,2157 +matmul,4x4x60xf64,linalg_xdsl,1587,3713,3710,0.0,0,960,1442,0,0.9086326402016384,0.9986149584487535,1444,0,0,0.909892879647133,0,0,1.8900523560209426,1.8900523560209423,1,0.0,764,0.8171122994652407,171,0,0,0.10775047258979206,0,2127,3717,1.017643352236925,2129 matmul,4x4x64xf64,baseline,6431,8590,8587,0.0,0,768,1025,0,0.15938423262323123,0.3079002703514569,3329,0,0,0.517648888197792,0,0,1.0,1.0,1,0.0,3329,0.7616106154198125,1042,0,0,0.16202767843259214,0,2160,8594,0.6796765666303841,2162 matmul,4x4x64xf64,linalg_xdsl,1740,3899,3896,0.0,0,1024,1538,0,0.8839080459770114,0.9987012987012988,1540,0,0,0.8850574712643678,0,0,1.8421052631578947,1.8421052631578947,1,0.0,836,0.7747914735866543,243,0,0,0.1396551724137931,0,2160,3903,1.024712643678161,2162 matmul,4x4x8xf64,baseline,831,2919,2916,0.0,0,96,129,0,0.1552346570397112,0.30935251798561153,417,0,0,0.5018050541516246,0,0,1.0,1.0,1,0.0,417,0.9413092550790068,26,0,0,0.031287605294825514,0,2089,2923,0.5330926594464501,2091 matmul,4x4x8xf64,linalg_xdsl,284,2372,2369,0.0,0,128,194,0,0.6830985915492958,0.9897959183673469,196,0,0,0.6901408450704225,0,0,1.8148148148148149,1.8148148148148149,1,0.0,108,0.5901639344262295,75,0,0,0.2640845070422535,0,2089,2376,0.954225352112676,2091 matmul,4x52x12xf64,baseline,17831,20020,20017,0.0,0,2496,2546,0,0.1427850372945993,0.33561824413393093,7586,0,0,0.4254388424653693,0,0,1.0,1.0,1,3.7142857142857144,7586,0.4272599267811884,10169,26,7,0.570298917615389,7,2190,20024,0.9957377600807582,2192 -matmul,4x52x12xf64,linalg_xdsl,2686,4873,4870,0.0,0,2496,2594,0,0.9657483246463142,0.9992295839753467,2596,0,0,0.9664929262844378,0,0,16.224999999999998,16.225,1,0.0,160,0.642570281124498,89,0,0,0.033134772896500374,0,2188,4877,0.9996276991809382,2190 +matmul,4x52x12xf64,linalg_xdsl,2677,4887,4884,0.0,0,2496,2594,0,0.9689951438177064,0.9992295839753467,2596,0,0,0.9697422487859544,0,0,16.641025641025642,16.641025641025642,1,0.0,156,0.6695278969957081,77,0,0,0.028763541277549497,0,2211,4891,0.9985057900635039,2213 matmul,4x52x16xf64,baseline,23846,26063,26060,0.0,0,3328,3394,0,0.14232995051580977,0.3355744512556852,10114,0,0,0.4241382202465822,0,0,1.0,1.0,1,3.3,10114,0.42596024258760107,13630,33,10,0.5715843328021472,10,2218,26067,0.9957225530487294,2220 matmul,4x52x16xf64,linalg_xdsl,3558,5777,5774,0.0,0,3328,3458,0,0.971894322653176,0.999421965317919,3460,0,0,0.9724564362001125,0,0,16.32075471698113,16.32075471698113,1,0.0,212,0.6773162939297125,101,0,0,0.0283867341202923,0,2220,5781,1.0008431703204048,2222 matmul,4x52x20xf64,baseline,29915,32181,32178,0.0,0,4160,4245,0,0.14190205582483703,0.33570581257413995,12645,0,0,0.4226976433227478,0,0,1.0,1.0,1,0.0,12645,0.4233486223174529,17224,0,0,0.5757646665552398,0,2267,32185,0.9984623098779877,2269 -matmul,4x52x20xf64,linalg_xdsl,4430,6679,6676,0.0,0,4160,4322,0,0.9756207674943567,0.9995374653098983,4324,0,0,0.9760722347629797,0,0,16.37878787878788,16.37878787878788,1,0.0,264,0.7002652519893899,113,0,0,0.025507900677200903,0,2250,6683,1.0015801354401805,2252 +matmul,4x52x20xf64,linalg_xdsl,4421,6690,6687,0.0,0,4160,4322,0,0.9776068762723366,0.9995374653098983,4324,0,0,0.9780592626102692,0,0,16.63076923076923,16.630769230769232,1,0.0,260,0.7202216066481995,101,0,0,0.022845510065596018,0,2270,6694,1.0009047726758653,2272 matmul,4x52x24xf64,baseline,35883,38192,38189,0.0,0,4992,5093,0,0.14193350611710281,0.3356620312397021,15173,0,0,0.42284647326031827,0,0,1.0,1.0,1,0.0,15173,0.4233892345899489,20664,0,0,0.5758715826435917,0,2310,38196,0.9987180559039099,2312 -matmul,4x52x24xf64,linalg_xdsl,5302,7579,7576,0.0,0,4992,5186,0,0.978121463598642,0.9996144949884348,5188,0,0,0.978498679743493,0,0,16.417721518987342,16.417721518987342,1,0.0,316,0.7165532879818595,125,0,0,0.023576009053187477,0,2278,7583,1.0020746887966805,2280 +matmul,4x52x24xf64,linalg_xdsl,5285,7585,7582,0.0,0,4992,5186,0,0.981267738883633,0.9996144949884348,5188,0,0,0.9816461684011353,0,0,16.844155844155843,16.844155844155843,1,0.0,308,0.7530562347188264,101,0,0,0.019110690633869443,0,2301,7589,1.0007568590350047,2303 matmul,4x52x28xf64,baseline,41851,44172,44169,0.0,0,5824,5941,0,0.14195598671477383,0.33563075532455794,17701,0,0,0.4229528565625672,0,0,1.0,1.0,1,0.0,17701,0.4234182514053343,24104,0,0,0.5759480060213615,0,2322,44176,0.9989008625839287,2324 -matmul,4x52x28xf64,linalg_xdsl,6174,8478,8475,0.0,0,5824,6050,0,0.9799157758341431,0.9996695307336417,6052,0,0,0.9802397149335925,0,0,16.445652173913043,16.445652173913043,1,0.0,368,0.7287128712871287,137,0,0,0.022189828312277293,0,2305,8482,1.0024295432458699,2307 +matmul,4x52x28xf64,linalg_xdsl,6148,8459,8456,0.0,0,5824,6050,0,0.9840598568640209,0.9996695307336417,6052,0,0,0.9843851659076123,0,0,17.0,17.0,1,0.0,356,0.7789934354485777,101,0,0,0.016428106701366296,0,2312,8463,1.0008132726089785,2314 matmul,4x52x32xf64,baseline,47819,50183,50180,0.0,0,6656,6789,0,0.14197285597774942,0.33560729645558357,20229,0,0,0.4230326857525252,0,0,1.0,1.0,1,0.0,20229,0.4234400184204467,27544,0,0,0.5760053535205671,0,2365,50187,0.9990380392730923,2367 matmul,4x52x32xf64,linalg_xdsl,7046,9378,9375,0.0,0,6656,6914,0,0.9812659665058189,0.9997108155002892,6916,0,0,0.981549815498155,0,0,16.46666666666667,16.466666666666665,1,0.0,420,0.7381370826010545,149,0,0,0.021146749929037752,0,2333,9382,1.0026965654271927,2335 matmul,4x52x36xf64,baseline,53787,56168,56165,0.0,0,7488,7637,0,0.1419859817428003,0.3355890495232236,22757,0,0,0.4230947998587019,0,0,1.0,1.0,1,0.0,22757,0.42345695093131874,30984,0,0,0.5760499749009984,0,2382,56172,0.9991447747597003,2384 -matmul,4x52x36xf64,linalg_xdsl,7918,10282,10279,0.0,0,7488,7778,0,0.9823187673654964,0.9997429305912596,7780,0,0,0.9825713564031321,0,0,16.48305084745763,16.483050847457626,1,0.0,472,0.7456556082148499,161,0,0,0.020333417529679213,0,2365,10286,1.0029047739328114,2367 +matmul,4x52x36xf64,linalg_xdsl,7893,10295,10292,0.0,0,7488,7778,0,0.9854301279614849,0.9997429305912596,7780,0,0,0.9856835170404156,0,0,16.91304347826087,16.91304347826087,1,0.0,460,0.7863247863247863,125,0,0,0.01583681743316863,0,2403,10299,1.0015203344735841,2405 matmul,4x52x40xf64,baseline,59755,62166,62163,0.0,0,8320,8485,0,0.14199648564973644,0.3355744512556852,25285,0,0,0.423144506735838,0,0,1.0,1.0,1,0.0,25285,0.42347049858480296,34424,0,0,0.5760856832064263,0,2412,62170,0.9992301899422642,2414 -matmul,4x52x40xf64,linalg_xdsl,8790,11184,11181,0.0,0,8320,8642,0,0.9831626848691695,0.9997686256362796,8644,0,0,0.9833902161547212,0,0,16.49618320610687,16.49618320610687,1,0.0,524,0.7517934002869441,173,0,0,0.019681456200227532,0,2395,11188,1.0030716723549487,2397 +matmul,4x52x40xf64,linalg_xdsl,8773,11187,11184,0.0,0,8320,8642,0,0.9850678217257495,0.9997686256362796,8644,0,0,0.9852957939131426,0,0,16.751937984496124,16.751937984496124,1,0.0,516,0.7759398496240602,149,0,0,0.016983927960788785,0,2415,11191,1.0022797218739314,2417 matmul,4x52x44xf64,baseline,65723,68177,68174,0.0,0,9152,9333,0,0.14200508193478692,0.3355625067414518,27813,0,0,0.4231851863122499,0,0,1.0,1.0,1,0.0,27813,0.42348158411620507,37864,0,0,0.5761149065015292,0,2455,68181,0.9993000928137791,2457 matmul,4x52x44xf64,linalg_xdsl,9662,12084,12081,0.0,0,9152,9506,0,0.9838542744773339,0.9997896508203618,9508,0,0,0.9840612709583937,0,0,16.506944444444443,16.506944444444443,1,0.0,576,0.7568988173455979,185,0,0,0.019147174498033534,0,2423,12088,1.0032084454564272,2425 matmul,4x52x48xf64,baseline,71691,74162,74159,0.0,0,9984,10181,0,0.14201224700450546,0.3355525526515276,30341,0,0,0.42321909305212646,0,0,1.0,1.0,1,0.0,30341,0.4234908228068951,41304,0,0,0.5761392643428045,0,2472,74166,0.999358357394931,2474 -matmul,4x52x48xf64,linalg_xdsl,10534,12988,12985,0.0,0,9984,10370,0,0.9844313651034745,0.9998071731585036,10372,0,0,0.9846212265046516,0,0,16.51592356687898,16.515923566878982,1,0.0,628,0.7612121212121212,197,0,0,0.018701348015948357,0,2455,12992,1.0033225745205998,2457 +matmul,4x52x48xf64,linalg_xdsl,10501,12993,12990,0.0,0,9984,10370,0,0.9875249976192744,0.9998071731585036,10372,0,0,0.9877154556708885,0,0,16.947712418300654,16.947712418300654,1,0.0,612,0.8042049934296978,149,0,0,0.014189124845252834,0,2493,12997,1.0019045805161413,2495 matmul,4x52x4xf64,baseline,5987,8114,8111,0.0,0,832,849,0,0.14180724903958578,0.33570581257413995,2529,0,0,0.42241523300484385,0,0,1.0,1.0,1,0.0,2529,0.4275570583262891,3386,0,0,0.5655587105395022,0,2128,8118,0.9879739435443461,2130 matmul,4x52x4xf64,linalg_xdsl,928,3035,3032,0.0,0,832,866,0,0.9331896551724138,0.9976958525345622,868,0,0,0.9353448275862069,0,0,15.5,15.5,1,0.0,56,0.5185185185185185,52,0,0,0.05603448275862069,0,2108,3039,0.9913793103448275,2110 matmul,4x52x52xf64,baseline,77659,80160,80157,0.0,0,10816,11029,0,0.1420183108203814,0.33554412972709846,32869,0,0,0.4232477884082978,0,0,1.0,1.0,1,0.0,32869,0.42349864069163673,44744,0,0,0.5761598784429365,0,2502,80164,0.9994076668512343,2504 matmul,4x52x52xf64,linalg_xdsl,11406,13890,13887,0.0,0,10816,11234,0,0.9849202174294232,0.9998220007119971,11236,0,0,0.9850955637383834,0,0,16.523529411764706,16.523529411764706,1,0.0,680,0.7649043869516311,209,0,0,0.01832368928634052,0,2485,13894,1.003419253024724,2487 matmul,4x52x56xf64,baseline,83627,86153,86150,0.0,0,11648,11877,0,0.1420235091537422,0.3355369099076193,35397,0,0,0.4232723881043204,0,0,1.0,1.0,1,0.0,35397,0.42350534212320984,48184,0,0,0.576177550312698,0,2527,86157,0.9994499384170183,2529 -matmul,4x52x56xf64,linalg_xdsl,12278,14787,14784,0.0,0,11648,12098,0,0.9853396318618668,0.9998347107438017,12100,0,0,0.9855025248411794,0,0,16.530054644808743,16.530054644808743,1,0.0,732,0.7681007345225603,221,0,0,0.017999674214041375,0,2510,14791,1.0035021990552209,2512 +matmul,4x52x56xf64,linalg_xdsl,12228,14744,14741,0.0,0,11648,12098,0,0.9893686620870135,0.9998347107438017,12100,0,0,0.9895322211318286,0,0,17.09039548022599,17.09039548022599,1,0.0,708,0.8261376896149358,149,0,0,0.012185148838730783,0,2517,14748,1.0017173699705593,2519 matmul,4x52x60xf64,baseline,89595,92164,92161,0.0,0,12480,12725,0,0.14202801495619174,0.3355306526038233,37925,0,0,0.42329371058652826,0,0,1.0,1.0,1,0.0,37925,0.4235111503199366,51624,0,0,0.5761928679055751,0,2570,92168,0.9994865784921034,2572 -matmul,4x52x60xf64,linalg_xdsl,13150,15687,15684,0.0,0,12480,12962,0,0.9857034220532319,0.9998457266275841,12964,0,0,0.9858555133079848,0,0,16.535714285714285,16.535714285714285,1,0.0,784,0.7708947885939036,233,0,0,0.017718631178707225,0,2538,15691,1.0035741444866921,2540 +matmul,4x52x60xf64,linalg_xdsl,13109,15669,15666,0.0,0,12480,12962,0,0.9887863300022885,0.9998457266275841,12964,0,0,0.9889388969410329,0,0,16.968586387434552,16.968586387434556,1,0.0,764,0.8153681963713981,173,0,0,0.01319704020138836,0,2561,15673,1.0021359371424212,2563 matmul,4x52x64xf64,baseline,95563,98149,98146,0.0,0,13312,13573,0,0.14203195797536702,0.33552517736632637,40453,0,0,0.42331236985025583,0,0,1.0,1.0,1,0.0,40453,0.42351623271250144,55064,0,0,0.5762062723020416,0,2587,98153,0.9995186421522975,2589 matmul,4x52x64xf64,linalg_xdsl,14022,16591,16588,0.0,0,13312,13826,0,0.9860219654828127,0.9998553659242118,13828,0,0,0.9861645984880901,0,0,16.54066985645933,16.54066985645933,1,0.0,836,0.7733580018501388,245,0,0,0.017472543146484096,0,2570,16595,1.0036371416345742,2572 matmul,4x52x8xf64,baseline,11939,14096,14093,0.0,0,1664,1698,0,0.1422229667476338,0.33570581257413995,5058,0,0,0.42365357232599044,0,0,1.0,1.0,1,3.0,5058,0.4257575757575758,6822,6,2,0.5714046402546277,2,2158,14100,0.9950582125806181,2160 matmul,4x52x8xf64,linalg_xdsl,1814,3973,3970,0.0,0,1664,1730,0,0.9536934950385888,0.9988452655889145,1732,0,0,0.9547960308710033,0,0,16.037037037037038,16.037037037037038,1,0.0,108,0.5837837837837838,77,0,0,0.04244762954796031,0,2160,3977,0.9972436604189636,2162 matmul,4x56x12xf64,baseline,19175,21369,21366,0.0,0,2688,2738,0,0.14279009126466755,0.33545699583435434,8162,0,0,0.42565840938722294,0,0,1.0,1.0,1,3.7142857142857144,8162,0.4273522173935808,10937,26,7,0.5703780964797914,7,2195,21373,0.9960365058670144,2197 -matmul,4x56x12xf64,linalg_xdsl,2878,5075,5072,0.0,0,2688,2786,0,0.9680333564975677,0.9992826398852224,2788,0,0,0.9687282835302293,0,0,17.425,17.425,1,0.0,160,0.642570281124498,89,0,0,0.03092425295343989,0,2198,5079,0.9996525364836693,2200 +matmul,4x56x12xf64,linalg_xdsl,2869,5089,5086,0.0,0,2688,2786,0,0.9710700592540955,0.9992826398852224,2788,0,0,0.9717671662600209,0,0,17.871794871794872,17.871794871794872,1,0.0,156,0.6695278969957081,77,0,0,0.026838619728128267,0,2221,5093,0.9986057859881492,2223 matmul,4x56x16xf64,baseline,25638,27865,27862,0.0,0,3584,3650,0,0.14236679928231533,0.33541628377136556,10882,0,0,0.42444808487401514,0,0,1.0,1.0,1,3.3,10882,0.4261434837092732,14654,33,10,0.5715734456665886,10,2228,27869,0.9960215305406037,2230 matmul,4x56x16xf64,linalg_xdsl,3814,6043,6040,0.0,0,3584,3714,0,0.9737808075511274,0.9994617868675996,3716,0,0,0.9743051914001049,0,0,17.528301886792452,17.528301886792452,1,0.0,212,0.6773162939297125,101,0,0,0.0264813843733613,0,2230,6047,1.0007865757734662,2232 matmul,4x56x20xf64,baseline,32155,34444,34441,0.0,0,4480,4565,0,0.1419685896439123,0.33553840499816245,13605,0,0,0.42310682631006064,0,0,1.0,1.0,1,0.0,13605,0.4237129776698122,18504,0,0,0.5754626030166382,0,2290,34448,0.9985694293266989,2292 -matmul,4x56x20xf64,linalg_xdsl,4750,7007,7004,0.0,0,4480,4642,0,0.9772631578947368,0.9995693367786391,4644,0,0,0.9776842105263158,0,0,17.59090909090909,17.59090909090909,1,0.0,264,0.7002652519893899,113,0,0,0.023789473684210527,0,2258,7011,1.0014736842105263,2260 +matmul,4x56x20xf64,linalg_xdsl,4747,7023,7020,0.0,0,4480,4642,0,0.9778807668000843,0.9995693367786391,4644,0,0,0.9783020855277017,0,0,17.86153846153846,17.861538461538462,1,0.0,260,0.7202216066481995,101,0,0,0.02127659574468085,0,2277,7027,0.9995786812723826,2279 matmul,4x56x24xf64,baseline,38571,40882,40879,0.0,0,5376,5477,0,0.14199787405045242,0.33549770290964775,16325,0,0,0.4232454434678904,0,0,1.0,1.0,1,0.0,16325,0.42375081116158336,22200,0,0,0.5755619506883409,0,2312,40886,0.9988073941562313,2314 -matmul,4x56x24xf64,linalg_xdsl,5686,7980,7977,0.0,0,5376,5570,0,0.9795990151248681,0.9996410624551328,5572,0,0,0.9799507562434049,0,0,17.632911392405063,17.632911392405063,1,0.0,316,0.7165532879818595,125,0,0,0.02198381990854731,0,2295,7984,1.0019345761519522,2297 +matmul,4x56x24xf64,linalg_xdsl,5669,8001,7998,0.0,0,5376,5570,0,0.9825366025754101,0.9996410624551328,5572,0,0,0.9828893984829776,0,0,18.09090909090909,18.09090909090909,1,0.0,308,0.7530562347188264,101,0,0,0.017816193332157348,0,2333,8005,1.000705591815135,2335 matmul,4x56x28xf64,baseline,44987,47336,47333,0.0,0,6272,6389,0,0.14201880543268056,0.3354686269362037,19045,0,0,0.423344521750728,0,0,1.0,1.0,1,0.0,19045,0.42377784205958924,25896,0,0,0.5756329606330718,0,2350,47340,0.9989774823837998,2352 -matmul,4x56x28xf64,linalg_xdsl,6622,8939,8936,0.0,0,6272,6498,0,0.9812745394140743,0.9996923076923077,6500,0,0,0.9815765629719118,0,0,17.66304347826087,17.66304347826087,1,0.0,368,0.7287128712871287,137,0,0,0.020688613711869527,0,2318,8943,1.0022651766837813,2320 +matmul,4x56x28xf64,linalg_xdsl,6603,8924,8921,0.0,0,6272,6498,0,0.9840981372103589,0.9996923076923077,6500,0,0,0.9844010298349235,0,0,18.258426966292134,18.258426966292134,1,0.0,356,0.7789934354485777,101,0,0,0.015296077540511889,0,2322,8928,0.9996971073754354,2324 matmul,4x56x32xf64,baseline,51403,53774,53771,0.0,0,7168,7301,0,0.14203451160438108,0.3354468182862394,21765,0,0,0.42341886660311656,0,0,1.0,1.0,1,0.0,21765,0.4237981190490099,29592,0,0,0.5756862439935412,0,2372,53778,0.9991051105966577,2374 matmul,4x56x32xf64,linalg_xdsl,7558,9912,9909,0.0,0,7168,7426,0,0.9825350621857635,0.9997307485191168,7428,0,0,0.9827996824556761,0,0,17.685714285714287,17.685714285714287,1,0.0,420,0.7381370826010545,149,0,0,0.01971421010849431,0,2355,9916,1.0025138925641703,2357 matmul,4x56x36xf64,baseline,57819,60220,60217,0.0,0,8064,8213,0,0.14204673204310003,0.33542985501327344,24485,0,0,0.4234767118075373,0,0,1.0,1.0,1,0.0,24485,0.4238138923026327,33288,0,0,0.5757277019664816,0,2402,60224,0.9992044137740189,2404 -matmul,4x56x36xf64,linalg_xdsl,8494,10878,10875,0.0,0,8064,8354,0,0.9835177772545326,0.9997606510292005,8356,0,0,0.9837532375794679,0,0,17.703389830508478,17.703389830508474,1,0.0,472,0.7456556082148499,161,0,0,0.018954556157287496,0,2385,10882,1.0027077937367554,2387 +matmul,4x56x36xf64,linalg_xdsl,8469,10891,10888,0.0,0,8064,8354,0,0.9864210650608101,0.9997606510292005,8356,0,0,0.9866572204510567,0,0,18.16521739130435,18.16521739130435,1,0.0,460,0.7863247863247863,125,0,0,0.0147597118904239,0,2423,10895,1.0014169323414805,2425 matmul,4x56x40xf64,baseline,64235,66684,66681,0.0,0,8960,9125,0,0.1420565112477621,0.33541628377136556,27205,0,0,0.4235230014789445,0,0,1.0,1.0,1,0.0,27205,0.4238265123307732,36984,0,0,0.5757608780259983,0,2450,66688,0.9992838795049428,2452 -matmul,4x56x40xf64,linalg_xdsl,9430,11847,11844,0.0,0,8960,9282,0,0.9843054082714741,0.9997845756139595,9284,0,0,0.9845174973488865,0,0,17.717557251908396,17.717557251908396,1,0.0,524,0.7517934002869441,173,0,0,0.018345705196182397,0,2418,11851,1.002863202545069,2420 +matmul,4x56x40xf64,linalg_xdsl,9419,11855,11852,0.0,0,8960,9282,0,0.985454931521393,0.9997845756139595,9284,0,0,0.985667268287504,0,0,17.992248062015502,17.992248062015506,1,0.0,516,0.7759398496240602,149,0,0,0.015819089075273383,0,2437,11859,1.0014863573627772,2439 matmul,4x56x44xf64,baseline,70651,73117,73114,0.0,0,9856,10037,0,0.14206451430269917,0.33540517961570593,29925,0,0,0.4235608837808382,0,0,1.0,1.0,1,0.0,29925,0.4238368387507967,40680,0,0,0.5757880284780116,0,2467,73121,0.9993489122588498,2469 matmul,4x56x44xf64,linalg_xdsl,10366,12815,12812,0.0,0,9856,10210,0,0.9849508006945784,0.999804151978065,10212,0,0,0.9851437391472121,0,0,17.729166666666664,17.729166666666668,1,0.0,576,0.7568988173455979,185,0,0,0.017846806868608914,0,2450,12819,1.002990546015821,2452 matmul,4x56x48xf64,baseline,77067,79576,79573,0.0,0,10752,10949,0,0.14207118481321448,0.335395925869199,32645,0,0,0.42359245851012756,0,0,1.0,1.0,1,0.0,32645,0.42384544474883473,44376,0,0,0.5758106582583985,0,2510,79580,0.999403116768526,2512 -matmul,4x56x48xf64,linalg_xdsl,11302,13779,13776,0.0,0,10752,11138,0,0.9854892939302778,0.9998204667863555,11140,0,0,0.9856662537603964,0,0,17.73885350318471,17.738853503184714,1,0.0,628,0.7612121212121212,197,0,0,0.017430543266678464,0,2478,13783,1.0030967970270748,2480 +matmul,4x56x48xf64,linalg_xdsl,11269,13769,13766,0.0,0,10752,11138,0,0.9883751885704144,0.9998204667863555,11140,0,0,0.9885526666075073,0,0,18.202614379084967,18.202614379084967,1,0.0,612,0.8042049934296978,149,0,0,0.013222113763421776,0,2501,13773,1.0017747803709292,2503 matmul,4x56x4xf64,baseline,6435,8567,8564,0.0,0,896,913,0,0.14188034188034188,0.33553840499816245,2721,0,0,0.4228438228438228,0,0,1.0,1.0,1,0.0,2721,0.4276284771334276,3642,0,0,0.565967365967366,0,2133,8571,0.9888111888111888,2135 matmul,4x56x4xf64,linalg_xdsl,992,3104,3101,0.0,0,896,930,0,0.9375,0.9978540772532188,932,0,0,0.9395161290322581,0,0,16.642857142857142,16.642857142857142,1,0.0,56,0.5185185185185185,52,0,0,0.05241935483870968,0,2113,3108,0.9919354838709677,2115 matmul,4x56x52xf64,baseline,83483,86009,86006,0.0,0,11648,11861,0,0.14207683001329613,0.33538809557472077,35365,0,0,0.42361917995280474,0,0,1.0,1.0,1,0.0,35365,0.42385272720735406,48072,0,0,0.5758298096618473,0,2527,86013,0.999448989614652,2529 matmul,4x56x52xf64,linalg_xdsl,12238,14747,14744,0.0,0,11648,12066,0,0.9859454159176336,0.9998342724560823,12068,0,0,0.9861088413139402,0,0,17.74705882352941,17.74705882352941,1,0.0,680,0.7649043869516311,209,0,0,0.01707795391403824,0,2510,14751,1.0031867952279785,2512 matmul,4x56x56xf64,baseline,89899,92460,92457,0.0,0,12544,12773,0,0.14208166942902592,0.335381383746882,38085,0,0,0.42364208723122615,0,0,1.0,1.0,1,0.0,38085,0.423858969650429,51768,0,0,0.5758462274330082,0,2562,92464,0.9994883146642344,2564 -matmul,4x56x56xf64,linalg_xdsl,13174,15718,15715,0.0,0,12544,12994,0,0.9863367238500076,0.9998461064943059,12996,0,0,0.9864885380294519,0,0,17.75409836065574,17.75409836065574,1,0.0,732,0.7681007345225603,221,0,0,0.01677546682860179,0,2545,15722,1.0032640048580537,2547 +matmul,4x56x56xf64,linalg_xdsl,13124,15675,15672,0.0,0,12544,12994,0,0.9900944833892106,0.9998461064943059,12996,0,0,0.9902468759524535,0,0,18.35593220338983,18.35593220338983,1,0.0,708,0.8261376896149358,149,0,0,0.011353245961597074,0,2552,15679,1.0016001219140507,2554 matmul,4x56x60xf64,baseline,96309,98903,98900,0.0,0,13440,13685,0,0.14209471596631676,0.33537556671976476,40805,0,0,0.42368833650022325,0,0,1.0,1.0,1,0.0,40805,0.42386438001848986,55464,0,0,0.5758963336759805,0,2595,98907,0.9995846701762037,2597 -matmul,4x56x60xf64,linalg_xdsl,14110,16663,16660,0.0,0,13440,13922,0,0.9866761162296244,0.9998563631140477,13924,0,0,0.98681785967399,0,0,17.76020408163265,17.760204081632654,1,0.0,784,0.7708947885939036,233,0,0,0.016513111268603827,0,2554,16667,1.003330970942594,2556 +matmul,4x56x60xf64,linalg_xdsl,14075,16678,16675,0.0,0,13440,13922,0,0.9891296625222025,0.9998563631140477,13924,0,0,0.9892717584369449,0,0,18.225130890052355,18.225130890052355,1,0.0,764,0.8153681963713981,173,0,0,0.012291296625222025,0,2604,16682,1.001563055062167,2606 matmul,4x56x64xf64,baseline,102725,105349,105346,0.0,0,14336,14597,0,0.14209783402287662,0.3353704767375072,43525,0,0,0.42370406424920903,0,0,1.0,1.0,1,0.0,43525,0.4238691142815406,59160,0,0,0.5759065466050134,0,2625,105353,0.9996106108542224,2627 matmul,4x56x64xf64,linalg_xdsl,15045,17629,17626,0.0,0,14336,14850,0,0.9870388833499502,0.9998653380016159,14852,0,0,0.9871718178796942,0,0,17.76555023923445,17.76555023923445,1,0.0,836,0.7733580018501388,245,0,0,0.016284479893652375,0,2585,17633,1.0034562977733466,2587 matmul,4x56x8xf64,baseline,12835,14997,14994,0.0,0,1792,1826,0,0.14226723802103622,0.33553840499816245,5442,0,0,0.42399688352162057,0,0,1.0,1.0,1,3.0,5442,0.42595491546649966,7334,6,2,0.5714063108687184,2,2163,15001,0.995403194390339,2165 matmul,4x56x8xf64,linalg_xdsl,1942,4106,4103,0.0,0,1792,1858,0,0.956745623069001,0.9989247311827957,1860,0,0,0.9577754891864058,0,0,17.22222222222222,17.22222222222222,1,0.0,108,0.5837837837837838,77,0,0,0.03964984552008239,0,2165,4110,0.9974253347064882,2167 matmul,4x60x12xf64,baseline,20519,22723,22720,0.0,0,2880,2930,0,0.14279448316194746,0.33531700617990384,8738,0,0,0.4258492129246065,0,0,1.0,1.0,1,3.7142857142857144,8738,0.42743237293939246,11705,26,7,0.5704469028705103,7,2205,22727,0.9962961157951167,2207 -matmul,4x60x12xf64,linalg_xdsl,3070,5272,5269,0.0,0,2880,2978,0,0.9700325732899023,0.9993288590604027,2980,0,0,0.9706840390879479,0,0,18.625,18.625,1,0.0,160,0.642570281124498,89,0,0,0.028990228013029317,0,2203,5276,0.9996742671009772,2205 +matmul,4x60x12xf64,linalg_xdsl,3061,5286,5283,0.0,0,2880,2978,0,0.9728846782097353,0.9993288590604027,2980,0,0,0.9735380594576936,0,0,19.102564102564102,19.102564102564102,1,0.0,156,0.6695278969957081,77,0,0,0.02515517804639007,0,2226,5290,0.9986932375040837,2228 matmul,4x60x16xf64,baseline,27430,29667,29664,0.0,0,3840,3906,0,0.14239883339409407,0.33527896995708156,11650,0,0,0.4247174626321546,0,0,1.0,1.0,1,3.3,11650,0.4263026932084309,15678,33,10,0.571563981042654,10,2238,29671,0.9962814436748086,2240 matmul,4x60x16xf64,linalg_xdsl,4070,6309,6306,0.0,0,3840,3970,0,0.9754299754299754,0.999496475327291,3972,0,0,0.975921375921376,0,0,18.735849056603772,18.735849056603772,1,0.0,212,0.6773162939297125,101,0,0,0.024815724815724815,0,2240,6313,1.0007371007371009,2242 matmul,4x60x20xf64,baseline,34395,36694,36691,0.0,0,4800,4885,0,0.1420264573339148,0.3353930655681428,14565,0,0,0.4234627126035761,0,0,1.0,1.0,1,0.0,14565,0.42402981163934905,19784,0,0,0.5751998837040267,0,2300,36698,0.9986625963076028,2302 -matmul,4x60x20xf64,linalg_xdsl,5070,7337,7334,0.0,0,4800,4962,0,0.978698224852071,0.999597099113618,4964,0,0,0.9790927021696253,0,0,18.803030303030305,18.803030303030305,1,0.0,264,0.7002652519893899,113,0,0,0.022287968441814597,0,2268,7341,1.0013806706114399,2270 +matmul,4x60x20xf64,linalg_xdsl,5067,7353,7350,0.0,0,4800,4962,0,0.9792776791000593,0.999597099113618,4964,0,0,0.9796723899743438,0,0,19.092307692307696,19.092307692307692,1,0.0,260,0.7202216066481995,101,0,0,0.01993289915137162,0,2287,7357,0.9996052891257154,2289 matmul,4x60x24xf64,baseline,41259,43580,43577,0.0,0,5760,5861,0,0.14205385491650308,0.3353550380500086,17477,0,0,0.4235924283186699,0,0,1.0,1.0,1,0.0,17477,0.42406522213864556,23736,0,0,0.5752926634188904,0,2322,43584,0.9988850917375602,2324 -matmul,4x60x24xf64,linalg_xdsl,6070,8374,8371,0.0,0,5760,5954,0,0.9808896210873147,0.9996642041638684,5956,0,0,0.9812191103789127,0,0,18.848101265822784,18.848101265822784,1,0.0,316,0.7165532879818595,125,0,0,0.02059308072487644,0,2305,8378,1.0018121911037892,2307 +matmul,4x60x24xf64,linalg_xdsl,6053,8395,8392,0.0,0,5760,5954,0,0.9836444738146374,0.9996642041638684,5956,0,0,0.9839748884850488,0,0,19.337662337662337,19.337662337662337,1,0.0,308,0.7530562347188264,101,0,0,0.016685940855773997,0,2343,8399,1.0006608293408228,2345 matmul,4x60x28xf64,baseline,48123,50492,50489,0.0,0,6720,6837,0,0.1420734368181535,0.3353278728726274,20389,0,0,0.4236851401616691,0,0,1.0,1.0,1,0.0,20389,0.4240905214551657,27688,0,0,0.5753589759574423,0,2370,50496,0.9990441161191115,2372 -matmul,4x60x28xf64,linalg_xdsl,7070,9407,9404,0.0,0,6720,6946,0,0.9824611032531825,0.9997121473805411,6948,0,0,0.9827439886845828,0,0,18.880434782608695,18.880434782608695,1,0.0,368,0.7287128712871287,137,0,0,0.01937765205091938,0,2338,9411,1.0021216407355023,2340 +matmul,4x60x28xf64,linalg_xdsl,7051,9392,9389,0.0,0,6720,6946,0,0.9851084952489009,0.9997121473805411,6948,0,0,0.9853921429584456,0,0,19.51685393258427,19.51685393258427,1,0.0,356,0.7789934354485777,101,0,0,0.014324209332009645,0,2342,9396,0.9997163522904552,2344 matmul,4x60x32xf64,baseline,54987,57378,57375,0.0,0,7680,7813,0,0.14208812992161785,0.3353074975322948,23301,0,0,0.4237547056577009,0,0,1.0,1.0,1,0.0,23301,0.42410949928104696,31640,0,0,0.5754087329732482,0,2392,57382,0.9991634386309491,2394 matmul,4x60x32xf64,linalg_xdsl,8070,10444,10441,0.0,0,7680,7938,0,0.9836431226765799,0.9997481108312343,7940,0,0,0.9838909541511772,0,0,18.9047619047619,18.904761904761905,1,0.0,420,0.7381370826010545,149,0,0,0.018463444857496902,0,2375,10448,1.002354399008674,2377 matmul,4x60x36xf64,baseline,61851,64285,64282,0.0,0,8640,8789,0,0.14209956185025302,0.33529164918170373,26213,0,0,0.42380883090006627,0,0,1.0,1.0,1,0.0,26213,0.42412426179111723,35592,0,0,0.5754474462821944,0,2435,64289,0.9992562771822606,2437 -matmul,4x60x36xf64,linalg_xdsl,9070,11472,11469,0.0,0,8640,8930,0,0.9845644983461963,0.9997760859829825,8932,0,0,0.9847850055126791,0,0,18.923728813559325,18.923728813559322,1,0.0,472,0.7456556082148499,161,0,0,0.017750826901874312,0,2403,11476,1.0025358324145535,2405 +matmul,4x60x36xf64,linalg_xdsl,9045,11470,11467,0.0,0,8640,8930,0,0.9872857932559425,0.9997760859829825,8932,0,0,0.9875069098949696,0,0,19.417391304347827,19.417391304347827,1,0.0,460,0.7863247863247863,125,0,0,0.013819789939192924,0,2426,11474,1.0013266998341626,2428 matmul,4x60x40xf64,baseline,68715,71171,71168,0.0,0,9600,9765,0,0.1421087098886706,0.33527896995708156,29125,0,0,0.4238521429091174,0,0,1.0,1.0,1,0.0,29125,0.42413607304606155,39544,0,0,0.5754784253801936,0,2457,71175,0.999330568289311,2459 -matmul,4x60x40xf64,linalg_xdsl,10070,12509,12506,0.0,0,9600,9922,0,0.9853028798411122,0.9997984683595325,9924,0,0,0.9855014895729891,0,0,18.938931297709924,18.938931297709924,1,0.0,524,0.7517934002869441,173,0,0,0.01717974180734856,0,2440,12513,1.0026812313803377,2442 +matmul,4x60x40xf64,linalg_xdsl,10053,12512,12509,0.0,0,9600,9922,0,0.9869690639610067,0.9997984683595325,9924,0,0,0.9871680095493882,0,0,19.232558139534884,19.232558139534884,1,0.0,516,0.7759398496240602,149,0,0,0.014821446334427535,0,2460,12516,1.0019894558838158,2462 matmul,4x60x44xf64,baseline,75579,78083,78080,0.0,0,10560,10741,0,0.14211619629791344,0.3352685956862378,32037,0,0,0.4238875878220141,0,0,1.0,1.0,1,0.0,32037,0.4241457376246144,43496,0,0,0.5755037775043332,0,2505,78087,0.9993913653263473,2507 matmul,4x60x44xf64,linalg_xdsl,11070,13542,13539,0.0,0,10560,10914,0,0.9859078590785908,0.9998167827042873,10916,0,0,0.9860885275519422,0,0,18.95138888888889,18.95138888888889,1,0.0,576,0.7568988173455979,185,0,0,0.016711833785004515,0,2473,13546,1.0028003613369467,2475 matmul,4x60x48xf64,baseline,82443,84969,84966,0.0,0,11520,11717,0,0.14212243610737116,0.33525995021316773,34949,0,0,0.42391713062358233,0,0,1.0,1.0,1,0.0,34949,0.42415379200699055,47448,0,0,0.5755249081183363,0,2527,84973,0.9994420387419187,2529 -matmul,4x60x48xf64,linalg_xdsl,12070,14579,14576,0.0,0,11520,11906,0,0.9864125932062966,0.9998320456835741,11908,0,0,0.9865782932891466,0,0,18.961783439490446,18.961783439490446,1,0.0,628,0.7612121212121212,197,0,0,0.01632145816072908,0,2510,14583,1.0028997514498756,2512 +matmul,4x60x48xf64,linalg_xdsl,12037,14584,14581,0.0,0,11520,11906,0,0.9891168895904295,0.9998320456835741,11908,0,0,0.9892830439478275,0,0,19.45751633986928,19.45751633986928,1,0.0,612,0.8042049934296978,149,0,0,0.012378499626152695,0,2548,14588,1.0016615435739802,2550 matmul,4x60x4xf64,baseline,6883,9020,9017,0.0,0,960,977,0,0.14194391980241175,0.3353930655681428,2913,0,0,0.4232166206595961,0,0,1.0,1.0,1,0.0,2913,0.4276905006606959,3898,0,0,0.5663228243498475,0,2138,9024,0.9895394450094436,2140 matmul,4x60x4xf64,linalg_xdsl,1056,3173,3170,0.0,0,960,994,0,0.9412878787878788,0.9979919678714859,996,0,0,0.9431818181818182,0,0,17.785714285714285,17.785714285714285,1,0.0,56,0.5185185185185185,52,0,0,0.04924242424242424,0,2118,3177,0.9924242424242424,2120 matmul,4x60x52xf64,baseline,89307,91876,91873,0.0,0,12480,12693,0,0.14212771675232624,0.33525263463722565,37861,0,0,0.42394213219568455,0,0,1.0,1.0,1,0.0,37861,0.42416060765619923,51400,0,0,0.5755427905987213,0,2570,91880,0.9994849227944058,2572 matmul,4x60x52xf64,linalg_xdsl,13070,15607,15604,0.0,0,12480,12898,0,0.9868400918133129,0.9998449612403101,12900,0,0,0.9869931140015302,0,0,18.97058823529412,18.970588235294116,1,0.0,680,0.7649043869516311,209,0,0,0.01599081866870696,0,2538,15611,1.0029839326702372,2540 matmul,4x60x56xf64,baseline,96171,98762,98759,0.0,0,13440,13669,0,0.14213224360774038,0.33524636401540236,40773,0,0,0.42396356490002185,0,0,1.0,1.0,1,0.0,40773,0.4241664499349805,55352,0,0,0.575558120431315,0,2592,98766,0.9995216853313369,2594 -matmul,4x60x56xf64,linalg_xdsl,14070,16644,16641,0.0,0,13440,13890,0,0.9872068230277186,0.9998560322487763,13892,0,0,0.9873489694385217,0,0,18.97814207650273,18.97814207650273,1,0.0,732,0.7681007345225603,221,0,0,0.01570717839374556,0,2575,16648,1.0030561478322673,2577 +matmul,4x60x56xf64,linalg_xdsl,14020,16601,16598,0.0,0,13440,13890,0,0.9907275320970043,0.9998560322487763,13892,0,0,0.990870185449358,0,0,19.62146892655367,19.62146892655367,1,0.0,708,0.8261376896149358,149,0,0,0.010627674750356633,0,2582,16605,1.0014978601997147,2584 matmul,4x60x60xf64,baseline,103035,105661,105658,0.0,0,14400,14645,0,0.14213616732178386,0.3352409293807943,43685,0,0,0.4239821419905857,0,0,1.0,1.0,1,0.0,43685,0.4241715134626028,59304,0,0,0.5755714077740574,0,2627,105665,0.9995535497646431,2629 -matmul,4x60x60xf64,linalg_xdsl,15070,17679,17676,0.0,0,14400,14882,0,0.9875248838752488,0.999865627519484,14884,0,0,0.987657597876576,0,0,18.98469387755102,18.98469387755102,1,0.0,784,0.7708947885939036,233,0,0,0.015461181154611812,0,2610,17683,1.0031187790311877,2612 +matmul,4x60x60xf64,linalg_xdsl,15029,17676,17673,0.0,0,14400,14882,0,0.9902189101071263,0.999865627519484,14884,0,0,0.9903519861600905,0,0,19.481675392670155,19.48167539267016,1,0.0,764,0.8153681963713981,173,0,0,0.011511078581409276,0,2648,17680,1.0018630647414997,2650 matmul,4x60x64xf64,baseline,109899,112555,112552,0.0,0,15360,15621,0,0.1421396009062867,0.3352361740026182,46597,0,0,0.42399839852955895,0,0,1.0,1.0,1,0.0,46597,0.42417594421636184,63256,0,0,0.5755830353324416,0,2657,112559,0.9995814338620006,2659 matmul,4x60x64xf64,linalg_xdsl,16070,18709,18706,0.0,0,15360,15874,0,0.9878033602986932,0.9998740236835475,15876,0,0,0.9879278158058494,0,0,18.99043062200957,18.99043062200957,1,0.0,836,0.7733580018501388,245,0,0,0.015245799626633479,0,2640,18713,1.0031736154324828,2642 matmul,4x60x8xf64,baseline,13731,15903,15900,0.0,0,1920,1954,0,0.1423057315563324,0.3353930655681428,5826,0,0,0.4242953899934455,0,0,1.0,1.0,1,3.0,5826,0.42612638970157984,7846,6,2,0.5714077634549559,2,2173,15907,0.9957031534484014,2175 matmul,4x60x8xf64,linalg_xdsl,2070,4244,4241,0.0,0,1920,1986,0,0.9594202898550724,0.9989939637826962,1988,0,0,0.9603864734299516,0,0,18.40740740740741,18.40740740740741,1,0.0,108,0.5837837837837838,77,0,0,0.03719806763285024,0,2175,4248,0.9975845410628019,2177 matmul,4x64x12xf64,baseline,21863,24077,24074,0.0,0,3072,3122,0,0.1427983350866761,0.33519433111445135,9314,0,0,0.42601655765448476,0,0,1.0,1.0,1,3.7142857142857144,9314,0.4275026391885069,12473,26,7,0.5705072496912592,7,2215,24081,0.996523807345744,2217 -matmul,4x64x12xf64,linalg_xdsl,3262,5474,5471,0.0,0,3072,3170,0,0.9717964438994482,0.9993694829760403,3172,0,0,0.9724095646842428,0,0,19.825,19.825,1,0.0,160,0.642570281124498,89,0,0,0.027283874923359902,0,2213,5478,0.9996934396076027,2215 +matmul,4x64x12xf64,linalg_xdsl,3253,5488,5485,0.0,0,3072,3170,0,0.974485090685521,0.9993694829760403,3172,0,0,0.9750999077774362,0,0,20.333333333333336,20.333333333333332,1,0.0,156,0.6695278969957081,77,0,0,0.023670458038733477,0,2236,5492,0.9987703658161696,2238 matmul,4x64x16xf64,baseline,29230,31454,31451,0.0,0,4096,4162,0,0.142387957577831,0.3351586406828797,12418,0,0,0.42483749572357166,0,0,1.0,1.0,1,3.3,12418,0.4264423076923077,16702,33,10,0.5713992473486145,10,2225,31458,0.9962367430721861,2227 matmul,4x64x16xf64,linalg_xdsl,4331,6557,6554,0.0,0,4096,4226,0,0.9757561764026783,0.9995269631031221,4228,0,0,0.9762179635188178,0,0,19.943396226415093,19.943396226415093,1,0.0,212,0.6773162939297125,101,0,0,0.023320249365042716,0,2227,6561,0.9995382128838606,2229 matmul,4x64x20xf64,baseline,36635,38949,38946,0.0,0,5120,5205,0,0.1420772485328238,0.3352657004830918,15525,0,0,0.4237750784768664,0,0,1.0,1.0,1,0.0,15525,0.42430785208669275,21064,0,0,0.57496929166098,0,2315,38953,0.9987443701378464,2317 -matmul,4x64x20xf64,linalg_xdsl,5390,7672,7669,0.0,0,5120,5282,0,0.9799628942486085,0.9996214988644966,5284,0,0,0.9803339517625231,0,0,20.015151515151516,20.015151515151516,1,0.0,264,0.7002652519893899,113,0,0,0.020964749536178107,0,2283,7676,1.0012987012987011,2285 +matmul,4x64x20xf64,linalg_xdsl,5387,7688,7685,0.0,0,5120,5282,0,0.9805086318915909,0.9996214988644966,5284,0,0,0.9808798960460368,0,0,20.323076923076925,20.323076923076922,1,0.0,260,0.7202216066481995,101,0,0,0.018748839799517355,0,2302,7692,0.9996287358455541,2304 matmul,4x64x24xf64,baseline,43941,46299,46296,0.0,0,6144,6245,0,0.1421223913884527,0.3352300177143164,18629,0,0,0.4239548485469152,0,0,1.0,1.0,1,0.0,18629,0.42434113118152206,25272,0,0,0.5751348398989554,0,2359,46303,0.9990896884458706,2361 -matmul,4x64x24xf64,linalg_xdsl,6459,8755,8752,0.0,0,6144,6338,0,0.9812664499148475,0.9996845425867508,6340,0,0,0.9815760953708005,0,0,20.063291139240505,20.063291139240505,1,0.0,316,0.7165532879818595,125,0,0,0.01935284099705837,0,2297,8759,1.0009289363678588,2299 +matmul,4x64x24xf64,linalg_xdsl,6437,8768,8765,0.0,0,6144,6338,0,0.9846201646729843,0.9996845425867508,6340,0,0,0.9849308684169644,0,0,20.584415584415584,20.584415584415584,1,0.0,308,0.7530562347188264,101,0,0,0.015690539070995806,0,2332,8772,1.0006214074879602,2334 matmul,4x64x28xf64,baseline,51259,53643,53640,0.0,0,7168,7285,0,0.1421213835619111,0.33520452767680486,21733,0,0,0.42398408084433953,0,0,1.0,1.0,1,0.0,21733,0.42436490734774374,29480,0,0,0.5751185157728399,0,2385,53647,0.9991025966171794,2387 -matmul,4x64x28xf64,linalg_xdsl,7518,9870,9867,0.0,0,7168,7394,0,0.9835062516626762,0.9997295835586804,7396,0,0,0.9837722798616654,0,0,20.09782608695652,20.097826086956523,1,0.0,368,0.7287128712871287,137,0,0,0.01822293163075286,0,2353,9874,1.0019952114924182,2355 +matmul,4x64x28xf64,linalg_xdsl,7499,9855,9852,0.0,0,7168,7394,0,0.9859981330844113,0.9997295835586804,7396,0,0,0.9862648353113749,0,0,20.775280898876403,20.775280898876403,1,0.0,356,0.7789934354485777,101,0,0,0.013468462461661555,0,2357,9859,0.9997332977730364,2359 matmul,4x64x32xf64,baseline,58565,60998,60995,0.0,0,8192,8325,0,0.14214974814308887,0.33518540886580506,24837,0,0,0.4240928882438316,0,0,1.0,1.0,1,0.0,24837,0.4243827424177702,33688,0,0,0.5752241099632887,0,2434,61002,0.9993169982071203,2436 matmul,4x64x32xf64,linalg_xdsl,8587,10953,10950,0.0,0,8192,8450,0,0.9840456504017702,0.9997633696166588,8452,0,0,0.984278560614883,0,0,20.123809523809523,20.123809523809523,1,0.0,420,0.7381370826010545,149,0,0,0.017351810876906952,0,2367,10957,1.0016303714917898,2369 matmul,4x64x36xf64,baseline,65883,68337,68334,0.0,0,9216,9365,0,0.14214592535251885,0.3351705379191869,27941,0,0,0.4241002990149204,0,0,1.0,1.0,1,0.0,27941,0.4243966158846849,37896,0,0,0.5752014935567598,0,2455,68341,0.9993017925716802,2457 -matmul,4x64x36xf64,linalg_xdsl,9646,12068,12065,0.0,0,9216,9506,0,0.9854862119013063,0.9997896508203618,9508,0,0,0.9856935517312876,0,0,20.144067796610173,20.14406779661017,1,0.0,472,0.7456556082148499,161,0,0,0.016690856313497822,0,2423,12072,1.0023844080447855,2425 +matmul,4x64x36xf64,linalg_xdsl,9621,12066,12063,0.0,0,9216,9506,0,0.988046980563351,0.9997896508203618,9508,0,0,0.9882548591622492,0,0,20.669565217391305,20.669565217391305,1,0.0,460,0.7863247863247863,125,0,0,0.012992412431140214,0,2446,12070,1.0012472715933893,2448 matmul,4x64x40xf64,baseline,73189,75692,75689,0.0,0,10240,10405,0,0.14216617251226277,0.3351586406828797,31045,0,0,0.42417576411755864,0,0,1.0,1.0,1,0.0,31045,0.4244077157582469,42104,0,0,0.575277705666152,0,2504,75696,0.9994534697837106,2506 -matmul,4x64x40xf64,linalg_xdsl,10715,13156,13153,0.0,0,10240,10562,0,0.9857209519365375,0.9998106777735706,10564,0,0,0.9859076061595894,0,0,20.16030534351145,20.16030534351145,1,0.0,524,0.7517934002869441,173,0,0,0.0161455902939804,0,2442,13160,1.0020531964535697,2444 +matmul,4x64x40xf64,linalg_xdsl,10699,13193,13190,0.0,0,10240,10562,0,0.987195064959342,0.9998106777735706,10564,0,0,0.9873819983175998,0,0,20.472868217054263,20.472868217054263,1,0.0,516,0.7759398496240602,149,0,0,0.013926535190204693,0,2495,13197,1.0013085335078045,2497 matmul,4x64x44xf64,baseline,80507,83036,83033,0.0,0,11264,11445,0,0.14216155116946352,0.3351489062637266,34149,0,0,0.4241742954028842,0,0,1.0,1.0,1,0.0,34149,0.42441679820037037,46312,0,0,0.5752543257108077,0,2530,83040,0.9994286211136919,2532 matmul,4x64x44xf64,linalg_xdsl,11774,14271,14268,0.0,0,11264,11618,0,0.9867504671309666,0.999827882960413,11620,0,0,0.9869203329369798,0,0,20.173611111111114,20.17361111111111,1,0.0,576,0.7568988173455979,185,0,0,0.015712587056225583,0,2498,14275,1.0026329199932054,2500 matmul,4x64x48xf64,baseline,87813,90386,90383,0.0,0,12288,12485,0,0.14217712639358637,0.335140794030011,37253,0,0,0.4242310364069101,0,0,1.0,1.0,1,0.0,37253,0.42442436740227635,50520,0,0,0.5753134501725257,0,2574,90390,0.9995444865794358,2576 -matmul,4x64x48xf64,linalg_xdsl,12843,15354,15351,0.0,0,12288,12674,0,0.9868410807443744,0.9998422215209846,12676,0,0,0.9869968075994705,0,0,20.18471337579618,20.18471337579618,1,0.0,628,0.7612121212121212,197,0,0,0.015339095226971891,0,2512,15358,1.0023359028264425,2514 +matmul,4x64x48xf64,linalg_xdsl,12805,15351,15348,0.0,0,12288,12674,0,0.9897696212417024,0.9998422215209846,12676,0,0,0.9899258102303787,0,0,20.712418300653592,20.712418300653596,1,0.0,612,0.8042049934296978,149,0,0,0.011636079656384225,0,2547,15355,1.0015618898867629,2549 matmul,4x64x4xf64,baseline,7328,9476,9473,0.0,0,1024,1041,0,0.14205786026200873,0.3352657004830918,3105,0,0,0.42371724890829693,0,0,1.0,1.0,1,0.0,3105,0.42774486843917897,4154,0,0,0.5668668122270742,0,2149,9480,0.9905840611353711,2151 matmul,4x64x4xf64,linalg_xdsl,1125,3272,3269,0.0,0,1024,1058,0,0.9404444444444444,0.9981132075471698,1060,0,0,0.9422222222222222,0,0,18.928571428571427,18.928571428571427,1,0.0,56,0.5185185185185185,52,0,0,0.04622222222222222,0,2148,3276,0.9884444444444445,2150 matmul,4x64x52xf64,baseline,95131,97730,97727,0.0,0,13312,13525,0,0.142172372833251,0.3351339296776272,40357,0,0,0.42422554162155346,0,0,1.0,1.0,1,0.0,40357,0.42443077246674027,54728,0,0,0.5752909146335053,0,2600,97734,0.9995164562550588,2602 matmul,4x64x52xf64,linalg_xdsl,13902,16469,16466,0.0,0,13312,13730,0,0.9876276794705797,0.9998543547917274,13732,0,0,0.9877715436627823,0,0,20.194117647058825,20.194117647058825,1,0.0,680,0.7649043869516311,209,0,0,0.015033808085167601,0,2568,16473,1.0028053517479498,2570 matmul,4x64x56xf64,baseline,102437,105080,105077,0.0,0,14336,14565,0,0.14218495270263673,0.3351280458341962,43461,0,0,0.42427052725089565,0,0,1.0,1.0,1,0.0,43461,0.42443626278113616,58936,0,0,0.5753389888419224,0,2644,105084,0.999609516092818,2646 -matmul,4x64x56xf64,linalg_xdsl,14971,17552,17549,0.0,0,14336,14786,0,0.9876427760336651,0.9998647552069245,14788,0,0,0.9877763676441119,0,0,20.202185792349727,20.202185792349727,1,0.0,732,0.7681007345225603,221,0,0,0.014761872954378466,0,2582,17556,1.0025382405984904,2584 +matmul,4x64x56xf64,linalg_xdsl,14923,17528,17525,0.0,0,14336,14786,0,0.9908195403069088,0.9998647552069245,14788,0,0,0.990953561616297,0,0,20.887005649717516,20.887005649717516,1,0.0,708,0.8261376896149358,149,0,0,0.009984587549420358,0,2606,17532,1.0009381491657174,2608 matmul,4x64x60xf64,baseline,109755,112424,112421,0.0,0,15360,15605,0,0.1421803106919958,0.3351229464189842,46565,0,0,0.4242631315202041,0,0,1.0,1.0,1,0.0,46565,0.42444102124711736,63144,0,0,0.5753177531775318,0,2670,112428,0.9995808846977359,2672 -matmul,4x64x60xf64,linalg_xdsl,16030,18667,18664,0.0,0,15360,15842,0,0.9882719900187149,0.9998737692501893,15844,0,0,0.9883967560823456,0,0,20.209183673469386,20.209183673469386,1,0.0,784,0.7708947885939036,233,0,0,0.014535246412975671,0,2638,18671,1.0029320024953212,2640 +matmul,4x64x60xf64,linalg_xdsl,15989,18649,18646,0.0,0,15360,15842,0,0.9908061792482331,0.9998737692501893,15844,0,0,0.9909312652448559,0,0,20.73821989528796,20.73821989528796,1,0.0,764,0.8153681963713981,173,0,0,0.010819938707861654,0,2661,18653,1.0017512039527174,2663 matmul,4x64x64xf64,baseline,117067,119763,119760,0.0,0,16384,16645,0,0.14218353592387264,0.33511848436650626,49669,0,0,0.4242784046742464,0,0,1.0,1.0,1,0.0,49669,0.4244451850522556,67352,0,0,0.5753286579480127,0,2697,119767,0.9996070626222591,2699 matmul,4x64x64xf64,linalg_xdsl,17099,19781,19778,0.0,0,16384,16898,0,0.988244926603895,0.9998816568047337,16900,0,0,0.9883618925083338,0,0,20.215311004784688,20.215311004784688,1,0.0,836,0.7733580018501388,245,0,0,0.01432832329375987,0,2683,19785,1.0026902158020936,2685 matmul,4x64x8xf64,baseline,14627,16819,16816,0.0,0,2048,2082,0,0.142339509126957,0.3352657004830918,6210,0,0,0.42455732549394953,0,0,1.0,1.0,1,3.0,6210,0.4262767710049423,8358,6,2,0.5714090380802626,2,2193,16823,0.9959663635742121,2195 matmul,4x64x8xf64,linalg_xdsl,2203,4383,4380,0.0,0,2048,2114,0,0.9596005447117567,0.999054820415879,2116,0,0,0.9605083976395824,0,0,19.59259259259259,19.59259259259259,1,0.0,108,0.5837837837837838,77,0,0,0.03495233772128915,0,2181,4387,0.9954607353608715,2183 matmul,4x8x12xf64,baseline,2239,4348,4345,0.0,0,336,385,0,0.1719517641804377,0.3205661948376353,1201,0,0,0.5364001786511836,0,0,1.0,1.0,1,0.0,1201,0.851169383416017,210,0,0,0.09379187137114783,0,2110,4352,0.6301920500223315,2112 -matmul,4x8x12xf64,linalg_xdsl,580,2689,2686,0.0,0,384,482,0,0.8310344827586207,0.9958677685950413,484,0,0,0.8344827586206897,0,0,3.0250000000000004,3.025,1,0.0,160,0.6477732793522267,87,0,0,0.15,0,2110,2693,0.9844827586206897,2112 +matmul,4x8x12xf64,linalg_xdsl,563,2644,2641,0.0,0,384,482,0,0.8561278863232682,0.9958677685950413,484,0,0,0.8596802841918295,0,0,3.1025641025641026,3.1025641025641026,1,0.0,156,0.6753246753246753,75,0,0,0.13321492007104796,0,2082,2648,0.9928952042628775,2084 matmul,4x8x16xf64,baseline,2975,5089,5086,0.0,0,448,513,0,0.17243697478991596,0.3204247345409119,1601,0,0,0.5381512605042017,0,0,1.0,1.0,1,0.0,1601,0.8538666666666667,274,0,0,0.09210084033613446,0,2115,5093,0.6302521008403361,2117 matmul,4x8x16xf64,linalg_xdsl,748,2862,2859,0.0,0,512,642,0,0.8582887700534759,0.9968944099378882,644,0,0,0.8609625668449198,0,0,3.0377358490566033,3.0377358490566038,1,0.0,212,0.6816720257234726,99,0,0,0.1323529411764706,0,2115,2866,0.9933155080213903,2117 matmul,4x8x20xf64,baseline,3711,5835,5832,0.0,0,560,641,0,0.17272972244677984,0.32033983008495753,2001,0,0,0.5392077607113985,0,0,1.0,1.0,1,0.0,2001,0.8554938007695596,338,0,0,0.09108057127458906,0,2125,5839,0.6302883319859875,2127 -matmul,4x8x20xf64,linalg_xdsl,918,3042,3039,0.0,0,640,802,0,0.8736383442265795,0.9975124378109452,804,0,0,0.8758169934640523,0,0,3.045454545454546,3.0454545454545454,1,0.0,264,0.704,111,0,0,0.12091503267973856,0,2125,3046,0.9967320261437909,2127 +matmul,4x8x20xf64,linalg_xdsl,900,2992,2989,0.0,0,640,802,0,0.8911111111111111,0.9975124378109452,804,0,0,0.8933333333333333,0,0,3.0923076923076924,3.0923076923076924,1,0.0,260,0.724233983286908,99,0,0,0.11,0,2093,2996,1.0033333333333334,2095 matmul,4x8x24xf64,baseline,4447,6576,6573,0.0,0,672,769,0,0.17292556779851587,0.3202832153269471,2401,0,0,0.5399145491342479,0,0,1.0,1.0,1,0.0,2401,0.8565822333214413,402,0,0,0.09039802113784574,0,2130,6580,0.6303125702720936,2132 -matmul,4x8x24xf64,linalg_xdsl,1084,3213,3210,0.0,0,768,962,0,0.8874538745387454,0.9979253112033195,964,0,0,0.8892988929889298,0,0,3.050632911392405,3.050632911392405,1,0.0,316,0.7198177676537585,123,0,0,0.11346863468634687,0,2130,3217,1.0027675276752768,2132 +matmul,4x8x24xf64,linalg_xdsl,1059,3160,3157,0.0,0,768,962,0,0.9084041548630784,0.9979253112033195,964,0,0,0.9102927289896129,0,0,3.12987012987013,3.1298701298701297,1,0.0,308,0.7567567567567568,99,0,0,0.09348441926345609,0,2102,3164,1.003777148253069,2104 matmul,4x8x28xf64,baseline,5183,7284,7281,0.0,0,784,897,0,0.17306579201234806,0.3202427704391289,2801,0,0,0.5404206058267412,0,0,1.0,1.0,1,0.0,2801,0.85736149372513,466,0,0,0.0899093189272622,0,2102,7288,0.6303299247540034,2104 -matmul,4x8x28xf64,linalg_xdsl,1252,3353,3350,0.0,0,896,1122,0,0.8961661341853036,0.998220640569395,1124,0,0,0.8977635782747604,0,0,3.0543478260869565,3.0543478260869565,1,0.0,368,0.731610337972167,135,0,0,0.10782747603833866,0,2102,3357,1.005591054313099,2104 +matmul,4x8x28xf64,linalg_xdsl,1219,3381,3378,0.0,0,896,1122,0,0.9204265791632485,0.998220640569395,1124,0,0,0.9220672682526662,0,0,3.157303370786517,3.157303370786517,1,0.0,356,0.7824175824175824,99,0,0,0.081214109926169,0,2163,3385,1.0032813781788352,2165 matmul,4x8x32xf64,baseline,5911,8013,8010,0.0,0,896,1025,0,0.17340551514126207,0.3202124336144955,3201,0,0,0.5415327355777364,0,0,1.0,1.0,1,0.0,3201,0.8579469311176628,530,0,0,0.08966333953645746,0,2103,8017,0.6311960751141938,2105 matmul,4x8x32xf64,linalg_xdsl,1412,3514,3511,0.0,0,1024,1282,0,0.9079320113314447,0.9984423676012462,1284,0,0,0.9093484419263456,0,0,3.057142857142857,3.057142857142857,1,0.0,420,0.7407407407407407,147,0,0,0.10410764872521247,0,2103,3518,1.013456090651558,2105 matmul,4x8x36xf64,baseline,6647,8754,8751,0.0,0,1008,1153,0,0.1734617120505491,0.3201888364343238,3601,0,0,0.5417481570633368,0,0,1.0,1.0,1,0.0,3601,0.8584028605482718,594,0,0,0.08936362268692644,0,2108,8758,0.6311117797502632,2110 -matmul,4x8x36xf64,linalg_xdsl,1581,3696,3693,0.0,0,1152,1442,0,0.9120809614168248,0.9986149584487535,1444,0,0,0.9133459835547122,0,0,3.059322033898305,3.059322033898305,1,0.0,472,0.7468354430379747,160,0,0,0.10120177103099304,0,2116,3700,1.0145477545857053,2118 +matmul,4x8x36xf64,linalg_xdsl,1562,3731,3728,0.0,0,1152,1442,0,0.9231754161331626,0.9986149584487535,1444,0,0,0.9244558258642765,0,0,3.1391304347826083,3.139130434782609,1,0.0,460,0.7876712328767124,124,0,0,0.0793854033290653,0,2170,3735,1.0038412291933418,2172 matmul,4x8x40xf64,baseline,7383,9500,9497,0.0,0,1120,1281,0,0.17350670459162942,0.3201699575106223,4001,0,0,0.5419206284708113,0,0,1.0,1.0,1,0.0,4001,0.8587679759605066,658,0,0,0.0891236624678315,0,2118,9504,0.6310442909386429,2120 -matmul,4x8x40xf64,linalg_xdsl,1750,3893,3890,0.0,0,1280,1602,0,0.9154285714285715,0.9987531172069826,1604,0,0,0.9165714285714286,0,0,3.061068702290076,3.0610687022900764,1,0.0,524,0.7517934002869441,173,0,0,0.09885714285714285,0,2144,3897,1.0154285714285713,2146 +matmul,4x8x40xf64,linalg_xdsl,1733,3897,3894,0.0,0,1280,1602,0,0.9244085401038661,0.9987531172069826,1604,0,0,0.9255626081938835,0,0,3.108527131782946,3.108527131782946,1,0.0,516,0.7759398496240602,149,0,0,0.08597807270628967,0,2165,3901,1.0115406809001732,2167 matmul,4x8x44xf64,baseline,8119,10241,10238,0.0,0,1232,1409,0,0.17354353984480847,0.3201545103385594,4401,0,0,0.5420618302746644,0,0,1.0,1.0,1,0.0,4401,0.8590669529572517,722,0,0,0.08892720778420987,0,2123,10245,0.6309890380588743,2125 matmul,4x8x44xf64,linalg_xdsl,1918,4066,4063,0.0,0,1408,1762,0,0.9186652763295099,0.9988662131519275,1764,0,0,0.9197080291970803,0,0,3.0625,3.0625,1,0.0,576,0.7568988173455979,185,0,0,0.09645464025026068,0,2149,4070,1.016162669447341,2151 matmul,4x8x48xf64,baseline,8855,10982,10979,0.0,0,1344,1537,0,0.1735742518351214,0.32014163715892524,4801,0,0,0.542179559570864,0,0,1.0,1.0,1,0.0,4801,0.8593162699122964,786,0,0,0.08876341050254094,0,2128,10986,0.6309429700734048,2130 -matmul,4x8x48xf64,linalg_xdsl,2086,4239,4236,0.0,0,1536,1922,0,0.9213806327900288,0.998960498960499,1924,0,0,0.9223394055608821,0,0,3.0636942675159236,3.0636942675159236,1,0.0,628,0.7612121212121212,197,0,0,0.09443911792905081,0,2154,4243,1.016778523489933,2156 +matmul,4x8x48xf64,linalg_xdsl,2053,4246,4243,0.0,0,1536,1922,0,0.9361909400876766,0.998960498960499,1924,0,0,0.9371651242084754,0,0,3.1437908496732025,3.1437908496732025,1,0.0,612,0.8042049934296978,149,0,0,0.0725767169995129,0,2194,4250,1.0097418412079884,2196 matmul,4x8x4xf64,baseline,752,2809,2806,0.0,0,112,129,0,0.17154255319148937,0.32169576059850374,401,0,0,0.5332446808510638,0,0,1.0,1.0,1,0.0,401,0.9413145539906104,25,0,0,0.03324468085106383,0,2058,2813,0.5664893617021276,2060 matmul,4x8x4xf64,linalg_xdsl,226,2307,2304,0.0,0,128,162,0,0.7168141592920354,0.9878048780487805,164,0,0,0.7256637168141593,0,0,2.9285714285714284,2.9285714285714284,1,0.0,56,0.5233644859813084,51,0,0,0.22566371681415928,0,2082,2311,0.9513274336283186,2084 matmul,4x8x52xf64,baseline,9589,11774,11771,0.0,0,1456,1665,0,0.17363645844196476,0.32013074408767545,5201,0,0,0.5423923245385337,0,0,1.0,1.0,1,0.0,5201,0.7978217518024237,1318,0,0,0.13744916049640213,0,2186,11778,0.6798414850349358,2188 matmul,4x8x52xf64,linalg_xdsl,2260,4423,4420,0.0,0,1664,2082,0,0.9212389380530973,0.9990403071017274,2084,0,0,0.9221238938053097,0,0,3.064705882352941,3.0647058823529414,1,0.0,680,0.7649043869516311,209,0,0,0.09247787610619469,0,2164,4427,1.0146017699115044,2166 matmul,4x8x56xf64,baseline,10325,12515,12512,0.0,0,1568,1793,0,0.17365617433414043,0.3201214068916265,5601,0,0,0.5424697336561743,0,0,1.0,1.0,1,0.0,5601,0.7979769197891438,1418,0,0,0.1373365617433414,0,2191,12519,0.6798062953995158,2193 -matmul,4x8x56xf64,linalg_xdsl,2422,4590,4587,0.0,0,1792,2242,0,0.925681255161024,0.9991087344028521,2244,0,0,0.9265070189925682,0,0,3.0655737704918034,3.0655737704918034,1,0.0,732,0.7681007345225603,221,0,0,0.09124690338563171,0,2169,4594,1.0177539223782,2171 +matmul,4x8x56xf64,linalg_xdsl,2372,4549,4546,0.0,0,1792,2242,0,0.945193929173693,0.9991087344028521,2244,0,0,0.9460370994940978,0,0,3.1694915254237284,3.169491525423729,1,0.0,708,0.8261376896149358,149,0,0,0.06281618887015177,0,2178,4553,1.0088532883642496,2180 matmul,4x8x60xf64,baseline,11061,13273,13270,0.0,0,1680,1921,0,0.17367326643160655,0.32011331444759206,6001,0,0,0.5425368411536028,0,0,1.0,1.0,1,0.0,6001,0.7981114509908233,1518,0,0,0.13723894765391917,0,2213,13277,0.679775788807522,2215 -matmul,4x8x60xf64,linalg_xdsl,2590,4743,4740,0.0,0,1920,2402,0,0.9274131274131274,0.9991680532445923,2404,0,0,0.9281853281853282,0,0,3.066326530612245,3.066326530612245,1,0.0,784,0.7708947885939036,233,0,0,0.08996138996138996,0,2154,4747,1.018146718146718,2156 +matmul,4x8x60xf64,linalg_xdsl,2555,4758,4755,0.0,0,1920,2402,0,0.9401174168297456,0.9991680532445923,2404,0,0,0.9409001956947163,0,0,3.1465968586387434,3.1465968586387434,1,0.0,764,0.8153681963713981,173,0,0,0.06771037181996085,0,2204,4762,1.008610567514677,2206 matmul,4x8x64xf64,baseline,11805,13962,13959,0.0,0,1792,2049,0,0.1735705209656925,0.3201062334010311,6401,0,0,0.5422278695468022,0,0,1.0,1.0,1,0.0,6401,0.8598871574422353,1043,0,0,0.08835239305379076,0,2158,13966,0.630580262600593,2160 matmul,4x8x64xf64,linalg_xdsl,2757,4913,4910,0.0,0,2048,2562,0,0.9292709466811752,0.999219968798752,2564,0,0,0.9299963728690606,0,0,3.0669856459330145,3.0669856459330145,1,0.0,836,0.7733580018501388,245,0,0,0.08886470801595937,0,2157,4917,1.01886108088502,2159 matmul,4x8x8xf64,baseline,1504,3592,3589,0.0,0,224,257,0,0.17087765957446807,0.3208489388264669,801,0,0,0.5325797872340425,0,0,1.0,1.0,1,0.0,801,0.9685610640870617,26,0,0,0.017287234042553192,0,2089,3596,0.5498670212765957,2091 matmul,4x8x8xf64,linalg_xdsl,412,2500,2497,0.0,0,256,322,0,0.7815533980582524,0.9938271604938271,324,0,0,0.7864077669902912,0,0,3.0,3.0,1,0.0,108,0.5901639344262295,75,0,0,0.1820388349514563,0,2089,2504,0.9684466019417476,2091 matmul,8x12x12xf64,baseline,6505,8641,8638,0.0,0,1056,1153,0,0.17724827056110684,0.32451449479313255,3553,0,0,0.5461952344350499,0,0,1.0,1.0,1,4.4,3553,0.8676434676434677,542,22,5,0.08332052267486549,5,2137,8645,0.6295157571099154,2139 -matmul,8x12x12xf64,linalg_xdsl,1468,3581,3578,0.0,0,1152,1346,0,0.9168937329700273,0.9985163204747775,1348,0,0,0.9182561307901907,0,0,4.265822784810126,4.265822784810126,1,0.0,316,0.7198177676537585,123,0,0,0.0837874659400545,0,2114,3585,1.0020435967302452,2116 +matmul,8x12x12xf64,linalg_xdsl,1443,3568,3565,0.0,0,1152,1346,0,0.9327789327789328,0.9985163204747775,1348,0,0,0.9341649341649342,0,0,4.376623376623376,4.376623376623376,1,0.0,308,0.7567567567567568,99,0,0,0.06860706860706861,0,2126,3572,1.0027720027720028,2128 matmul,8x12x16xf64,baseline,8651,10776,10773,0.0,0,1408,1537,0,0.17766732169691365,0.3244669622123707,4737,0,0,0.5475667552884059,0,0,1.0,1.0,1,4.166666666666667,4737,0.8756007393715342,673,25,6,0.07779447462721073,6,2126,10780,0.6253612299156166,2128 matmul,8x12x16xf64,linalg_xdsl,1932,4033,4030,0.0,0,1536,1794,0,0.9285714285714286,0.9988864142538976,1796,0,0,0.9296066252587992,0,0,4.276190476190476,4.276190476190476,1,0.0,420,0.7407407407407407,147,0,0,0.07608695652173914,0,2102,4037,1.0056935817805384,2104 matmul,8x12x20xf64,baseline,10795,12930,12927,0.0,0,1760,1921,0,0.17795275590551182,0.32443843945279516,5921,0,0,0.5484946734599352,0,0,1.0,1.0,1,4.166666666666667,5921,0.8808390360011901,801,25,6,0.07420101899027327,6,2136,12934,0.6226956924502085,2138 -matmul,8x12x20xf64,linalg_xdsl,2396,4507,4504,0.0,0,1920,2242,0,0.9357262103505843,0.9991087344028521,2244,0,0,0.9365609348914858,0,0,4.2824427480916025,4.282442748091603,1,0.0,524,0.753956834532374,171,0,0,0.07136894824707847,0,2112,4511,1.0079298831385644,2114 +matmul,8x12x20xf64,linalg_xdsl,2372,4510,4507,0.0,0,1920,2242,0,0.945193929173693,0.9991087344028521,2244,0,0,0.9460370994940978,0,0,4.348837209302325,4.348837209302325,1,0.0,516,0.7782805429864253,147,0,0,0.06197301854974705,0,2139,4514,1.0080101180438448,2141 matmul,8x12x24xf64,baseline,12939,15087,15084,0.0,0,2112,2305,0,0.17814359687765668,0.32441942294159043,7105,0,0,0.5491150784450112,0,0,1.0,1.0,1,4.166666666666667,7105,0.8843664426188698,929,25,6,0.07179843882834841,6,2149,15091,0.6209135172733595,2151 -matmul,8x12x24xf64,linalg_xdsl,2854,5002,4999,0.0,0,2304,2690,0,0.9425367904695164,0.9992570579494799,2692,0,0,0.9432375613174492,0,0,4.286624203821655,4.286624203821656,1,0.0,628,0.7612121212121212,197,0,0,0.06902592852137351,0,2149,5006,1.0122634898388227,2151 +matmul,8x12x24xf64,linalg_xdsl,2821,5009,5006,0.0,0,2304,2690,0,0.9535625664657923,0.9992570579494799,2692,0,0,0.9542715349166963,0,0,4.398692810457517,4.398692810457517,1,0.0,612,0.8042049934296978,149,0,0,0.05281814959234314,0,2189,5013,1.0070896845090394,2191 matmul,8x12x28xf64,baseline,15083,17241,17238,0.0,0,2464,2689,0,0.17828018298746934,0.32440583906381953,8289,0,0,0.5495591062785918,0,0,1.0,1.0,1,4.166666666666667,8289,0.8869034881232613,1057,25,6,0.07007889677119937,6,2159,17245,0.6196380030497912,2161 -matmul,8x12x28xf64,linalg_xdsl,3318,5476,5473,0.0,0,2688,3138,0,0.945750452079566,0.9993630573248408,3140,0,0,0.9463532248342374,0,0,4.2896174863387975,4.2896174863387975,1,0.0,732,0.7681007345225603,221,0,0,0.06660638939119952,0,2159,5480,1.012959614225437,2161 +matmul,8x12x28xf64,linalg_xdsl,3268,5435,5432,0.0,0,2688,3138,0,0.9602203182374541,0.9993630573248408,3140,0,0,0.9608323133414932,0,0,4.435028248587571,4.435028248587571,1,0.0,708,0.8261376896149358,149,0,0,0.045593635250917995,0,2168,5439,1.0064259485924112,2170 matmul,8x12x32xf64,baseline,17245,19386,19383,0.0,0,2816,3073,0,0.1781965787184691,0.324395650797002,9473,0,0,0.5493186430849522,0,0,1.0,1.0,1,3.4285714285714284,9473,0.8879827521559805,1195,24,7,0.06929544795592925,7,2142,19390,0.6186140910408814,2144 matmul,8x12x32xf64,linalg_xdsl,3782,5927,5924,0.0,0,3072,3586,0,0.9481755684822845,0.9994425863991081,3588,0,0,0.9487043892120571,0,0,4.291866028708134,4.291866028708134,1,0.0,836,0.7733580018501388,245,0,0,0.06478053939714437,0,2146,5931,1.0134849286092016,2148 matmul,8x12x36xf64,baseline,19387,21539,21536,0.0,0,3168,3457,0,0.17831536596688502,0.3243877263770292,10657,0,0,0.549698251405581,0,0,1.0,1.0,1,3.4285714285714284,10657,0.8895659432387312,1323,24,7,0.0682416051993604,7,2153,21543,0.6179398566049414,2155 -matmul,8x12x36xf64,linalg_xdsl,4245,6404,6401,0.0,0,3456,4034,0,0.9502944640753828,0.9995044598612488,4036,0,0,0.9507656065959953,0,0,4.293617021276595,4.293617021276596,1,0.0,940,0.7775020678246485,269,0,0,0.06336866902237927,0,2160,6408,1.0141342756183747,2162 +matmul,8x12x36xf64,linalg_xdsl,4203,6411,6408,0.0,0,3456,4034,0,0.9597906257435166,0.9995044598612488,4036,0,0,0.9602664763264335,0,0,4.406113537117904,4.406113537117904,1,0.0,916,0.8230008984725966,197,0,0,0.04687128241732096,0,2209,6415,1.0071377587437544,2211 matmul,8x12x40xf64,baseline,21518,23703,23700,0.0,0,3520,3841,0,0.178501719490659,0.3243813867072038,11841,0,0,0.5502834835951297,0,0,1.0,1.0,1,4.166666666666667,11841,0.8915073031170004,1441,25,6,0.06696719025931779,6,2186,23707,0.6172506738544474,2188 -matmul,8x12x40xf64,linalg_xdsl,4709,6878,6875,0.0,0,3840,4482,0,0.9517944361860268,0.9995539696699376,4484,0,0,0.9522191548099385,0,0,4.295019157088123,4.295019157088123,1,0.0,1044,0.7808526551982049,293,0,0,0.062221278403057974,0,2170,6882,1.0144404332129964,2172 +matmul,8x12x40xf64,linalg_xdsl,4677,6848,6845,0.0,0,3840,4482,0,0.9583066067992303,0.9995539696699376,4484,0,0,0.9587342313448792,0,0,4.361867704280155,4.361867704280155,1,0.0,1028,0.8075412411626081,245,0,0,0.05238400684199273,0,2172,6852,1.011118238186872,2174 matmul,8x12x44xf64,baseline,23656,25824,25821,0.0,0,3872,4225,0,0.1786016232668245,0.32437619961612285,13025,0,0,0.5506002705444707,0,0,1.0,1.0,1,3.7142857142857144,13025,0.8712957388454077,1924,26,7,0.08133243151843084,7,2169,25828,0.6319327020629015,2171 matmul,8x12x44xf64,linalg_xdsl,5173,7357,7354,0.0,0,4224,4930,0,0.9530253237966364,0.9995944849959448,4932,0,0,0.9534119466460468,0,0,4.29616724738676,4.29616724738676,1,0.0,1148,0.783617747440273,317,0,0,0.06127972163154843,0,2185,7361,1.0146916682775953,2187 matmul,8x12x48xf64,baseline,25800,27978,27975,0.0,0,4224,4609,0,0.17864341085271318,0.32437187697937925,14209,0,0,0.5507364341085271,0,0,1.0,1.0,1,3.7142857142857144,14209,0.8720923095808015,2084,26,7,0.08077519379844961,7,2179,27982,0.6315116279069768,2181 -matmul,8x12x48xf64,linalg_xdsl,5637,7831,7828,0.0,0,4608,5378,0,0.9540535745964165,0.9996282527881041,5380,0,0,0.9544083732481816,0,0,4.297124600638978,4.297124600638978,1,0.0,1252,0.7859384808537351,341,0,0,0.060493170125953524,0,2195,7835,1.014901543374135,2197 +matmul,8x12x48xf64,linalg_xdsl,5579,7822,7819,0.0,0,4608,5378,0,0.9639720379996415,0.9996282527881041,5380,0,0,0.9643305251837246,0,0,4.409836065573771,4.409836065573771,1,0.0,1220,0.8327645051194539,245,0,0,0.043914680050188205,0,2244,7826,1.0082452052339128,2246 matmul,8x12x4xf64,baseline,2164,4271,4268,0.0,0,352,385,0,0.1779112754158965,0.32489451476793246,1185,0,0,0.5475970425138632,0,0,1.0,1.0,1,0.0,1185,0.966557911908646,41,0,0,0.018946395563770795,0,2108,4275,0.566543438077634,2110 matmul,8x12x4xf64,linalg_xdsl,520,2619,2616,0.0,0,384,450,0,0.8653846153846154,0.995575221238938,452,0,0,0.8692307692307693,0,0,4.185185185185185,4.185185185185185,1,0.0,108,0.631578947368421,63,0,0,0.12115384615384615,0,2100,2623,0.9903846153846154,2102 matmul,8x12x52xf64,baseline,27944,30132,30129,0.0,0,4576,4993,0,0.178678786143716,0.32436821932047033,15393,0,0,0.5508517034068137,0,0,1.0,1.0,1,3.7142857142857144,15393,0.8727674774621534,2244,26,7,0.08030346407099914,7,2189,30136,0.6311551674778129,2191 matmul,8x12x52xf64,linalg_xdsl,6101,8305,8302,0.0,0,4992,5826,0,0.9549254220619571,0.9996568291008923,5828,0,0,0.9552532371742337,0,0,4.297935103244837,4.297935103244837,1,0.0,1356,0.7879140034863451,365,0,0,0.05982625799049336,0,2205,8309,1.015079495164727,2207 matmul,8x12x56xf64,baseline,30088,32294,32291,0.0,0,4928,5377,0,0.17870911991491625,0.32436508415274173,16577,0,0,0.5509505450678012,0,0,1.0,1.0,1,3.7142857142857144,16577,0.873347031241768,2404,26,7,0.07989896304174422,7,2207,32298,0.6308495081095454,2209 -matmul,8x12x56xf64,linalg_xdsl,6566,8800,8797,0.0,0,5376,6274,0,0.9555284800487359,0.9996813256851498,6276,0,0,0.9558330795004569,0,0,4.298630136986301,4.298630136986302,1,0.0,1460,0.7896160086533262,389,0,0,0.05924459335973195,0,2235,8804,1.015077672860189,2237 +matmul,8x12x56xf64,linalg_xdsl,6468,8710,8707,0.0,0,5376,6274,0,0.9700061842918986,0.9996813256851498,6276,0,0,0.9703153988868275,0,0,4.444759206798867,4.444759206798867,1,0.0,1412,0.852142426071213,245,0,0,0.03787878787878788,0,2243,8714,1.0081941867656155,2245 matmul,8x12x60xf64,baseline,32232,34448,34445,0.0,0,5280,5761,0,0.17873541821792008,0.324362366983841,17761,0,0,0.5510362372797221,0,0,1.0,1.0,1,3.7142857142857144,17761,0.873849938499385,2564,26,7,0.07954827500620501,7,2217,34452,0.630584512285927,2219 -matmul,8x12x60xf64,linalg_xdsl,7030,9274,9271,0.0,0,5760,6722,0,0.9561877667140825,0.9997025580011898,6724,0,0,0.9564722617354197,0,0,4.299232736572891,4.29923273657289,1,0.0,1564,0.7910976226605969,413,0,0,0.05874822190611664,0,2245,9278,1.0152204836415364,2247 +matmul,8x12x60xf64,linalg_xdsl,6949,9232,9229,0.0,0,5760,6722,0,0.9673334292703987,0.9997025580011898,6724,0,0,0.9676212404662541,0,0,4.412073490813648,4.412073490813648,1,0.0,1524,0.8387451843698404,293,0,0,0.0421643401928335,0,2284,9236,1.0097855806590876,2286 matmul,8x12x64xf64,baseline,34376,36594,36591,0.0,0,5632,6145,0,0.178758436118222,0.32435998944312483,18945,0,0,0.5511112404002793,0,0,1.0,1.0,1,3.7142857142857144,18945,0.874290461027274,2724,26,7,0.07924133116127531,7,2219,36598,0.6303525715615546,2221 matmul,8x12x64xf64,linalg_xdsl,7493,9727,9724,0.0,0,6144,7170,0,0.9568931002268785,0.9997211377579476,7172,0,0,0.9571600160149473,0,0,4.299760191846524,4.299760191846523,1,0.0,1668,0.7923990498812351,437,0,0,0.05832109969304684,0,2235,9731,1.0154811157079942,2237 matmul,8x12x8xf64,baseline,4356,6461,6458,0.0,0,704,769,0,0.17653810835629016,0.32460953989024904,2369,0,0,0.5438475665748393,0,0,1.0,1.0,1,4.166666666666667,2369,0.8503230437903805,417,25,6,0.09573002754820936,6,2106,6465,0.6395775941230487,2108 matmul,8x12x8xf64,linalg_xdsl,1004,3107,3104,0.0,0,768,898,0,0.8944223107569721,0.9977777777777778,900,0,0,0.896414342629482,0,0,4.245283018867924,4.245283018867925,1,0.0,212,0.6816720257234726,99,0,0,0.09860557768924302,0,2104,3111,0.9950199203187251,2106 matmul,8x16x12xf64,baseline,8528,10636,10633,0.0,0,1440,1537,0,0.18022983114446528,0.32667375132837406,4705,0,0,0.5517120075046904,0,0,1.0,1.0,1,3.7777777777777777,4705,0.8899186684320031,582,34,9,0.06824577861163227,9,2109,10640,0.6199577861163227,2111 -matmul,8x16x12xf64,linalg_xdsl,1852,3953,3950,0.0,0,1536,1730,0,0.9341252699784017,0.9988452655889145,1732,0,0,0.9352051835853131,0,0,5.481012658227848,5.481012658227848,1,0.0,316,0.7198177676537585,123,0,0,0.066414686825054,0,2102,3957,1.0016198704103672,2104 +matmul,8x16x12xf64,linalg_xdsl,1827,3976,3973,0.0,0,1536,1730,0,0.9469074986316366,0.9988452655889145,1732,0,0,0.9480021893814997,0,0,5.623376623376624,5.623376623376624,1,0.0,308,0.7567567567567568,99,0,0,0.054187192118226604,0,2150,3980,1.0021893814997263,2152 matmul,8x16x16xf64,baseline,11344,13462,13459,0.0,0,1920,2049,0,0.1806241184767278,0.3266379722620756,6273,0,0,0.5529795486600846,0,0,1.0,1.0,1,3.7777777777777777,6273,0.8983245023628813,710,34,9,0.06258815232722144,9,2119,13466,0.6155677009873061,2121 matmul,8x16x16xf64,linalg_xdsl,2444,4560,4557,0.0,0,2048,2306,0,0.9435351882160393,0.9991334488734835,2308,0,0,0.9443535188216039,0,0,5.495238095238095,5.495238095238095,1,0.0,420,0.7407407407407407,147,0,0,0.060147299509001634,0,2117,4564,1.0045008183306054,2119 matmul,8x16x20xf64,baseline,14160,16313,16310,0.0,0,2400,2561,0,0.18086158192090396,0.3266165029970667,7841,0,0,0.5537429378531074,0,0,1.0,1.0,1,3.7777777777777777,7841,0.9034450973614472,838,34,9,0.05918079096045198,9,2154,16317,0.6129237288135594,2156 -matmul,8x16x20xf64,linalg_xdsl,3030,5183,5180,0.0,0,2560,2882,0,0.9511551155115512,0.9993065187239945,2884,0,0,0.9518151815181518,0,0,5.5038167938931295,5.5038167938931295,1,0.0,524,0.7517934002869441,173,0,0,0.057095709570957096,0,2154,5187,1.008910891089109,2156 +matmul,8x16x20xf64,linalg_xdsl,3013,5187,5184,0.0,0,2560,2882,0,0.9565217391304348,0.9993065187239945,2884,0,0,0.9571855293727182,0,0,5.589147286821706,5.589147286821706,1,0.0,516,0.7759398496240602,149,0,0,0.04945237305011616,0,2175,5191,1.0066379024228342,2177 matmul,8x16x24xf64,baseline,16992,19138,19135,0.0,0,2880,3073,0,0.18084981167608286,0.32660218939313423,9409,0,0,0.5537311676082862,0,0,1.0,1.0,1,3.3,9409,0.9060182956186807,976,33,10,0.05743879472693032,10,2147,19142,0.6111699623352166,2149 -matmul,8x16x24xf64,linalg_xdsl,3622,5765,5762,0.0,0,3072,3458,0,0.9547211485367201,0.999421965317919,3460,0,0,0.9552733296521259,0,0,5.509554140127389,5.509554140127388,1,0.0,628,0.7612121212121212,197,0,0,0.05438983986747653,0,2144,5769,1.0096631695196023,2146 +matmul,8x16x24xf64,linalg_xdsl,3595,5788,5785,0.0,0,3072,3458,0,0.9618915159944367,0.999421965317919,3460,0,0,0.9624478442280946,0,0,5.65359477124183,5.65359477124183,1,0.0,612,0.8042049934296978,149,0,0,0.04144645340751043,0,2194,5792,1.0038942976356051,2196 matmul,8x16x28xf64,baseline,19808,22007,22004,0.0,0,3360,3585,0,0.18098747980613894,0.32659196501776444,10977,0,0,0.5541700323101777,0,0,1.0,1.0,1,3.3,10977,0.9086168363546064,1104,33,10,0.05573505654281099,10,2200,22011,0.6099050888529887,2202 -matmul,8x16x28xf64,linalg_xdsl,4214,6393,6390,0.0,0,3584,4034,0,0.9572852396772663,0.9995044598612488,4036,0,0,0.9577598481252966,0,0,5.513661202185792,5.5136612021857925,1,0.0,732,0.7681007345225603,221,0,0,0.05244423350735643,0,2180,6397,1.010204081632653,2182 +matmul,8x16x28xf64,linalg_xdsl,4164,6350,6347,0.0,0,3584,4034,0,0.9687800192122958,0.9995044598612488,4036,0,0,0.9692603266090298,0,0,5.700564971751413,5.700564971751413,1,0.0,708,0.8261376896149358,149,0,0,0.035782901056676274,0,2187,6354,1.0050432276657062,2189 matmul,8x16x32xf64,baseline,22609,24785,24782,0.0,0,3840,4097,0,0.1812110221593171,0.32658429653248305,12545,0,0,0.5548675306293954,0,0,1.0,1.0,1,3.3,12545,0.8944103807215171,1481,33,10,0.06550488743420761,10,2177,24789,0.620372418063603,2179 matmul,8x16x32xf64,linalg_xdsl,4805,6971,6968,0.0,0,4096,4610,0,0.959417273673257,0.9995663486556808,4612,0,0,0.9598335067637878,0,0,5.516746411483254,5.516746411483253,1,0.0,836,0.7733580018501388,245,0,0,0.05098855359001041,0,2167,6975,1.010822060353798,2169 matmul,8x16x36xf64,baseline,25425,27649,27646,0.0,0,4320,4609,0,0.18127826941986233,0.32657833203429465,14113,0,0,0.5550835791543756,0,0,1.0,1.0,1,3.3,14113,0.8958359781642757,1641,33,10,0.06454277286135693,10,2225,27653,0.6196263520157325,2227 -matmul,8x16x36xf64,linalg_xdsl,5397,7581,7578,0.0,0,4608,5186,0,0.9609042060403928,0.9996144949884348,5188,0,0,0.9612747822864555,0,0,5.519148936170213,5.519148936170213,1,0.0,940,0.7775020678246485,269,0,0,0.04984250509542339,0,2185,7585,1.0111172873818788,2187 +matmul,8x16x36xf64,linalg_xdsl,5355,7588,7585,0.0,0,4608,5186,0,0.9684407096171802,0.9996144949884348,5188,0,0,0.9688141923436041,0,0,5.663755458515284,5.663755458515284,1,0.0,916,0.8230008984725966,197,0,0,0.036788048552754436,0,2234,7592,1.0056022408963585,2236 matmul,8x16x40xf64,baseline,28255,30468,30465,0.0,0,4800,5121,0,0.18124225800743232,0.32657356035967094,15681,0,0,0.5549814192178375,0,0,1.0,1.0,1,3.5833333333333335,15681,0.8805592991913747,2127,43,12,0.07527871173243673,12,2214,30472,0.6302601309502742,2216 -matmul,8x16x40xf64,linalg_xdsl,5990,8204,8201,0.0,0,5120,5762,0,0.9619365609348914,0.9996530187369882,5764,0,0,0.9622704507512521,0,0,5.521072796934866,5.521072796934866,1,0.0,1044,0.7808526551982049,293,0,0,0.048914858096828044,0,2215,8208,1.01118530884808,2217 +matmul,8x16x40xf64,linalg_xdsl,5957,8191,8188,0.0,0,5120,5762,0,0.9672654020480107,0.9996530187369882,5764,0,0,0.967601141514185,0,0,5.607003891050583,5.607003891050583,1,0.0,1028,0.8075412411626081,245,0,0,0.041128084606345476,0,2235,8195,1.0087292261205305,2237 matmul,8x16x44xf64,baseline,31072,33314,33311,0.0,0,5280,5633,0,0.18128861997940268,0.32656965621195433,17249,0,0,0.5551300205973223,0,0,1.0,1.0,1,3.5833333333333335,17249,0.8814451428279422,2320,43,12,0.07466529351184346,12,2243,33318,0.6297953141091658,2245 matmul,8x16x44xf64,linalg_xdsl,6582,8811,8808,0.0,0,5632,6338,0,0.9629292008508052,0.9996845425867508,6340,0,0,0.9632330598602249,0,0,5.522648083623694,5.522648083623693,1,0.0,1148,0.783617747440273,317,0,0,0.04816165299301124,0,2230,8815,1.0113947128532361,2232 matmul,8x16x48xf64,baseline,33888,36140,36137,0.0,0,5760,6145,0,0.18133262511803588,0.32656640272094384,18817,0,0,0.5552703021718602,0,0,1.0,1.0,1,3.5833333333333335,18817,0.8822260771719256,2512,43,12,0.07412653446647781,12,2253,36144,0.629396836638338,2255 -matmul,8x16x48xf64,linalg_xdsl,7174,9413,9410,0.0,0,6144,6914,0,0.963758015054363,0.9997108155002892,6916,0,0,0.9640367995539448,0,0,5.523961661341853,5.523961661341853,1,0.0,1252,0.7859384808537351,341,0,0,0.04753275717870086,0,2240,9417,1.0115695567326457,2242 +matmul,8x16x48xf64,linalg_xdsl,7109,9387,9384,0.0,0,6144,6914,0,0.9725699817133211,0.9997108155002892,6916,0,0,0.9728513152342102,0,0,5.668852459016393,5.668852459016393,1,0.0,1220,0.8327645051194539,245,0,0,0.03446335630890421,0,2279,9391,1.0073146715431145,2281 matmul,8x16x4xf64,baseline,2836,4948,4945,0.0,0,480,513,0,0.1808885754583921,0.32695984703632885,1569,0,0,0.5532440056417489,0,0,1.0,1.0,1,0.0,1569,0.9745341614906833,41,0,0,0.014456981664315938,0,2113,4952,0.5677009873060649,2115 matmul,8x16x4xf64,linalg_xdsl,648,2752,2749,0.0,0,512,578,0,0.8919753086419753,0.996551724137931,580,0,0,0.8950617283950617,0,0,5.37037037037037,5.37037037037037,1,0.0,108,0.631578947368421,63,0,0,0.09722222222222222,0,2105,2756,0.9922839506172839,2107 matmul,8x16x52xf64,baseline,36699,38953,38950,0.0,0,6240,6657,0,0.1813945884084035,0.32656364974245766,20385,0,0,0.5554647265593068,0,0,1.0,1.0,1,3.5833333333333335,20385,0.8671516079632465,3123,43,12,0.08509768658546554,12,2255,38957,0.6405624131447724,2257 matmul,8x16x52xf64,linalg_xdsl,7766,10020,10017,0.0,0,6656,7490,0,0.9644604687097605,0.9997330485851575,7492,0,0,0.964718001545197,0,0,5.525073746312684,5.525073746312684,1,0.0,1356,0.7879140034863451,365,0,0,0.04699974246716456,0,2255,10024,1.0117177440123617,2257 matmul,8x16x56xf64,baseline,39515,41755,41752,0.0,0,6720,7169,0,0.18142477540174617,0.32656129002869766,21953,0,0,0.5555611792990004,0,0,1.0,1.0,1,3.5833333333333335,21953,0.867707509881423,3347,43,12,0.08470201189421739,12,2241,41759,0.6402631911932177,2243 -matmul,8x16x56xf64,linalg_xdsl,8358,10598,10595,0.0,0,7168,8066,0,0.9650634122995932,0.9997521070897373,8068,0,0,0.9653027039961714,0,0,5.526027397260274,5.526027397260274,1,0.0,1460,0.7896160086533262,389,0,0,0.04654223498444604,0,2241,10602,1.0118449389806174,2243 +matmul,8x16x56xf64,linalg_xdsl,8260,10524,10521,0.0,0,7168,8066,0,0.9765133171912833,0.9997521070897373,8068,0,0,0.9767554479418886,0,0,5.713881019830028,5.713881019830028,1,0.0,1412,0.852142426071213,245,0,0,0.029661016949152543,0,2265,10528,1.0064164648910412,2267 matmul,8x16x60xf64,baseline,42331,44610,44607,0.0,0,7200,7681,0,0.1814509461151402,0.3265592449300625,23521,0,0,0.5556447993196475,0,0,1.0,1.0,1,3.5833333333333335,23521,0.8681898715487967,3571,43,12,0.08435898041624341,12,2280,44614,0.640003779735891,2282 -matmul,8x16x60xf64,linalg_xdsl,8950,11229,11226,0.0,0,7680,8642,0,0.965586592178771,0.9997686256362796,8644,0,0,0.9658100558659218,0,0,5.526854219948849,5.5268542199488495,1,0.0,1564,0.7910976226605969,413,0,0,0.046145251396648046,0,2280,11233,1.01195530726257,2282 +matmul,8x16x60xf64,linalg_xdsl,8869,11187,11184,0.0,0,7680,8642,0,0.9744052317059421,0.9997686256362796,8644,0,0,0.9746307362724095,0,0,5.671916010498688,5.671916010498688,1,0.0,1524,0.8387451843698404,293,0,0,0.033036418987484495,0,2319,11191,1.007667155259894,2321 matmul,8x16x64xf64,baseline,45149,47425,47422,0.0,0,7680,8193,0,0.18146581319630556,0.3265574554585675,25089,0,0,0.5556933708387782,0,0,1.0,1.0,1,3.5384615384615383,25089,0.8533963740263274,4310,46,13,0.09546169350373208,13,2277,47429,0.6511550643425104,2279 matmul,8x16x64xf64,linalg_xdsl,9541,11807,11804,0.0,0,8192,9218,0,0.9661461062781679,0.9997830802603037,9220,0,0,0.9663557279111205,0,0,5.5275779376498795,5.52757793764988,1,0.0,1668,0.7923990498812351,437,0,0,0.045802326800125776,0,2267,11811,1.0121580547112463,2269 matmul,8x16x8xf64,baseline,5718,7803,7800,0.0,0,960,1025,0,0.17925848198670863,0.326745298055467,3137,0,0,0.5486183980412732,0,0,1.0,1.0,1,3.7777777777777777,3137,0.873572820941242,454,34,9,0.07939839104582022,9,2086,7807,0.6280167890870935,2088 matmul,8x16x8xf64,linalg_xdsl,1260,3368,3365,0.0,0,1024,1154,0,0.9158730158730158,0.9982698961937716,1156,0,0,0.9174603174603174,0,0,5.452830188679246,5.452830188679245,1,0.0,212,0.6816720257234726,99,0,0,0.07857142857142857,0,2109,3372,0.996031746031746,2111 matmul,8x20x12xf64,baseline,10622,12760,12757,0.0,0,1824,1921,0,0.18085106382978725,0.32798360935632576,5857,0,0,0.5514027490114856,0,0,1.0,1.0,1,3.5384615384615383,5857,0.9028826884538307,630,46,13,0.05931086424402184,13,2139,12764,0.6107136132555074,2141 -matmul,8x20x12xf64,linalg_xdsl,2236,4347,4344,0.0,0,1920,2114,0,0.945438282647585,0.999054820415879,2116,0,0,0.9463327370304114,0,0,6.69620253164557,6.69620253164557,1,0.0,316,0.7198177676537585,123,0,0,0.055008944543828264,0,2112,4351,1.0013416815742398,2114 +matmul,8x20x12xf64,linalg_xdsl,2211,4370,4367,0.0,0,1920,2114,0,0.9561284486657621,0.999054820415879,2116,0,0,0.9570330167345092,0,0,6.87012987012987,6.87012987012987,1,0.0,308,0.7567567567567568,99,0,0,0.04477611940298507,0,2160,4374,1.0018091361374943,2162 matmul,8x20x16xf64,baseline,14138,16293,16290,0.0,0,2432,2561,0,0.18114301881454237,0.32795492380586505,7809,0,0,0.5523412080916679,0,0,1.0,1.0,1,3.230769230769231,7809,0.9099277557678863,773,42,13,0.05467534304710709,13,2156,16297,0.607016551138775,2158 matmul,8x20x16xf64,linalg_xdsl,2950,5103,5100,0.0,0,2560,2818,0,0.9552542372881356,0.999290780141844,2820,0,0,0.9559322033898305,0,0,6.714285714285714,6.714285714285714,1,0.0,420,0.7381370826010545,149,0,0,0.05050847457627119,0,2154,5107,1.0064406779661017,2156 matmul,8x20x20xf64,baseline,17589,19766,19763,0.0,0,3040,3201,0,0.18198874296435272,0.3279377113000717,9761,0,0,0.5549491159247257,0,0,1.0,1.0,1,3.5384615384615383,9761,0.9174734467525143,878,46,13,0.04991756211268406,13,2178,19770,0.6048666780374098,2180 -matmul,8x20x20xf64,linalg_xdsl,3669,5818,5815,0.0,0,3200,3522,0,0.9599345870809485,0.9994324631101021,3524,0,0,0.9604796947397111,0,0,6.7251908396946565,6.7251908396946565,1,0.0,524,0.7517934002869441,173,0,0,0.047151812482965384,0,2150,5822,1.0076315072226765,2152 +matmul,8x20x20xf64,linalg_xdsl,3653,5804,5801,0.0,0,3200,3522,0,0.9641390637831919,0.9994324631101021,3524,0,0,0.9646865589926088,0,0,6.829457364341085,6.829457364341085,1,0.0,516,0.7759398496240602,149,0,0,0.04078839310156036,0,2152,5808,1.0054749520941693,2154 matmul,8x20x24xf64,baseline,21086,23277,23274,0.0,0,3648,3841,0,0.1821587783363369,0.327926235806369,11713,0,0,0.5554870530209618,0,0,1.0,1.0,1,3.5384615384615383,11713,0.9203268641470889,1014,46,13,0.04808877928483354,13,2192,23281,0.6035758323057954,2194 -matmul,8x20x24xf64,linalg_xdsl,4390,6574,6571,0.0,0,3840,4226,0,0.9626423690205012,0.9995269631031221,4228,0,0,0.9630979498861048,0,0,6.732484076433121,6.732484076433121,1,0.0,628,0.7612121212121212,197,0,0,0.044874715261959,0,2185,6578,1.0079726651480638,2187 +matmul,8x20x24xf64,linalg_xdsl,4357,6579,6576,0.0,0,3840,4226,0,0.9699334404406702,0.9995269631031221,4228,0,0,0.9703924718843241,0,0,6.908496732026144,6.908496732026144,1,0.0,612,0.8042049934296978,149,0,0,0.03419784255221483,0,2223,6583,1.004590314436539,2225 matmul,8x20x28xf64,baseline,24591,26788,26785,0.0,0,4256,4481,0,0.18222113781464763,0.3279180387852177,13665,0,0,0.555691106502379,0,0,1.0,1.0,1,3.230769230769231,13665,0.9086375423897866,1374,42,13,0.05587410028059046,13,2198,26792,0.6115652067829694,2200 -matmul,8x20x28xf64,linalg_xdsl,5110,7309,7306,0.0,0,4480,4930,0,0.9647749510763209,0.9995944849959448,4932,0,0,0.9651663405088062,0,0,6.7377049180327875,6.737704918032787,1,0.0,732,0.7681007345225603,221,0,0,0.04324853228962818,0,2200,7313,1.0084148727984343,2202 +matmul,8x20x28xf64,linalg_xdsl,5060,7266,7263,0.0,0,4480,4930,0,0.974308300395257,0.9995944849959448,4932,0,0,0.974703557312253,0,0,6.966101694915254,6.966101694915254,1,0.0,708,0.8261376896149358,149,0,0,0.029446640316205534,0,2207,7270,1.0041501976284586,2209 matmul,8x20x32xf64,baseline,28128,30321,30318,0.0,0,4864,5121,0,0.18206058020477817,0.3279118908881347,15617,0,0,0.5552118885096701,0,0,1.0,1.0,1,3.7241379310344827,15617,0.895778364116095,1817,108,29,0.06459755403868032,22,2194,30325,0.6198094425483504,2196 matmul,8x20x32xf64,linalg_xdsl,5830,8044,8041,0.0,0,5120,5634,0,0.9663807890222984,0.9996451383960255,5636,0,0,0.9667238421955403,0,0,6.741626794258373,6.741626794258373,1,0.0,836,0.7733580018501388,245,0,0,0.04202401372212693,0,2215,8048,1.0087478559176672,2217 matmul,8x20x36xf64,baseline,31617,33861,33858,0.0,0,5472,5761,0,0.1822121010848594,0.3279071091126416,17569,0,0,0.5556820697725907,0,0,1.0,1.0,1,3.7241379310344827,17569,0.897338985647888,2010,108,29,0.06357339406015751,22,2245,33865,0.6192554638327482,2247 -matmul,8x20x36xf64,linalg_xdsl,6550,8774,8771,0.0,0,5760,6338,0,0.9676335877862595,0.9996845425867508,6340,0,0,0.9679389312977099,0,0,6.74468085106383,6.74468085106383,1,0.0,940,0.7775020678246485,269,0,0,0.04106870229007634,0,2225,8778,1.0090076335877862,2227 +matmul,8x20x36xf64,linalg_xdsl,6501,8764,8761,0.0,0,5760,6338,0,0.9749269343177973,0.9996845425867508,6340,0,0,0.975234579295493,0,0,6.921397379912664,6.921397379912664,1,0.0,916,0.8230008984725966,197,0,0,0.030303030303030304,0,2264,8768,1.0055376095985233,2266 matmul,8x20x40xf64,baseline,35102,37310,37307,0.0,0,6080,6401,0,0.18235428180730442,0.327903283643256,19521,0,0,0.5561221582815794,0,0,1.0,1.0,1,3.142857142857143,19521,0.912537397157816,1871,66,21,0.05330180616489089,14,2209,37314,0.6094239644464703,2211 -matmul,8x20x40xf64,linalg_xdsl,7270,9509,9506,0.0,0,6400,7042,0,0.9686382393397525,0.9997160704145373,7044,0,0,0.9689133425034387,0,0,6.747126436781609,6.747126436781609,1,0.0,1044,0.7808526551982049,293,0,0,0.04030261348005502,0,2240,9513,1.0092159559834937,2242 +matmul,8x20x40xf64,linalg_xdsl,7237,9496,9493,0.0,0,6400,7042,0,0.9730551333425452,0.9997160704145373,7044,0,0,0.9733314909492884,0,0,6.852140077821011,6.852140077821011,1,0.0,1028,0.8075412411626081,245,0,0,0.03385380682603289,0,2260,9500,1.0071852977753213,2262 matmul,8x20x44xf64,baseline,38598,40873,40870,0.0,0,6688,7041,0,0.18241877817503496,0.3279001536813673,21473,0,0,0.5563241618736722,0,0,1.0,1.0,1,3.7241379310344827,21473,0.8865081331021386,2749,108,29,0.07122130680346132,22,2276,40877,0.6275454686771335,2278 matmul,8x20x44xf64,linalg_xdsl,7990,10244,10241,0.0,0,7040,7746,0,0.9694618272841051,0.9997418688693857,7748,0,0,0.969712140175219,0,0,6.7491289198606275,6.7491289198606275,1,0.0,1148,0.783617747440273,317,0,0,0.03967459324155194,0,2255,10248,1.009386733416771,2257 matmul,8x20x48xf64,baseline,42086,44376,44373,0.0,0,7296,7681,0,0.18250724706553248,0.327897545357524,23425,0,0,0.5565983937651475,0,0,1.0,1.0,1,3.7241379310344827,23425,0.8873778316539132,2973,108,29,0.0706410682887421,22,2291,44380,0.6272394620538896,2293 -matmul,8x20x48xf64,linalg_xdsl,8710,10979,10976,0.0,0,7680,8450,0,0.9701492537313433,0.9997633696166588,8452,0,0,0.9703788748564868,0,0,6.7507987220447285,6.7507987220447285,1,0.0,1252,0.7859384808537351,341,0,0,0.039150401836969,0,2270,10983,1.0095292766934558,2272 +matmul,8x20x48xf64,linalg_xdsl,8645,10953,10950,0.0,0,7680,8450,0,0.9774436090225563,0.9997633696166588,8452,0,0,0.9776749566223251,0,0,6.927868852459016,6.927868852459016,1,0.0,1220,0.8327645051194539,245,0,0,0.02834008097165992,0,2309,10957,1.006015037593985,2311 matmul,8x20x4xf64,baseline,3646,5763,5760,0.0,0,608,641,0,0.17580910586944598,0.32821300563236044,1953,0,0,0.5356555128908392,0,0,1.0,1.0,1,3.5384615384615383,1953,0.8392780403953588,374,46,13,0.10257816785518377,13,2118,5767,0.638233680746023,2120 matmul,8x20x4xf64,linalg_xdsl,776,2885,2882,0.0,0,640,706,0,0.9097938144329897,0.9971751412429378,708,0,0,0.9123711340206185,0,0,6.555555555555556,6.555555555555555,1,0.0,108,0.631578947368421,63,0,0,0.08118556701030928,0,2110,2889,0.9935567010309279,2112 matmul,8x20x52xf64,baseline,45699,47996,47993,0.0,0,7904,8321,0,0.18208275892251471,0.32789533829845924,25377,0,0,0.5553075559640255,0,0,1.0,1.0,1,3.0369515011547343,25377,0.8270434102463825,5307,2630,866,0.1161294557867787,43,2298,48000,0.6714370117508042,2300 matmul,8x20x52xf64,linalg_xdsl,9430,11714,11711,0.0,0,8320,9154,0,0.9707317073170731,0.9997815640017474,9156,0,0,0.9709437963944857,0,0,6.7522123893805315,6.752212389380531,1,0.0,1356,0.7879140034863451,365,0,0,0.03870625662778367,0,2285,11718,1.0096500530222694,2287 matmul,8x20x56xf64,baseline,49187,51461,51458,0.0,0,8512,8961,0,0.18218228393681257,0.3278934465220096,27329,0,0,0.5556142883282168,0,0,1.0,1.0,1,3.0344086021505374,27329,0.8276499091459721,5691,2822,930,0.11570130318986724,43,2275,51465,0.6713155915180841,2277 -matmul,8x20x56xf64,linalg_xdsl,10150,12447,12444,0.0,0,8960,9858,0,0.9712315270935961,0.9997971602434077,9860,0,0,0.9714285714285714,0,0,6.7534246575342465,6.7534246575342465,1,0.0,1460,0.7896160086533262,389,0,0,0.03832512315270936,0,2298,12451,1.0097536945812808,2300 +matmul,8x20x56xf64,linalg_xdsl,10059,12361,12358,0.0,0,8960,9858,0,0.9800178944229049,0.9997971602434077,9860,0,0,0.98021672134407,0,0,6.98300283286119,6.98300283286119,1,0.0,1412,0.852142426071213,245,0,0,0.024356297842727904,0,2303,12365,1.0045730191867979,2305 matmul,8x20x60xf64,baseline,52675,54959,54956,0.0,0,9120,9601,0,0.1822686283815852,0.32789180697380554,29281,0,0,0.5558803986710964,0,0,1.0,1.0,1,3.0321931589537225,29281,0.8281762642832899,6075,3014,994,0.11532985287138112,43,2285,54963,0.6712102515424775,2287 -matmul,8x20x60xf64,linalg_xdsl,10870,13182,13179,0.0,0,9600,10562,0,0.9716651333946642,0.9998106777735706,10564,0,0,0.9718491260349587,0,0,6.754475703324808,6.754475703324808,1,0.0,1564,0.7910976226605969,413,0,0,0.03799448022079117,0,2313,13186,1.0098436062557499,2315 +matmul,8x20x60xf64,linalg_xdsl,10789,13125,13122,0.0,0,9600,10562,0,0.9789600519047178,0.9998106777735706,10564,0,0,0.9791454258967467,0,0,6.9317585301837275,6.9317585301837275,1,0.0,1524,0.8387451843698404,293,0,0,0.027157289832236538,0,2337,13129,1.0063027157289832,2339 matmul,8x20x64xf64,baseline,56211,58539,58536,0.0,0,9728,10241,0,0.18218853960968492,0.32789037236256524,31233,0,0,0.555638576079415,0,0,1.0,1.0,1,3.261996161228407,31233,0.7854789628549154,8530,6798,2084,0.1517496575403391,61,2329,58543,0.7073882336197541,2331 matmul,8x20x64xf64,linalg_xdsl,11589,13898,13895,0.0,0,10240,11266,0,0.9721287427733195,0.9998225062122825,11268,0,0,0.9723013202174475,0,0,6.755395683453238,6.755395683453237,1,0.0,1668,0.7923990498812351,437,0,0,0.03770817154197946,0,2310,13902,1.010009491759427,2312 matmul,8x20x8xf64,baseline,7134,9283,9280,0.0,0,1216,1281,0,0.17956265769554247,0.32804097311139563,3905,0,0,0.5473787496495655,0,0,1.0,1.0,1,3.5384615384615383,3905,0.886090310869072,502,46,13,0.07036725539669189,13,2150,9287,0.6177460050462573,2152 matmul,8x20x8xf64,linalg_xdsl,1516,3634,3631,0.0,0,1280,1410,0,0.9300791556728232,0.9985835694050992,1412,0,0,0.9313984168865436,0,0,6.660377358490566,6.660377358490566,1,0.0,212,0.6816720257234726,99,0,0,0.06530343007915568,0,2119,3638,0.9967018469656992,2121 matmul,8x24x12xf64,baseline,12749,14871,14868,0.0,0,2208,2305,0,0.18079849399952938,0.3288628905692681,7009,0,0,0.5497686093026904,0,0,1.0,1.0,1,3.7241379310344827,7009,0.898820210310336,789,108,29,0.061887206839752136,22,2123,14875,0.6116558161424426,2125 -matmul,8x24x12xf64,linalg_xdsl,2614,4762,4759,0.0,0,2304,2498,0,0.9556235654169855,0.9992,2500,0,0,0.9563886763580719,0,0,7.9113924050632916,7.9113924050632916,1,0.0,316,0.7165532879818595,125,0,0,0.047819433817903594,0,2149,4766,1.0042081101759754,2151 +matmul,8x24x12xf64,linalg_xdsl,2597,4785,4782,0.0,0,2304,2498,0,0.9618790912591452,0.9992,2500,0,0,0.9626492106276473,0,0,8.116883116883118,8.116883116883116,1,0.0,308,0.7530562347188264,101,0,0,0.03889102810935695,0,2189,4789,1.0015402387370043,2191 matmul,8x24x16xf64,baseline,16926,19070,19067,0.0,0,2944,3073,0,0.1815550041356493,0.32883895131086144,9345,0,0,0.5521091811414393,0,0,1.0,1.0,1,3.3513513513513513,9345,0.9070173735805105,958,124,37,0.056599314663830794,23,2145,19074,0.6087084958052701,2147 matmul,8x24x16xf64,linalg_xdsl,3462,5626,5623,0.0,0,3072,3330,0,0.9618717504332756,0.9993997599039616,3332,0,0,0.9624494511842865,0,0,7.933333333333334,7.933333333333334,1,0.0,420,0.7381370826010545,149,0,0,0.04303870595031774,0,2165,5630,1.0054881571346042,2167 matmul,8x24x20xf64,baseline,21086,23250,23247,0.0,0,3680,3841,0,0.1821587783363369,0.32882458693605,11681,0,0,0.5539694584084226,0,0,1.0,1.0,1,3.3513513513513513,11681,0.9126494257363856,1118,124,37,0.0530209617755857,23,2165,23254,0.6069904201840083,2167 -matmul,8x24x20xf64,linalg_xdsl,4310,6494,6491,0.0,0,3840,4162,0,0.965661252900232,0.9995196926032661,4164,0,0,0.9661252900232019,0,0,7.946564885496183,7.9465648854961835,1,0.0,524,0.7517934002869441,173,0,0,0.04013921113689095,0,2185,6498,1.0062645011600928,2187 +matmul,8x24x20xf64,linalg_xdsl,4293,6497,6494,0.0,0,3840,4162,0,0.9694852084789192,0.9995196926032661,4164,0,0,0.9699510831586303,0,0,8.069767441860463,8.069767441860465,1,0.0,516,0.7759398496240602,149,0,0,0.03470766363848125,0,2205,6501,1.0046587467971115,2207 matmul,8x24x24xf64,baseline,25380,27548,27545,0.0,0,4416,4609,0,0.18159968479117417,0.3288150103445816,14017,0,0,0.5522852639873916,0,0,1.0,1.0,1,3.0609555189456343,14017,0.8416596613426204,2637,1858,607,0.10390070921985815,48,2169,27552,0.6561859732072498,2171 -matmul,8x24x24xf64,linalg_xdsl,5158,7357,7354,0.0,0,4608,4994,0,0.9682047305157038,0.999599679743795,4996,0,0,0.9685924777045366,0,0,7.955414012738853,7.955414012738854,1,0.0,628,0.7612121212121212,197,0,0,0.03819309810003878,0,2200,7361,1.0067855758045754,2202 +matmul,8x24x24xf64,linalg_xdsl,5125,7362,7359,0.0,0,4608,4994,0,0.9744390243902439,0.999599679743795,4996,0,0,0.9748292682926829,0,0,8.163398692810457,8.163398692810457,1,0.0,612,0.8042049934296978,149,0,0,0.02907317073170732,0,2238,7366,1.0039024390243902,2240 matmul,8x24x28xf64,baseline,29540,31731,31728,0.0,0,5152,5377,0,0.18202437373053487,0.32880816975478505,16353,0,0,0.5535883547731889,0,0,1.0,1.0,1,3.054054054054054,16353,0.8437645116351066,3028,2147,703,0.1025050778605281,48,2192,31735,0.656093432633717,2194 -matmul,8x24x28xf64,linalg_xdsl,6006,8218,8215,0.0,0,5376,5826,0,0.97002997002997,0.9996568291008923,5828,0,0,0.9703629703629704,0,0,7.961748633879781,7.961748633879782,1,0.0,732,0.7681007345225603,221,0,0,0.0367965367965368,0,2213,8222,1.0071595071595072,2215 +matmul,8x24x28xf64,linalg_xdsl,5963,8179,8176,0.0,0,5376,5826,0,0.9770249874224384,0.9996568291008923,5828,0,0,0.9773603890659064,0,0,8.231638418079097,8.231638418079097,1,0.0,708,0.8261376896149358,149,0,0,0.024987422438369947,0,2217,8183,1.0023478115042763,2219 matmul,8x24x32xf64,baseline,33537,35770,35767,0.0,0,5888,6145,0,0.18323046187792588,0.3286271993154714,18699,0,0,0.5575632883084355,0,0,1.0,1.0,1,3.088888888888889,18699,0.9091306884480747,1869,139,45,0.05572949279899812,31,2234,35774,0.6132927811074336,2236 matmul,8x24x32xf64,linalg_xdsl,6854,9088,9085,0.0,0,6144,6658,0,0.971403559964984,0.9996996996996997,6660,0,0,0.9716953603735046,0,0,7.966507177033493,7.966507177033493,1,0.0,836,0.7733580018501388,245,0,0,0.03574555004377006,0,2235,9092,1.0074409104172746,2237 matmul,8x24x36xf64,baseline,38065,40293,40290,0.0,0,6624,6913,0,0.1816104032575857,0.32864273829332064,21035,0,0,0.5526073821095494,0,0,1.0,1.0,1,3.8682634730538923,21035,0.8881523391319034,2649,1292,334,0.0695914882437935,40,2229,40297,0.6221988703533429,2231 -matmul,8x24x36xf64,linalg_xdsl,7702,9951,9948,0.0,0,6912,7490,0,0.972474681900805,0.9997330485851575,7492,0,0,0.9727343547130616,0,0,7.970212765957446,7.970212765957447,1,0.0,940,0.7775020678246485,269,0,0,0.034925993248506884,0,2250,9955,1.0076603479615684,2252 +matmul,8x24x36xf64,linalg_xdsl,7653,9941,9938,0.0,0,6912,7490,0,0.9787011629426369,0.9997330485851575,7492,0,0,0.9789624983666536,0,0,8.179039301310043,8.179039301310043,1,0.0,916,0.8230008984725966,197,0,0,0.02574153926564746,0,2289,9945,1.004704037632301,2291 matmul,8x24x40xf64,baseline,44149,46434,46431,0.0,0,7360,7681,0,0.17397902557249315,0.3286551709383424,23371,0,0,0.5293664635665587,0,0,1.0,1.0,1,3.941690962099125,23371,0.8679714773824556,3555,2704,686,0.08052277514779496,48,2286,46438,0.6098892387143536,2288 -matmul,8x24x40xf64,linalg_xdsl,8550,10814,10811,0.0,0,7680,8322,0,0.9733333333333334,0.9997597308986065,8324,0,0,0.9735672514619883,0,0,7.973180076628352,7.973180076628353,1,0.0,1044,0.7808526551982049,293,0,0,0.03426900584795322,0,2265,10818,1.0078362573099415,2267 +matmul,8x24x40xf64,linalg_xdsl,8517,10801,10798,0.0,0,7680,8322,0,0.9771046143008102,0.9997597308986065,8324,0,0,0.9773394387695198,0,0,8.09727626459144,8.09727626459144,1,0.0,1028,0.8075412411626081,245,0,0,0.028765997416930845,0,2285,10805,1.0061054361864505,2287 matmul,8x24x44xf64,baseline,46945,49249,49246,0.0,0,8096,8449,0,0.1799765683246352,0.3287932443475892,25697,0,0,0.5473852380445202,0,0,1.0,1.0,1,3.1873252562907735,25697,0.8104519506733528,6010,6840,2146,0.12802215358398125,75,2305,49253,0.6754073916285015,2307 matmul,8x24x44xf64,linalg_xdsl,9398,11682,11679,0.0,0,8448,9154,0,0.9740370291551393,0.9997815640017474,9156,0,0,0.9742498403915727,0,0,7.975609756097561,7.975609756097561,1,0.0,1148,0.783617747440273,317,0,0,0.03373058097467546,0,2285,11686,1.0079804213662482,2287 matmul,8x24x48xf64,baseline,51176,53505,53502,0.0,0,8832,9217,0,0.18010395497889636,0.3287910676702458,28033,0,0,0.5477763013912772,0,0,1.0,1.0,1,3.18562874251497,28033,0.8112339391133233,6523,7448,2338,0.12746209160544006,75,2330,53509,0.6752383929967173,2332 -matmul,8x24x48xf64,linalg_xdsl,10246,12543,12540,0.0,0,9216,9986,0,0.9746242436072614,0.999799759711654,9988,0,0,0.9748194417333593,0,0,7.977635782747603,7.977635782747604,1,0.0,1252,0.7859384808537351,341,0,0,0.0332812804997072,0,2298,12547,1.0081007222330665,2300 +matmul,8x24x48xf64,linalg_xdsl,10181,12502,12499,0.0,0,9216,9986,0,0.9808466751792555,0.999799759711654,9988,0,0,0.9810431195363913,0,0,8.186885245901639,8.186885245901639,1,0.0,1220,0.8327645051194539,245,0,0,0.024064433749140555,0,2322,12506,1.0051075532855318,2324 matmul,8x24x4xf64,baseline,4429,6554,6551,0.0,0,736,769,0,0.17362835854594716,0.3290543431750107,2337,0,0,0.5276586136825469,0,0,1.0,1.0,1,3.7241379310344827,2337,0.8328581610833927,469,108,29,0.10589297809889366,22,2126,6558,0.6335515917814405,2128 matmul,8x24x4xf64,linalg_xdsl,909,3022,3019,0.0,0,768,834,0,0.9174917491749175,0.9976076555023924,836,0,0,0.9196919691969196,0,0,7.7407407407407405,7.7407407407407405,1,0.0,108,0.631578947368421,63,0,0,0.06930693069306931,0,2114,3026,0.988998899889989,2116 matmul,8x24x52xf64,baseline,57524,59848,59845,0.0,0,9568,9985,0,0.17357972324594953,0.328789225855313,30369,0,0,0.5279361657742855,0,0,1.0,1.0,1,3.123247818037556,30369,0.7604607487166646,9566,11809,3781,0.1662958069675266,102,2325,59852,0.694231972741812,2327 matmul,8x24x52xf64,linalg_xdsl,11094,13406,13403,0.0,0,9984,10818,0,0.9751216873985938,0.999815157116451,10820,0,0,0.9753019650261403,0,0,7.9793510324483785,7.979351032448378,1,0.0,1356,0.7879140034863451,365,0,0,0.03290066702722192,0,2313,13410,1.0082026320533621,2315 matmul,8x24x56xf64,baseline,61903,64232,64229,0.0,0,10304,10753,0,0.17370725166793208,0.328787647148754,32705,0,0,0.5283265754486859,0,0,1.0,1.0,1,3.1223887933153107,32705,0.7610061429635145,10271,12705,4069,0.16592087620955365,102,2330,64236,0.6942474516582395,2332 -matmul,8x24x56xf64,linalg_xdsl,11942,14247,14244,0.0,0,10752,11650,0,0.9755484843409814,0.9998283556470993,11652,0,0,0.9757159604756322,0,0,7.9808219178082185,7.980821917808219,1,0.0,1460,0.7896160086533262,389,0,0,0.032574108189582986,0,2306,14251,1.0082900686652152,2308 +matmul,8x24x56xf64,linalg_xdsl,11844,14173,14170,0.0,0,10752,11650,0,0.9836203985140155,0.9998283556470993,11652,0,0,0.983789260385005,0,0,8.252124645892351,8.252124645892351,1,0.0,1412,0.852142426071213,245,0,0,0.020685579196217493,0,2330,14177,1.0044748395812224,2332 matmul,8x24x60xf64,baseline,66287,68644,68641,0.0,0,11040,11521,0,0.1738048184410216,0.3287862789303958,35041,0,0,0.528625522349782,0,0,1.0,1.0,1,3.121643332568281,35041,0.7614960013908206,10975,13601,4357,0.1655679092431397,102,2358,68648,0.6941934315929217,2360 -matmul,8x24x60xf64,linalg_xdsl,12790,15139,15136,0.0,0,11520,12482,0,0.9759186864738076,0.9998397949375201,12484,0,0,0.9760750586395621,0,0,7.982097186700766,7.982097186700767,1,0.0,1564,0.7910976226605969,413,0,0,0.032290852228303364,0,2350,15143,1.0083659108678655,2352 +matmul,8x24x60xf64,linalg_xdsl,12709,15097,15094,0.0,0,11520,12482,0,0.9821386419073098,0.9998397949375201,12484,0,0,0.982296010701078,0,0,8.191601049868765,8.191601049868767,1,0.0,1524,0.8387451843698404,293,0,0,0.02305452828704068,0,2389,15101,1.0053505389881185,2391 matmul,8x24x64xf64,baseline,73744,76081,76078,0.0,0,11776,12289,0,0.16664406595790843,0.3287850817347567,37377,0,0,0.5068480147537426,0,0,1.0,1.0,1,3.4051958123303607,37377,0.7461819488530874,12714,17564,5158,0.17240724669125623,111,2338,76085,0.6792552614449989,2340 matmul,8x24x64xf64,linalg_xdsl,13637,15973,15970,0.0,0,12288,13314,0,0.9763144386595293,0.99984980474617,13316,0,0,0.9764610984820709,0,0,7.983213429256594,7.983213429256595,1,0.0,1668,0.7923990498812351,437,0,0,0.03204517122534282,0,2337,15977,1.0085062697074136,2339 matmul,8x24x8xf64,baseline,8589,10716,10713,0.0,0,1472,1537,0,0.1789498195366166,0.3289107639631928,4673,0,0,0.5440679939457446,0,0,1.0,1.0,1,3.7241379310344827,4673,0.8813655224443606,629,108,29,0.07323320526254512,22,2128,10720,0.6173011992082897,2130 matmul,8x24x8xf64,linalg_xdsl,1772,3900,3897,0.0,0,1536,1666,0,0.9401805869074492,0.9988009592326139,1668,0,0,0.9413092550790068,0,0,7.867924528301886,7.867924528301887,1,0.0,212,0.6816720257234726,99,0,0,0.055869074492099324,0,2129,3904,0.9971783295711061,2131 matmul,8x28x12xf64,baseline,14942,17121,17118,0.0,0,2592,2689,0,0.17996252175076966,0.3294939345668423,8161,0,0,0.5461785570874046,0,0,1.0,1.0,1,3.2455795677799606,8161,0.8588718164596927,1341,1652,509,0.08974702181769509,62,2180,17125,0.6359255789050997,2182 -matmul,8x28x12xf64,linalg_xdsl,2998,5157,5154,0.0,0,2688,2882,0,0.9613075383589059,0.9993065187239945,2884,0,0,0.961974649766511,0,0,9.126582278481012,9.126582278481013,1,0.0,316,0.7165532879818595,125,0,0,0.04169446297531688,0,2160,5161,1.003669112741828,2162 +matmul,8x28x12xf64,linalg_xdsl,2981,5178,5175,0.0,0,2688,2882,0,0.966789667896679,0.9993065187239945,2884,0,0,0.967460583696746,0,0,9.363636363636363,9.363636363636363,1,0.0,308,0.7530562347188264,101,0,0,0.033881247903388124,0,2198,5182,1.0013418316001341,2200 matmul,8x28x16xf64,baseline,19774,21973,21970,0.0,0,3456,3585,0,0.1812986750278143,0.329473393989523,10881,0,0,0.5502680287245878,0,0,1.0,1.0,1,3.234678624813154,10881,0.867564981661617,1661,2164,669,0.08399919085668049,62,2200,21977,0.6342672195812683,2202 matmul,8x28x16xf64,linalg_xdsl,3974,6153,6150,0.0,0,3584,3842,0,0.9667840966280825,0.9994797086368367,3844,0,0,0.9672873678912934,0,0,9.152380952380952,9.152380952380952,1,0.0,420,0.7381370826010545,149,0,0,0.03749370910920986,0,2180,6157,1.0047810770005032,2182 matmul,8x28x20xf64,baseline,25625,27854,27851,0.0,0,4320,4481,0,0.17486829268292683,0.32946106903904127,13601,0,0,0.530770731707317,0,0,1.0,1.0,1,3.4500434404865334,13601,0.8372422283779625,2644,3971,1151,0.10318048780487805,80,2230,27858,0.6339512195121951,2232 -matmul,8x28x20xf64,linalg_xdsl,4950,7147,7144,0.0,0,4480,4802,0,0.9701010101010101,0.9995836802664446,4804,0,0,0.9705050505050505,0,0,9.16793893129771,9.16793893129771,1,0.0,524,0.7517934002869441,173,0,0,0.03494949494949495,0,2198,7151,1.0054545454545454,2200 +matmul,8x28x20xf64,linalg_xdsl,4939,7155,7152,0.0,0,4480,4802,0,0.9722615914152662,0.9995836802664446,4804,0,0,0.9726665316865762,0,0,9.310077519379846,9.310077519379846,1,0.0,516,0.7759398496240602,149,0,0,0.030168050212593642,0,2217,7159,1.00283458189917,2219 matmul,8x28x24xf64,baseline,30649,32893,32890,0.0,0,5184,5377,0,0.17543802407908904,0.32945285215366704,16321,0,0,0.5325132957029594,0,0,1.0,1.0,1,3.4465454545454546,16321,0.8407252871786947,3092,4739,1375,0.10088420503115926,80,2245,32897,0.6333975007341186,2247 -matmul,8x28x24xf64,linalg_xdsl,5926,8138,8135,0.0,0,5376,5762,0,0.9723253459331759,0.9996530187369882,5764,0,0,0.9726628417144786,0,0,9.178343949044587,9.178343949044587,1,0.0,628,0.7612121212121212,197,0,0,0.03324333445831927,0,2213,8142,1.0059061761727979,2215 +matmul,8x28x24xf64,linalg_xdsl,5893,8128,8125,0.0,0,5376,5762,0,0.9777702358730698,0.9996530187369882,5764,0,0,0.9781096215849313,0,0,9.418300653594772,9.418300653594772,1,0.0,612,0.8042049934296978,149,0,0,0.025284235533684033,0,2236,8132,1.0033938571186154,2238 matmul,8x28x28xf64,baseline,35682,37932,37929,0.0,0,6048,6273,0,0.17580292584496385,0.32944698282653223,19041,0,0,0.5336304018833025,0,0,1.0,1.0,1,3.4434021263289556,19041,0.8434551495016611,3534,5506,1599,0.09904153354632587,80,2251,37936,0.6326719354296283,2253 -matmul,8x28x28xf64,linalg_xdsl,6901,9115,9112,0.0,0,6272,6722,0,0.9740617301840313,0.9997025580011898,6724,0,0,0.9743515432546008,0,0,9.185792349726775,9.185792349726777,1,0.0,732,0.7681007345225603,221,0,0,0.03202434429792784,0,2215,9119,1.0063758875525286,2217 +matmul,8x28x28xf64,linalg_xdsl,6852,9084,9081,0.0,0,6272,6722,0,0.9810274372446001,0.9997025580011898,6724,0,0,0.9813193228254524,0,0,9.497175141242938,9.497175141242938,1,0.0,708,0.8261376896149358,149,0,0,0.021745475773496788,0,2233,9088,1.0030647985989491,2235 matmul,8x28x32xf64,baseline,43406,45668,45665,0.0,0,6912,7169,0,0.16516149841035802,0.3291703016667432,21779,0,0,0.5017509100124407,0,0,1.0,1.0,1,3.813527180783818,21779,0.8282878223168784,4515,6033,1582,0.10401787771275861,80,2263,45672,0.6057687877251993,2265 matmul,8x28x32xf64,linalg_xdsl,7878,10132,10129,0.0,0,7168,7682,0,0.9751205889819751,0.9997397188964081,7684,0,0,0.9753744605229754,0,0,9.191387559808613,9.191387559808613,1,0.0,836,0.7733580018501388,245,0,0,0.0310992637725311,0,2255,10136,1.0064737242955064,2257 matmul,8x28x36xf64,baseline,48791,51063,51060,0.0,0,7776,8065,0,0.16529687852267835,0.32919711008612595,24499,0,0,0.5021212928613884,0,0,1.0,1.0,1,3.8156708004509583,24499,0.8217280472261353,5315,6769,1774,0.10893402471767334,80,2273,51067,0.6110553175790617,2275 -matmul,8x28x36xf64,linalg_xdsl,8854,11128,11125,0.0,0,8064,8642,0,0.9760560198780213,0.9997686256362796,8644,0,0,0.9762819064829455,0,0,9.195744680851064,9.195744680851064,1,0.0,940,0.7775020678246485,269,0,0,0.030381748362322113,0,2275,11132,1.0066636548452677,2277 +matmul,8x28x36xf64,linalg_xdsl,8805,11118,11115,0.0,0,8064,8642,0,0.9814877910278251,0.9997686256362796,8644,0,0,0.9817149346961953,0,0,9.436681222707422,9.436681222707424,1,0.0,916,0.8230008984725966,197,0,0,0.02237365133446905,0,2314,11122,1.0040885860306643,2316 matmul,8x28x40xf64,baseline,53031,55335,55332,0.0,0,8640,8961,0,0.1689766363070657,0.32943641777875815,27201,0,0,0.5129264015387226,0,0,1.0,1.0,1,3.507730364873222,27201,0.7990188878770966,6842,11344,3234,0.1290188757519187,107,2305,55339,0.6419452772906413,2307 -matmul,8x28x40xf64,linalg_xdsl,9830,12117,12114,0.0,0,8960,9602,0,0.9768056968463886,0.9997917534360683,9604,0,0,0.9770091556459817,0,0,9.199233716475096,9.199233716475096,1,0.0,1044,0.7808526551982049,293,0,0,0.029806714140386572,0,2288,12121,1.0068158697863683,2290 +matmul,8x28x40xf64,linalg_xdsl,9803,12109,12106,0.0,0,8960,9602,0,0.9794960726308273,0.9997917534360683,9604,0,0,0.97970009180863,0,0,9.342412451361868,9.342412451361868,1,0.0,1028,0.8075412411626081,245,0,0,0.0249923492808324,0,2307,12113,1.0046924410894624,2309 matmul,8x28x44xf64,baseline,60062,62369,62366,0.0,0,9504,9857,0,0.16411374912590324,0.3294341766652184,29921,0,0,0.49816855915553926,0,0,1.0,1.0,1,3.31432907001951,29921,0.7565169022275038,9630,15289,4613,0.16033432120142518,134,2308,62373,0.6585028803569645,2310 matmul,8x28x44xf64,linalg_xdsl,10806,13113,13110,0.0,0,9856,10562,0,0.977419951878586,0.9998106777735706,10564,0,0,0.9776050342402369,0,0,9.202090592334496,9.202090592334494,1,0.0,1148,0.783617747440273,317,0,0,0.029335554321673146,0,2308,13117,1.00694058856191,2310 matmul,8x28x48xf64,baseline,65476,67803,67800,0.0,0,10368,10753,0,0.16422811411815016,0.3294323090591587,32641,0,0,0.49851854114484695,0,0,1.0,1.0,1,3.3137800755617417,32641,0.7572615070527097,10463,16665,5029,0.15979901032439367,134,2328,67807,0.6583175514692406,2330 -matmul,8x28x48xf64,linalg_xdsl,11782,14111,14108,0.0,0,10752,11522,0,0.9779324393142081,0.9998264491496008,11524,0,0,0.9781021897810219,0,0,9.20447284345048,9.20447284345048,1,0.0,1252,0.7859384808537351,341,0,0,0.028942454591750127,0,2330,14115,1.007044644372772,2332 +matmul,8x28x48xf64,linalg_xdsl,11717,14085,14082,0.0,0,10752,11522,0,0.9833575147221986,0.9998264491496008,11524,0,0,0.9835282068788939,0,0,9.445901639344262,9.445901639344262,1,0.0,1220,0.8327645051194539,245,0,0,0.02090978919518648,0,2369,14089,1.0044379960740804,2371 matmul,8x28x4xf64,baseline,5278,7440,7437,0.0,0,864,897,0,0.16995073891625614,0.3296582138919515,2721,0,0,0.515536187949981,0,0,1.0,1.0,1,3.322751322751323,2721,0.7951490356516657,701,628,189,0.1328154604016673,62,2163,7444,0.6483516483516483,2165 matmul,8x28x4xf64,linalg_xdsl,1037,3155,3152,0.0,0,896,962,0,0.9276759884281581,0.9979253112033195,964,0,0,0.9296046287367405,0,0,8.925925925925926,8.925925925925926,1,0.0,108,0.631578947368421,63,0,0,0.06075216972034716,0,2119,3159,0.9903567984570877,2121 matmul,8x28x52xf64,baseline,75068,77389,77386,0.0,0,11232,11649,0,0.15517930409761815,0.3294307287689828,35361,0,0,0.47105291202642935,0,0,1.0,1.0,1,3.40330525981249,35361,0.7312337152074114,12997,21417,6293,0.17313635637022434,152,2322,77393,0.6441892683966537,2324 matmul,8x28x52xf64,linalg_xdsl,12758,15107,15104,0.0,0,11648,12482,0,0.978366515127763,0.9998397949375201,12484,0,0,0.9785232795108951,0,0,9.206489675516224,9.206489675516224,1,0.0,1356,0.7879140034863451,365,0,0,0.02860949992161781,0,2350,15111,1.007132779432513,2352 matmul,8x28x56xf64,baseline,80796,83157,83154,0.0,0,12096,12545,0,0.1552675875043319,0.32942937422861795,38081,0,0,0.4713228377642458,0,0,1.0,1.0,1,3.4030710172744723,38081,0.7317921518890041,13957,23049,6773,0.1727437001831774,152,2362,83161,0.6440665379474232,2364 -matmul,8x28x56xf64,linalg_xdsl,13734,16096,16093,0.0,0,12544,13442,0,0.9787388961700888,0.999851234751562,13444,0,0,0.9788845201689238,0,0,9.208219178082192,9.208219178082192,1,0.0,1460,0.7896160086533262,389,0,0,0.028323867773409058,0,2363,16100,1.0072083879423328,2365 +matmul,8x28x56xf64,linalg_xdsl,13643,16010,16007,0.0,0,12544,13442,0,0.9852671699772777,0.999851234751562,13444,0,0,0.9854137653008869,0,0,9.521246458923512,9.521246458923512,1,0.0,1412,0.852142426071213,245,0,0,0.017957927142124165,0,2368,16014,1.003371692443011,2370 matmul,8x28x60xf64,baseline,87460,89821,89818,0.0,0,12960,13441,0,0.1536816830551109,0.3294282002892086,40801,0,0,0.4665104047564601,0,0,1.0,1.0,1,3.3377912587894665,40801,0.7322899653606619,14916,24209,7253,0.17054653555911273,152,2362,89825,0.6370569403155728,2364 -matmul,8x28x60xf64,linalg_xdsl,14710,17092,17089,0.0,0,13440,14402,0,0.9790618626784501,0.9998611496806442,14404,0,0,0.9791978246091094,0,0,9.209718670076727,9.209718670076727,1,0.0,1564,0.7910976226605969,413,0,0,0.028076138681169274,0,2383,17096,1.0072739632902787,2385 +matmul,8x28x60xf64,linalg_xdsl,14629,17035,17032,0.0,0,13440,14402,0,0.9844828764782282,0.9998611496806442,14404,0,0,0.9846195912229134,0,0,9.451443569553806,9.451443569553806,1,0.0,1524,0.8387451843698404,293,0,0,0.020028710096383896,0,2407,17039,1.0046483013192973,2409 matmul,8x28x64xf64,baseline,92303,94703,94700,0.0,0,13824,14337,0,0.15532539570761514,0.32942717308885366,43521,0,0,0.47150146799128956,0,0,1.0,1.0,1,3.29865389002966,43521,0.707946319642131,17954,28916,8766,0.1945115543373455,170,2401,94707,0.666013022328635,2403 matmul,8x28x64xf64,linalg_xdsl,15685,18069,18066,0.0,0,14336,15362,0,0.9794070768249921,0.9998698255662588,15364,0,0,0.9795345871852088,0,0,9.21103117505995,9.211031175059953,1,0.0,1668,0.7923990498812351,437,0,0,0.027861013707363724,0,2385,18073,1.0073956008925726,2387 matmul,8x28x8xf64,baseline,10116,12271,12268,0.0,0,1728,1793,0,0.17724396994859629,0.3295350119463334,5441,0,0,0.537860814551206,0,0,1.0,1.0,1,3.2664756446991405,5441,0.8419993809965954,1021,1140,349,0.1009292210359826,62,2156,12275,0.6387900355871886,2158 matmul,8x28x8xf64,linalg_xdsl,2028,4161,4158,0.0,0,1792,1922,0,0.9477317554240631,0.998960498960499,1924,0,0,0.9487179487179487,0,0,9.075471698113207,9.075471698113208,1,0.0,212,0.6816720257234726,99,0,0,0.04881656804733728,0,2134,4165,0.9975345167652859,2136 matmul,8x32x12xf64,baseline,21518,23668,23665,0.0,0,3064,3162,0,0.14694674226229204,0.3363114231014678,9402,0,0,0.43693651826377916,0,0,1.0,1.0,1,3.5555555555555554,9402,0.4475864038846044,11604,32,9,0.5392694488335347,9,2151,23672,0.9762059670973138,2153 -matmul,8x32x12xf64,linalg_xdsl,3387,5557,5554,0.0,0,3072,3266,0,0.9642751697667552,0.9993880048959608,3268,0,0,0.9648656628284618,0,0,10.341772151898734,10.341772151898734,1,0.0,316,0.7165532879818595,125,0,0,0.03690581635665781,0,2171,5561,1.0017714791851196,2173 +matmul,8x32x12xf64,linalg_xdsl,3365,5554,5551,0.0,0,3072,3266,0,0.9705794947994056,0.9993880048959608,3268,0,0,0.9711738484398217,0,0,10.61038961038961,10.61038961038961,1,0.0,308,0.7530562347188264,101,0,0,0.030014858841010402,0,2190,5558,1.001188707280832,2192 matmul,8x32x16xf64,baseline,29033,31240,31237,0.0,0,4088,4218,0,0.1452829538800675,0.33641729143404053,12538,0,0,0.4318534081906796,0,0,1.0,1.0,1,3.25,12538,0.43988352103287376,15965,39,12,0.5498915027727069,12,2208,31244,0.9817449109633865,2210 matmul,8x32x16xf64,linalg_xdsl,4491,6681,6678,0.0,0,4096,4354,0,0.9694945446448452,0.9995408631772268,4356,0,0,0.969939879759519,0,0,10.371428571428572,10.371428571428572,1,0.0,420,0.7381370826010545,149,0,0,0.033177466043197504,0,2191,6685,1.0031173458027165,2193 matmul,8x32x20xf64,baseline,36169,38422,38419,0.0,0,5100,5268,0,0.14564958942741021,0.3362267041102885,15668,0,0,0.4331886422074152,0,0,1.0,1.0,1,0.0,15668,0.45108539183508956,19066,0,0,0.527136498106113,0,2254,38426,0.9603251403135282,2256 -matmul,8x32x20xf64,linalg_xdsl,5595,7786,7783,0.0,0,5120,5442,0,0.9726541554959786,0.9996326230712711,5444,0,0,0.9730116175156389,0,0,10.389312977099236,10.389312977099237,1,0.0,524,0.7517934002869441,173,0,0,0.03092046470062556,0,2192,7790,1.0039320822162645,2194 +matmul,8x32x20xf64,linalg_xdsl,5579,7823,7820,0.0,0,5120,5442,0,0.9754436278903029,0.9996326230712711,5444,0,0,0.9758021150743861,0,0,10.550387596899226,10.550387596899224,1,0.0,516,0.7759398496240602,149,0,0,0.026707295214196094,0,2245,7827,1.002509410288582,2247 matmul,8x32x24xf64,baseline,43384,45611,45608,0.0,0,6120,6320,0,0.14567582518900976,0.33617021276595743,18800,0,0,0.433339479992624,0,0,1.0,1.0,1,0.0,18800,0.45120721931550906,22866,0,0,0.5270606675271989,0,2228,45615,0.9604001475198229,2230 -matmul,8x32x24xf64,linalg_xdsl,6694,8921,8918,0.0,0,6144,6530,0,0.9755004481625336,0.9996938150642989,6532,0,0,0.9757992231849417,0,0,10.401273885350317,10.401273885350319,1,0.0,628,0.7612121212121212,197,0,0,0.029429339707200478,0,2228,8925,1.0052285628921422,2230 +matmul,8x32x24xf64,linalg_xdsl,6661,8911,8908,0.0,0,6144,6530,0,0.9803332832907972,0.9996938150642989,6532,0,0,0.9806335385077316,0,0,10.673202614379084,10.673202614379084,1,0.0,612,0.8042049934296978,149,0,0,0.02236901366161237,0,2251,8915,1.003002552169344,2253 matmul,8x32x28xf64,baseline,50605,52860,52857,0.0,0,7140,7372,0,0.14567730461416856,0.3361298559182929,21932,0,0,0.4333959094951092,0,0,1.0,1.0,1,0.0,21932,0.4509231465109585,26706,0,0,0.5277344135954946,0,2256,52864,0.9611303230906038,2258 -matmul,8x32x28xf64,linalg_xdsl,7803,10034,10031,0.0,0,7168,7618,0,0.9762911700627963,0.9997375328083989,7620,0,0,0.9765474817377932,0,0,10.40983606557377,10.40983606557377,1,0.0,732,0.7681007345225603,221,0,0,0.02832244008714597,0,2232,10038,1.004869921824939,2234 +matmul,8x32x28xf64,linalg_xdsl,7755,10010,10007,0.0,0,7168,7618,0,0.982333978078659,0.9997375328083989,7620,0,0,0.9825918762088974,0,0,10.76271186440678,10.76271186440678,1,0.0,708,0.8261376896149358,149,0,0,0.019213410702772406,0,2256,10014,1.0018052869116698,2258 matmul,8x32x32xf64,baseline,57815,60087,60084,0.0,0,8160,8424,0,0.14570613162674045,0.3360995850622407,25064,0,0,0.43352071261783276,0,0,1.0,1.0,1,0.0,25064,0.4507021992051932,30547,0,0,0.5283576926403183,0,2273,60091,0.961878405258151,2275 matmul,8x32x32xf64,linalg_xdsl,8907,11184,11181,0.0,0,8192,8706,0,0.9774334792859549,0.9997703261368857,8708,0,0,0.977658021780622,0,0,10.416267942583731,10.416267942583731,1,0.0,836,0.7733580018501388,245,0,0,0.027506455596721678,0,2278,11188,1.0051644773773436,2280 matmul,8x32x36xf64,baseline,65034,67327,67324,0.0,0,9180,9476,0,0.14570839868376542,0.33607603915449,28196,0,0,0.4335578312882492,0,0,1.0,1.0,1,0.0,28196,0.45045851040035784,34398,0,0,0.528923332410739,0,2294,67331,0.9624811636989882,2296 -matmul,8x32x36xf64,linalg_xdsl,10011,12282,12279,0.0,0,9216,9794,0,0.978323843771851,0.999795835034708,9796,0,0,0.9785236240135851,0,0,10.421276595744681,10.421276595744681,1,0.0,940,0.7775020678246485,269,0,0,0.02687044251323544,0,2272,12286,1.0053940665268204,2274 +matmul,8x32x36xf64,linalg_xdsl,9957,12264,12261,0.0,0,9216,9794,0,0.9836296073114392,0.999795835034708,9796,0,0,0.9838304710254092,0,0,10.694323144104803,10.694323144104803,1,0.0,916,0.8230008984725966,197,0,0,0.019785075826052025,0,2308,12268,1.0036155468514611,2310 matmul,8x32x40xf64,baseline,72284,74606,74603,0.0,0,10200,10528,0,0.1456477228708981,0.33605720122574056,31328,0,0,0.43340158264622874,0,0,1.0,1.0,1,0.0,31328,0.44941757043667874,38380,0,0,0.5309612085662111,0,2323,74610,0.9643627912124398,2325 -matmul,8x32x40xf64,linalg_xdsl,11110,13424,13421,0.0,0,10240,10882,0,0.9794779477947795,0.9998162440279309,10884,0,0,0.9796579657965797,0,0,10.425287356321839,10.425287356321839,1,0.0,1044,0.7808526551982049,293,0,0,0.02637263726372637,0,2315,13428,1.0060306030603061,2317 +matmul,8x32x40xf64,linalg_xdsl,11077,13411,13408,0.0,0,10240,10882,0,0.9823959555836418,0.9998162440279309,10884,0,0,0.9825765098853481,0,0,10.587548638132295,10.587548638132295,1,0.0,1028,0.8075412411626081,245,0,0,0.022117901959014172,0,2335,13415,1.0046944118443621,2337 matmul,8x32x44xf64,baseline,79552,81903,81900,0.0,0,11220,11580,0,0.145565164923572,0.3360417875798027,34460,0,0,0.4331757843925986,0,0,1.0,1.0,1,3.0,34460,0.44861029746794245,42355,6,2,0.5324190466613034,2,2352,81907,0.965594831053902,2354 matmul,8x32x44xf64,linalg_xdsl,12219,14559,14556,0.0,0,11264,11970,0,0.9796219003191751,0.9998329435349148,11972,0,0,0.9797855798346837,0,0,10.428571428571429,10.428571428571429,1,0.0,1148,0.783617747440273,317,0,0,0.025943203208118503,0,2341,14563,1.0057287830428023,2343 matmul,8x32x48xf64,baseline,86772,89143,89140,0.0,0,12240,12632,0,0.1455769142119578,0.33602894232815494,37592,0,0,0.43322730834831513,0,0,1.0,1.0,1,3.0,37592,0.44864006874246637,46199,6,2,0.5324182916148066,2,2372,89147,0.9656455999631217,2374 -matmul,8x32x48xf64,linalg_xdsl,13323,15683,15680,0.0,0,12288,13058,0,0.9801095849283195,0.9998468606431853,13060,0,0,0.980259701268483,0,0,10.431309904153355,10.431309904153355,1,0.0,1252,0.7859384808537351,341,0,0,0.02559483599789837,0,2361,15687,1.0058545372663814,2363 +matmul,8x32x48xf64,linalg_xdsl,13253,15633,15630,0.0,0,12288,13058,0,0.9852863502603184,0.9998468606431853,13060,0,0,0.9854372594884178,0,0,10.704918032786885,10.704918032786885,1,0.0,1220,0.8327645051194539,245,0,0,0.018486380442164038,0,2381,15637,1.0039236399305818,2383 matmul,8x32x4xf64,baseline,6550,8691,8688,0.0,0,1016,1050,0,0.16030534351145037,0.3354632587859425,3130,0,0,0.4778625954198473,0,0,1.0,1.0,1,0.0,3130,0.49036503211655963,3253,0,0,0.4966412213740458,0,2142,8695,0.9745038167938931,2144 matmul,8x32x4xf64,linalg_xdsl,1159,3305,3302,0.0,0,1024,1090,0,0.9404659188955996,0.9981684981684982,1092,0,0,0.9421915444348576,0,0,10.111111111111112,10.11111111111111,1,0.0,108,0.631578947368421,63,0,0,0.054357204486626405,0,2147,3309,0.996548748921484,2149 matmul,8x32x52xf64,baseline,94050,96450,96447,0.0,0,13260,13684,0,0.14549707602339182,0.3360180728808565,40724,0,0,0.43300372142477406,0,0,1.0,1.0,1,3.6,40724,0.4475804235769945,50263,18,5,0.534428495481127,5,2401,96454,0.9674322169059011,2403 matmul,8x32x52xf64,linalg_xdsl,14427,16783,16780,0.0,0,13312,14146,0,0.980522631177653,0.9998586372632174,14148,0,0,0.9806612601372426,0,0,10.43362831858407,10.43362831858407,1,0.0,1356,0.7879140034863451,365,0,0,0.025299785125112637,0,2357,16787,1.0059610452623553,2359 matmul,8x32x56xf64,baseline,101274,103694,103691,0.0,0,14280,14736,0,0.14550625037028259,0.3360087559284933,43856,0,0,0.43304303177518416,0,0,1.0,1.0,1,3.6,43856,0.44760611967870667,54123,18,5,0.5344214704662599,5,2421,103698,0.9674645022414441,2423 -matmul,8x32x56xf64,linalg_xdsl,15526,17925,17922,0.0,0,14336,15234,0,0.9811928378204302,0.9998687319506432,15236,0,0,0.9813216539997424,0,0,10.435616438356163,10.435616438356165,1,0.0,1460,0.7896160086533262,389,0,0,0.02505474687620765,0,2400,17929,1.00637640087595,2402 +matmul,8x32x56xf64,linalg_xdsl,15428,17835,17832,0.0,0,14336,15234,0,0.9874254602022298,0.9998687319506432,15236,0,0,0.9875550946331345,0,0,10.790368271954675,10.790368271954675,1,0.0,1412,0.852142426071213,245,0,0,0.01588021778584392,0,2408,17839,1.0034353124189783,2410 matmul,8x32x60xf64,baseline,108504,110937,110934,0.0,0,15300,15788,0,0.14550615645506157,0.3360006810249425,46988,0,0,0.43305315933053157,0,0,1.0,1.0,1,3.6,46988,0.4476241283389856,57984,18,5,0.5343950453439504,5,2434,110941,0.967448204674482,2436 -matmul,8x32x60xf64,linalg_xdsl,16635,19060,19057,0.0,0,15360,16322,0,0.9811842500751428,0.9998774810095565,16324,0,0,0.9813044785091675,0,0,10.437340153452684,10.437340153452686,1,0.0,1564,0.7910976226605969,413,0,0,0.02482717162608957,0,2426,19064,1.006131650135257,2428 +matmul,8x32x60xf64,linalg_xdsl,16549,18994,18991,0.0,0,15360,16322,0,0.986283159103269,0.9998774810095565,16324,0,0,0.9864040123270288,0,0,10.711286089238845,10.711286089238845,1,0.0,1524,0.8387451843698404,293,0,0,0.017704997280802465,0,2446,18998,1.0041090096078313,2448 matmul,8x32x64xf64,baseline,115808,118281,118278,0.0,0,16320,16840,0,0.14541309754075712,0.33599361532322425,50120,0,0,0.43278529980657643,0,0,1.0,1.0,1,3.375,50120,0.44658688930668544,62109,27,8,0.5363100994749931,8,2474,118285,0.9690953992815695,2476 matmul,8x32x64xf64,linalg_xdsl,17739,20186,20183,0.0,0,16384,17410,0,0.9814532949997181,0.999885136687342,17412,0,0,0.9815660409267715,0,0,10.43884892086331,10.43884892086331,1,0.0,1668,0.7923990498812351,437,0,0,0.024634985061164665,0,2448,20190,1.0062010259879361,2450 matmul,8x32x8xf64,baseline,14221,16407,16404,0.0,0,2040,2106,0,0.14809085155755572,0.3360995850622407,6266,0,0,0.44061599043667815,0,0,1.0,1.0,1,4.0,6266,0.4555434387495456,7489,12,3,0.5266155685254201,3,2187,16411,0.9672315589620983,2189 matmul,8x32x8xf64,linalg_xdsl,2282,4404,4401,0.0,0,2048,2178,0,0.9544259421560035,0.9990825688073395,2180,0,0,0.9553023663453112,0,0,10.283018867924527,10.283018867924529,1,0.0,212,0.6816720257234726,99,0,0,0.043382997370727434,0,2123,4408,0.9986853637160387,2125 matmul,8x36x12xf64,baseline,24815,26995,26992,0.0,0,3456,3554,0,0.14321982671771105,0.33648930126869914,10562,0,0,0.42562965948015313,0,0,1.0,1.0,1,3.7142857142857144,10562,0.4272826570654153,14157,26,7,0.570501712673786,7,2181,26999,0.9961313721539391,2183 -matmul,8x36x12xf64,linalg_xdsl,3771,5951,5948,0.0,0,3456,3650,0,0.967913020418987,0.9994523548740416,3652,0,0,0.9684433837178468,0,0,11.556962025316457,11.556962025316455,1,0.0,316,0.7165532879818595,125,0,0,0.03314770617873243,0,2181,5955,1.0015910898965792,2183 +matmul,8x36x12xf64,linalg_xdsl,3749,5948,5945,0.0,0,3456,3650,0,0.973592958122166,0.9994523548740416,3652,0,0,0.9741264337156575,0,0,11.857142857142858,11.857142857142858,1,0.0,308,0.7530562347188264,101,0,0,0.026940517471325687,0,2200,5952,1.0010669511869832,2202 matmul,8x36x16xf64,baseline,33234,35413,35410,0.0,0,4608,4738,0,0.14256484323283383,0.33645788950433175,14082,0,0,0.4237226936270085,0,0,1.0,1.0,1,3.3,14082,0.4253866602223296,19022,33,10,0.5723656496359151,10,2180,35417,0.9960883432629235,2182 matmul,8x36x16xf64,linalg_xdsl,5003,7184,7181,0.0,0,4608,4866,0,0.9726164301419149,0.9995891536565324,4868,0,0,0.9730161902858285,0,0,11.59047619047619,11.59047619047619,1,0.0,420,0.7381370826010545,149,0,0,0.02978213072156706,0,2182,7188,1.0027983210073956,2184 matmul,8x36x20xf64,baseline,41881,44075,44072,0.0,0,5760,5929,0,0.14156777536353,0.3367028224203532,17609,0,0,0.42045318879682914,0,0,1.0,1.0,1,0.0,17609,0.4211369669719944,24204,0,0,0.577923163248251,0,2195,44079,0.9983763520450801,2197 -matmul,8x36x20xf64,linalg_xdsl,6235,8441,8438,0.0,0,5760,6082,0,0.9754611066559743,0.9996712689020382,6084,0,0,0.9757818765036087,0,0,11.610687022900763,11.610687022900763,1,0.0,524,0.7517934002869441,173,0,0,0.027746591820368885,0,2207,8445,1.0035284683239776,2209 +matmul,8x36x20xf64,linalg_xdsl,6219,8478,8475,0.0,0,5760,6082,0,0.9779707348448303,0.9996712689020382,6084,0,0,0.9782923299565847,0,0,11.790697674418604,11.790697674418604,1,0.0,516,0.7759398496240602,149,0,0,0.02395883582569545,0,2260,8482,1.0022511657822801,2262 matmul,8x36x24xf64,baseline,50233,52452,52449,0.0,0,6912,7113,0,0.14160014333207255,0.336646315490558,21129,0,0,0.420619911213744,0,0,1.0,1.0,1,0.0,21129,0.42119007275989234,29036,0,0,0.5780263969900264,0,2220,52456,0.9986463082037704,2222 -matmul,8x36x24xf64,linalg_xdsl,7467,9693,9690,0.0,0,6912,7298,0,0.9773670818267042,0.9997260273972602,7300,0,0,0.9776349270121869,0,0,11.624203821656051,11.624203821656051,1,0.0,628,0.7612121212121212,197,0,0,0.02638275077005491,0,2227,9697,1.0040176777822418,2229 +matmul,8x36x24xf64,linalg_xdsl,7429,9690,9687,0.0,0,6912,7298,0,0.9823664019383497,0.9997260273972602,7300,0,0,0.9826356171759322,0,0,11.928104575163399,11.928104575163399,1,0.0,612,0.8042049934296978,149,0,0,0.020056535199892315,0,2262,9694,1.0026921523758245,2264 matmul,8x36x28xf64,baseline,58585,60832,60829,0.0,0,8064,8297,0,0.14162328241017325,0.3366059475029413,24649,0,0,0.4207390970384911,0,0,1.0,1.0,1,0.0,24649,0.4212280192080934,33868,0,0,0.5781001962959802,0,2248,60836,0.9988392933344713,2250 -matmul,8x36x28xf64,linalg_xdsl,8699,10988,10985,0.0,0,8064,8514,0,0.9787331877227268,0.9997651479567872,8516,0,0,0.9789630992068054,0,0,11.633879781420767,11.633879781420765,1,0.0,732,0.7681007345225603,221,0,0,0.025405218990688583,0,2290,10992,1.0043683181974938,2292 +matmul,8x36x28xf64,linalg_xdsl,8651,10942,10939,0.0,0,8064,8514,0,0.9841636804993642,0.9997651479567872,8516,0,0,0.9843948676453589,0,0,12.028248587570621,12.028248587570621,1,0.0,708,0.8261376896149358,149,0,0,0.01722344237660386,0,2292,10946,1.0016183100219627,2294 matmul,8x36x32xf64,baseline,66937,69201,69198,0.0,0,9216,9481,0,0.14164064717570252,0.33657566828783414,28169,0,0,0.42082854026920835,0,0,1.0,1.0,1,0.0,28169,0.42125648656328046,38700,0,0,0.5781555791266415,0,2265,69205,0.9989841193958499,2267 matmul,8x36x32xf64,linalg_xdsl,9931,12202,12199,0.0,0,9216,9730,0,0.9797603463900917,0.9997944923962186,9732,0,0,0.9799617359782499,0,0,11.641148325358852,11.641148325358852,1,0.0,836,0.7733580018501388,245,0,0,0.024670224549390798,0,2272,12206,1.0046319605276406,2274 matmul,8x36x36xf64,baseline,75297,77628,77625,0.0,0,10368,10665,0,0.1416391091278537,0.33655211587617156,31689,0,0,0.4208534204549982,0,0,1.0,1.0,1,0.0,31689,0.421278632296832,43532,0,0,0.5781372431836593,0,2332,77632,0.9989906636386575,2334 -matmul,8x36x36xf64,linalg_xdsl,11164,13486,13483,0.0,0,10368,10946,0,0.9804729487638839,0.9998173182316404,10948,0,0,0.9806520960229308,0,0,11.646808510638298,11.646808510638298,1,0.0,940,0.7775020678246485,269,0,0,0.02409530634181297,0,2323,13490,1.0047474023647438,2325 +matmul,8x36x36xf64,linalg_xdsl,11110,13467,13464,0.0,0,10368,10946,0,0.9852385238523852,0.9998173182316404,10948,0,0,0.9854185418541854,0,0,11.951965065502185,11.951965065502183,1,0.0,916,0.8230008984725966,197,0,0,0.017731773177317733,0,2358,13471,1.003150315031503,2360 matmul,8x36x40xf64,baseline,83681,85990,85987,0.0,0,11520,11849,0,0.14159725624693778,0.3365332727427646,35209,0,0,0.4207526200690718,0,0,1.0,1.0,1,0.0,35209,0.42109480583162906,48404,0,0,0.5784347701389801,0,2310,85994,0.9991873902080519,2312 -matmul,8x36x40xf64,linalg_xdsl,12395,14740,14737,0.0,0,11520,12162,0,0.9812020976200081,0.9998355804011838,12164,0,0,0.9813634530052441,0,0,11.651340996168583,11.651340996168582,1,0.0,1044,0.7808526551982049,293,0,0,0.0236385639370714,0,2346,14744,1.0050020169423155,2348 +matmul,8x36x40xf64,linalg_xdsl,12363,14724,14721,0.0,0,11520,12162,0,0.983741810240233,0.9998355804011838,12164,0,0,0.9839035832726685,0,0,11.832684824902724,11.832684824902724,1,0.0,1028,0.8075412411626081,245,0,0,0.019817196473347894,0,2362,14728,1.0037207797460164,2364 matmul,8x36x44xf64,baseline,92083,94448,94445,0.0,0,12672,13033,0,0.14153535397413203,0.33651785483746033,38729,0,0,0.4205879478296754,0,0,1.0,1.0,1,0.0,38729,0.42090791518589765,53284,0,0,0.5786518684230532,0,2366,94452,0.9992398162527285,2368 matmul,8x36x44xf64,linalg_xdsl,13627,15968,15965,0.0,0,12672,13378,0,0.9817274528509576,0.9998505231689088,13380,0,0,0.9818742202979379,0,0,11.655052264808363,11.655052264808363,1,0.0,1148,0.783617747440273,317,0,0,0.023262640346371176,0,2342,15972,1.0051368606443092,2344 matmul,8x36x48xf64,baseline,100443,102833,102830,0.0,0,13824,14217,0,0.14154296466652727,0.3365050060356458,42249,0,0,0.42062662405543444,0,0,1.0,1.0,1,0.0,42249,0.42091996851742997,58124,0,0,0.5786764632677239,0,2391,102837,0.9993030873231583,2393 -matmul,8x36x48xf64,linalg_xdsl,14859,17220,17217,0.0,0,13824,14594,0,0.9821656908271081,0.9998629761578515,14596,0,0,0.9823002893869036,0,0,11.65814696485623,11.65814696485623,1,0.0,1252,0.7859384808537351,341,0,0,0.022949054445117436,0,2362,17224,1.0052493438320211,2364 +matmul,8x36x48xf64,linalg_xdsl,14789,17186,17183,0.0,0,13824,14594,0,0.9868145243086077,0.9998629761578515,14596,0,0,0.9869497599567246,0,0,11.963934426229507,11.963934426229509,1,0.0,1220,0.8327645051194539,245,0,0,0.01656636689431334,0,2398,17190,1.003516126851038,2400 matmul,8x36x4xf64,baseline,8316,10419,10416,0.0,0,1152,1186,0,0.1426166426166426,0.336740488358887,3522,0,0,0.4235209235209235,0,0,1.0,1.0,1,0.0,3522,0.42423512406649,4780,0,0,0.5747955747955747,0,2104,10423,0.9983164983164983,2106 matmul,8x36x4xf64,linalg_xdsl,1287,3438,3435,0.0,0,1152,1218,0,0.9463869463869464,0.9983606557377049,1220,0,0,0.947940947940948,0,0,11.296296296296298,11.296296296296296,1,0.0,108,0.631578947368421,63,0,0,0.04895104895104895,0,2152,3442,0.9968919968919969,2154 matmul,8x36x52xf64,baseline,108857,111272,111269,0.0,0,14976,15401,0,0.14147918829289802,0.3364941335838668,45769,0,0,0.4204506830061457,0,0,1.0,1.0,1,0.0,45769,0.42072896079422717,63016,0,0,0.5788878988030168,0,2416,111276,0.9993385818091625,2418 matmul,8x36x52xf64,linalg_xdsl,16091,18506,18503,0.0,0,14976,15810,0,0.9825368218258654,0.9998735137869972,15812,0,0,0.9826611149089554,0,0,11.660766961651918,11.660766961651918,1,0.0,1356,0.7879140034863451,365,0,0,0.022683487663911504,0,2416,18510,1.005344602572867,2418 matmul,8x36x56xf64,baseline,117221,119654,119651,0.0,0,16128,16585,0,0.14148488752015423,0.33648481405587455,49289,0,0,0.42047926566058985,0,0,1.0,1.0,1,0.0,49289,0.4207376930234146,67860,0,0,0.5789065099256959,0,2434,119658,0.9993857755862858,2436 -matmul,8x36x56xf64,linalg_xdsl,17323,19734,19731,0.0,0,16128,17026,0,0.982855163655256,0.9998825463941743,17028,0,0,0.982970617098655,0,0,11.663013698630136,11.663013698630136,1,0.0,1460,0.7896160086533262,389,0,0,0.022455694741095652,0,2412,19738,1.0054263118397506,2414 +matmul,8x36x56xf64,linalg_xdsl,17227,19663,19660,0.0,0,16128,17026,0,0.9883322691124398,0.9998825463941743,17028,0,0,0.9884483659371917,0,0,12.059490084985836,12.059490084985836,1,0.0,1412,0.852142426071213,245,0,0,0.014221861032100772,0,2437,19667,1.0026702269692924,2439 matmul,8x36x60xf64,baseline,125585,128043,128040,0.0,0,17280,17769,0,0.14148982760680018,0.3364767369198432,52809,0,0,0.4205040410877095,0,0,1.0,1.0,1,0.0,52809,0.4207452614470214,72704,0,0,0.5789226420352749,0,2459,128047,0.9994266831229843,2461 -matmul,8x36x60xf64,linalg_xdsl,18555,20986,20983,0.0,0,17280,18242,0,0.9831312314739963,0.9998903749177812,18244,0,0,0.9832390191323094,0,0,11.664961636828643,11.664961636828645,1,0.0,1564,0.7910976226605969,413,0,0,0.02225815144165993,0,2432,20990,1.0054971705739693,2434 +matmul,8x36x60xf64,linalg_xdsl,18469,20936,20933,0.0,0,17280,18242,0,0.9877091342249175,0.9998903749177812,18244,0,0,0.9878174237912177,0,0,11.971128608923884,11.971128608923884,1,0.0,1524,0.8387451843698404,293,0,0,0.01586442146299204,0,2468,20940,1.0036818452542098,2470 matmul,8x36x64xf64,baseline,134014,136501,136498,0.0,0,18432,18953,0,0.1414255227065829,0.3364696692644996,56329,0,0,0.4203217574283284,0,0,1.0,1.0,1,0.0,56329,0.42055083954875655,77612,0,0,0.5791335233632308,0,2488,136505,0.9994552807915591,2490 matmul,8x36x64xf64,linalg_xdsl,19787,22274,22271,0.0,0,18432,19458,0,0.9833729216152018,0.9998972250770812,19460,0,0,0.9834739980795472,0,0,11.666666666666666,11.666666666666666,1,0.0,1668,0.7923990498812351,437,0,0,0.02208520745944307,0,2488,22278,1.0055592055389901,2490 matmul,8x36x8xf64,baseline,16627,18783,18780,0.0,0,2304,2370,0,0.1425392433992903,0.33655211587617156,7042,0,0,0.42352799663198415,0,0,1.0,1.0,1,3.0,7042,0.425036214389184,9526,6,2,0.5729235580682023,2,2157,18787,0.9964515547001864,2159 matmul,8x36x8xf64,linalg_xdsl,2539,4701,4698,0.0,0,2304,2434,0,0.9586451358802678,0.9991789819376026,2436,0,0,0.9594328475777866,0,0,11.490566037735851,11.49056603773585,1,0.0,212,0.6773162939297125,101,0,0,0.03977944072469476,0,2163,4705,0.9992122883024813,2165 matmul,8x40x12xf64,baseline,27503,29696,29693,0.0,0,3840,3938,0,0.14318437988583063,0.3361789311934437,11714,0,0,0.42591717267207213,0,0,1.0,1.0,1,3.7142857142857144,11714,0.42740905608056334,15693,26,7,0.5705922990219249,7,2194,29700,0.9965094716939971,2196 -matmul,8x40x12xf64,linalg_xdsl,4155,6321,6318,0.0,0,3840,4034,0,0.9708784596871239,0.9995044598612488,4036,0,0,0.9713598074608905,0,0,12.772151898734176,12.772151898734178,1,0.0,316,0.7165532879818595,125,0,0,0.030084235860409144,0,2167,6325,1.0014440433212997,2169 +matmul,8x40x12xf64,linalg_xdsl,4133,6334,6331,0.0,0,3840,4034,0,0.9760464553593031,0.9995044598612488,4036,0,0,0.9765303653520445,0,0,13.103896103896103,13.103896103896103,1,0.0,308,0.7530562347188264,101,0,0,0.02443745463343818,0,2202,6338,1.0009678199854828,2204 matmul,8x40x16xf64,baseline,36818,39007,39004,0.0,0,5120,5250,0,0.142593296757021,0.3361505954667691,15618,0,0,0.4241946873811723,0,0,1.0,1.0,1,3.3,15618,0.42569777583951157,21070,33,10,0.5722744309848443,10,2190,39011,0.9964691183660166,2192 matmul,8x40x16xf64,linalg_xdsl,5515,7711,7708,0.0,0,5120,5378,0,0.9751586582048958,0.9996282527881041,5380,0,0,0.9755213055303718,0,0,12.80952380952381,12.80952380952381,1,0.0,420,0.7381370826010545,149,0,0,0.02701722574796011,0,2197,7715,1.002538531278332,2199 matmul,8x40x20xf64,baseline,46363,48583,48580,0.0,0,6400,6569,0,0.1416862584388413,0.3363715500025603,19529,0,0,0.4212195069344089,0,0,1.0,1.0,1,0.0,19529,0.4218473236272519,26765,0,0,0.5772922373444341,0,2221,48587,0.998511744278843,2223 -matmul,8x40x20xf64,linalg_xdsl,6879,9095,9092,0.0,0,6400,6722,0,0.9771769152493095,0.9997025580011898,6724,0,0,0.9774676551824393,0,0,12.83206106870229,12.83206106870229,1,0.0,524,0.7517934002869441,173,0,0,0.02514900421572903,0,2217,9099,1.0026166593981682,2219 +matmul,8x40x20xf64,linalg_xdsl,6859,9128,9125,0.0,0,6400,6722,0,0.9800262428925499,0.9997025580011898,6724,0,0,0.9803178305875492,0,0,13.031007751937983,13.031007751937985,1,0.0,516,0.7759398496240602,149,0,0,0.02172328327744569,0,2270,9132,1.002041113864995,2272 matmul,8x40x24xf64,baseline,55611,57876,57873,0.0,0,7680,7881,0,0.14171656686626746,0.3363205735501216,23433,0,0,0.4213734692776609,0,0,1.0,1.0,1,0.0,23433,0.4218969428540564,32109,0,0,0.5773857690025355,0,2266,57880,0.9987592382801964,2268 -matmul,8x40x24xf64,linalg_xdsl,8235,10514,10511,0.0,0,7680,8066,0,0.979477838494232,0.9997521070897373,8068,0,0,0.9797207043108682,0,0,12.847133757961782,12.847133757961783,1,0.0,628,0.7612121212121212,197,0,0,0.023922282938676383,0,2280,10518,1.0036429872495447,2282 +matmul,8x40x24xf64,linalg_xdsl,8197,10482,10479,0.0,0,7680,8066,0,0.9840185433695254,0.9997521070897373,8068,0,0,0.9842625350738075,0,0,13.183006535947712,13.183006535947712,1,0.0,612,0.8042049934296978,149,0,0,0.018177381969013053,0,2286,10486,1.0024399170428204,2288 matmul,8x40x28xf64,baseline,64859,67149,67146,0.0,0,8960,9193,0,0.14173823216515827,0.3362841570033288,27337,0,0,0.4214835258021246,0,0,1.0,1.0,1,0.0,27337,0.4219323969748418,37453,0,0,0.5774526280084491,0,2291,67153,0.9989361538105737,2293 -matmul,8x40x28xf64,linalg_xdsl,9595,11899,11896,0.0,0,8960,9410,0,0.9807191245440333,0.9997875053123672,9412,0,0,0.9809275664408547,0,0,12.857923497267759,12.857923497267759,1,0.0,732,0.7681007345225603,221,0,0,0.02303282959874935,0,2305,11903,1.003960396039604,2307 +matmul,8x40x28xf64,linalg_xdsl,9547,11853,11850,0.0,0,8960,9410,0,0.9856499423902797,0.9997875053123672,9412,0,0,0.9858594322823924,0,0,13.293785310734464,13.293785310734464,1,0.0,708,0.8261376896149358,149,0,0,0.015606996962396565,0,2307,11857,1.001466429244789,2309 matmul,8x40x32xf64,baseline,74107,76391,76388,0.0,0,10240,10505,0,0.1417544901291376,0.3362568419704875,31241,0,0,0.4215661138623882,0,0,1.0,1.0,1,0.0,31241,0.4219589940300927,42797,0,0,0.5775028000053976,0,2285,76395,0.9990689138677857,2287 matmul,8x40x32xf64,linalg_xdsl,10955,13270,13267,0.0,0,10240,10754,0,0.9816522136010953,0.9998140572703608,10756,0,0,0.9818347786398904,0,0,12.866028708133971,12.866028708133971,1,0.0,836,0.7733580018501388,245,0,0,0.022364217252396165,0,2316,13274,1.0041989958922866,2318 matmul,8x40x36xf64,baseline,83355,85664,85661,0.0,0,11520,11817,0,0.1417671405434587,0.33623559539052494,35145,0,0,0.42163037610221343,0,0,1.0,1.0,1,0.0,35145,0.4219796844607737,48141,0,0,0.5775418391218283,0,2310,85668,0.9991722152240418,2312 -matmul,8x40x36xf64,linalg_xdsl,12315,14660,14657,0.0,0,11520,12098,0,0.9823792123426716,0.9998347107438017,12100,0,0,0.9825416159155501,0,0,12.872340425531915,12.872340425531915,1,0.0,940,0.7775020678246485,269,0,0,0.021843280552172148,0,2346,14664,1.0043848964677222,2348 +matmul,8x40x36xf64,linalg_xdsl,12261,14626,14623,0.0,0,11520,12098,0,0.9867058151863632,0.9998347107438017,12100,0,0,0.9868689340184325,0,0,13.209606986899562,13.209606986899564,1,0.0,916,0.8230008984725966,197,0,0,0.016067204958812496,0,2366,14630,1.0029361389772449,2368 matmul,8x40x40xf64,baseline,92643,94993,94990,0.0,0,12800,13129,0,0.1417160497824984,0.33621859714717406,39049,0,0,0.42149973554396986,0,0,1.0,1.0,1,0.0,39049,0.42181390023116644,53525,0,0,0.5777554699221744,0,2351,94997,0.9992552054661443,2353 -matmul,8x40x40xf64,linalg_xdsl,13675,16045,16042,0.0,0,12800,13442,0,0.9829616087751372,0.999851234751562,13444,0,0,0.9831078610603291,0,0,12.877394636015326,12.877394636015326,1,0.0,1044,0.7808526551982049,293,0,0,0.021425959780621572,0,2371,16049,1.0045338208409507,2373 +matmul,8x40x40xf64,linalg_xdsl,13643,16029,16026,0.0,0,12800,13442,0,0.9852671699772777,0.999851234751562,13444,0,0,0.9854137653008869,0,0,13.077821011673151,13.077821011673151,1,0.0,1028,0.8075412411626081,245,0,0,0.017957927142124165,0,2387,16033,1.003371692443011,2389 matmul,8x40x44xf64,baseline,101941,104334,104331,0.0,0,14080,14441,0,0.14166037217606262,0.3362046888459479,42953,0,0,0.42135156610196095,0,0,1.0,1.0,1,0.0,42953,0.4216452341219201,58917,0,0,0.5779519526000334,0,2394,104338,0.9993035187019943,2396 matmul,8x40x44xf64,linalg_xdsl,15035,17401,17398,0.0,0,14080,14786,0,0.9834386431659461,0.9998647552069245,14788,0,0,0.9835716661124044,0,0,12.881533101045296,12.881533101045296,1,0.0,1148,0.783617747440273,317,0,0,0.021084137013634853,0,2367,17405,1.0046558031260393,2369 matmul,8x40x48xf64,baseline,111197,113617,113614,0.0,0,15360,15753,0,0.14166749102943424,0.3361930981496895,46857,0,0,0.42138726764211265,0,0,1.0,1.0,1,0.0,46857,0.4216564980292641,64269,0,0,0.5779742259233612,0,2421,113621,0.9993614935654739,2423 -matmul,8x40x48xf64,linalg_xdsl,16395,18815,18812,0.0,0,15360,16130,0,0.9838365355291248,0.9998760228118027,16132,0,0,0.9839585239402256,0,0,12.884984025559106,12.884984025559106,1,0.0,1252,0.7859384808537351,341,0,0,0.020799024092711192,0,2421,18819,1.004757548032937,2423 +matmul,8x40x48xf64,linalg_xdsl,16325,18765,18762,0.0,0,15360,16130,0,0.9880551301684533,0.9998760228118027,16132,0,0,0.9881776416539051,0,0,13.22295081967213,13.222950819672132,1,0.0,1220,0.8327645051194539,245,0,0,0.015007656967840736,0,2441,18769,1.0031852986217458,2443 matmul,8x40x4xf64,baseline,9212,11320,11317,0.0,0,1280,1314,0,0.14264003473729917,0.33640552995391704,3906,0,0,0.42401215805471126,0,0,1.0,1.0,1,0.0,3906,0.4246575342465753,5292,0,0,0.574468085106383,0,2109,11324,0.9984802431610943,2111 matmul,8x40x4xf64,linalg_xdsl,1415,3571,3568,0.0,0,1280,1346,0,0.9512367491166078,0.9985163204747775,1348,0,0,0.9526501766784452,0,0,12.481481481481483,12.481481481481481,1,0.0,108,0.631578947368421,63,0,0,0.04452296819787986,0,2157,3575,0.997173144876325,2159 matmul,8x40x52xf64,baseline,120511,122927,122924,0.0,0,16640,17065,0,0.14160533063371808,0.33618329032130967,50761,0,0,0.4212146609023243,0,0,1.0,1.0,1,0.0,50761,0.4214839663218028,69673,0,0,0.5781463932753027,0,2417,122931,0.999361054177627,2419 matmul,8x40x52xf64,linalg_xdsl,17767,20183,20180,0.0,0,16640,17474,0,0.9835087521810097,0.9998855573357748,17476,0,0,0.983621320425508,0,0,12.887905604719764,12.887905604719764,1,0.0,1356,0.7879140034863451,365,0,0,0.020543704620926438,0,2417,20187,1.0041650250464345,2419 matmul,8x40x56xf64,baseline,129766,132228,132225,0.0,0,17920,18377,0,0.14161644806806098,0.33617488338059087,54665,0,0,0.4212582648767782,0,0,1.0,1.0,1,0.0,54665,0.421492127623483,75029,0,0,0.5781868902486014,0,2463,132232,0.9994451551253796,2465 -matmul,8x40x56xf64,linalg_xdsl,19110,21572,21569,0.0,0,17920,18818,0,0.984720041862899,0.999893730074389,18820,0,0,0.9848246991104134,0,0,12.89041095890411,12.89041095890411,1,0.0,1460,0.7896160086533262,389,0,0,0.02035583464154893,0,2463,21576,1.0051805337519624,2465 +matmul,8x40x56xf64,linalg_xdsl,19019,21486,21483,0.0,0,17920,18818,0,0.9894316210105684,0.999893730074389,18820,0,0,0.9895367790104632,0,0,13.328611898016998,13.328611898016996,1,0.0,1412,0.852142426071213,245,0,0,0.012881854987118146,0,2468,21490,1.0024186339975814,2470 matmul,8x40x60xf64,baseline,139031,141526,141523,0.0,0,19200,19689,0,0.14161589861253965,0.33616759719305433,58569,0,0,0.4212657608734743,0,0,1.0,1.0,1,0.0,58569,0.4214992011744894,80385,0,0,0.5781804058087765,0,2496,141530,0.9994461666822507,2498 -matmul,8x40x60xf64,linalg_xdsl,20475,22970,22967,0.0,0,19200,20162,0,0.9847130647130647,0.9999008133306884,20164,0,0,0.9848107448107448,0,0,12.892583120204604,12.892583120204604,1,0.0,1564,0.7910976226605969,413,0,0,0.02017094017094017,0,2496,22974,1.004981684981685,2498 +matmul,8x40x60xf64,linalg_xdsl,20389,22904,22901,0.0,0,19200,20162,0,0.9888665456863995,0.9999008133306884,20164,0,0,0.9889646377948894,0,0,13.230971128608923,13.230971128608925,1,0.0,1524,0.8387451843698404,293,0,0,0.014370493893766247,0,2516,22908,1.0033351316886556,2518 matmul,8x40x64xf64,baseline,148343,150864,150861,0.0,0,20480,21001,0,0.14157054933498717,0.3361612216477518,62473,0,0,0.42113884713131056,0,0,1.0,1.0,1,0.0,62473,0.4213234599873211,85805,0,0,0.5784229791766379,0,2522,150868,0.9995618263079484,2524 matmul,8x40x64xf64,linalg_xdsl,21835,24357,24354,0.0,0,20480,21506,0,0.9849324479047401,0.9999070113446159,21508,0,0,0.9850240439661094,0,0,12.894484412470025,12.894484412470025,1,0.0,1668,0.7923990498812351,437,0,0,0.020013739409205405,0,2523,24361,1.0050377833753148,2525 matmul,8x40x8xf64,baseline,18419,20585,20582,0.0,0,2560,2626,0,0.1425701721048917,0.33623559539052494,7810,0,0,0.42401867636679513,0,0,1.0,1.0,1,3.0,7810,0.42538126361655776,10550,6,2,0.5727781095607797,2,2167,20589,0.9967967859275748,2169 matmul,8x40x8xf64,linalg_xdsl,2795,4967,4964,0.0,0,2560,2690,0,0.962432915921288,0.9992570579494799,2692,0,0,0.9631484794275492,0,0,12.69811320754717,12.69811320754717,1,0.0,212,0.6773162939297125,101,0,0,0.036135957066189626,0,2173,4971,0.9992844364937389,2175 matmul,8x44x12xf64,baseline,30191,32389,32386,0.0,0,4224,4322,0,0.14315524494054518,0.3359241411472097,12866,0,0,0.42615348945049847,0,0,1.0,1.0,1,3.7142857142857144,12866,0.42751287589300546,17229,26,7,0.5706667549932098,7,2199,32393,0.9968202444437083,2201 -matmul,8x44x12xf64,linalg_xdsl,4539,6720,6717,0.0,0,4224,4418,0,0.9733421458471029,0.9995475113122172,4420,0,0,0.9737827715355806,0,0,13.987341772151899,13.987341772151899,1,0.0,316,0.7165532879818595,125,0,0,0.02753910552985239,0,2182,6724,1.0013218770654329,2184 +matmul,8x44x12xf64,linalg_xdsl,4517,6733,6730,0.0,0,4224,4418,0,0.9780827983174674,0.9995475113122172,4420,0,0,0.9785255700686296,0,0,14.35064935064935,14.35064935064935,1,0.0,308,0.7530562347188264,101,0,0,0.02235997343369493,0,2217,6737,1.0008855435023245,2219 matmul,8x44x16xf64,baseline,40402,42606,42603,0.0,0,5632,5762,0,0.14261670214345826,0.33589833275037895,17154,0,0,0.42458294143854264,0,0,1.0,1.0,1,3.3,17154,0.425953516090584,23118,33,10,0.5721993960695015,10,2205,42610,0.9967823375080442,2207 matmul,8x44x16xf64,linalg_xdsl,6027,8233,8230,0.0,0,5632,5890,0,0.977268956363033,0.9996605566870332,5892,0,0,0.9776007964161274,0,0,14.028571428571428,14.028571428571428,1,0.0,420,0.7381370826010545,149,0,0,0.024722083955533432,0,2207,8237,1.0023228803716608,2209 matmul,8x44x20xf64,baseline,50843,53078,53075,0.0,0,7040,7209,0,0.14178943020671478,0.3360995850622407,21449,0,0,0.4218673170347934,0,0,1.0,1.0,1,0.0,21449,0.4224406192145586,29325,0,0,0.5767755639911099,0,2236,53082,0.9986428810259033,2238 -matmul,8x44x20xf64,linalg_xdsl,7515,9746,9743,0.0,0,7040,7362,0,0.9796407185628743,0.9997284084736556,7364,0,0,0.9799068529607452,0,0,14.053435114503817,14.053435114503817,1,0.0,524,0.7517934002869441,173,0,0,0.023020625415834998,0,2232,9750,1.0029274783765803,2234 +matmul,8x44x20xf64,linalg_xdsl,7499,9783,9780,0.0,0,7040,7362,0,0.9817308974529937,0.9997284084736556,7364,0,0,0.9819975996799574,0,0,14.271317829457363,14.271317829457365,1,0.0,516,0.7759398496240602,149,0,0,0.01986931590878784,0,2285,9787,1.0018669155887452,2287 matmul,8x44x24xf64,baseline,60987,63272,63269,0.0,0,8448,8649,0,0.14181710856412022,0.3360531530481408,25737,0,0,0.42200796891140735,0,0,1.0,1.0,1,0.0,25737,0.42248596473948585,35181,0,0,0.5768606424319938,0,2286,63276,0.9988686113434011,2288 -matmul,8x44x24xf64,linalg_xdsl,9003,11302,11299,0.0,0,8448,8834,0,0.981228479395757,0.9997736532367587,8836,0,0,0.9814506275685883,0,0,14.070063694267516,14.070063694267516,1,0.0,628,0.7612121212121212,197,0,0,0.02188159502388093,0,2300,11306,1.0033322225924692,2302 +matmul,8x44x24xf64,linalg_xdsl,8965,11270,11267,0.0,0,8448,8834,0,0.9853876185164528,0.9997736532367587,8836,0,0,0.9856107083100948,0,0,14.437908496732026,14.437908496732026,1,0.0,612,0.8042049934296978,149,0,0,0.016620189626324597,0,2306,11274,1.0022308979364194,2308 matmul,8x44x28xf64,baseline,71131,73441,73438,0.0,0,9856,10089,0,0.14183689249413053,0.33601998334721067,30025,0,0,0.4221085040277797,0,0,1.0,1.0,1,0.0,30025,0.4225183642453069,41037,0,0,0.5769214547806161,0,2311,73445,0.9990299588083957,2313 -matmul,8x44x28xf64,linalg_xdsl,10491,12815,12812,0.0,0,9856,10306,0,0.9823658373844247,0.9998059759410167,10308,0,0,0.9825564769802688,0,0,14.081967213114753,14.081967213114755,1,0.0,732,0.7681007345225603,221,0,0,0.021065675340768277,0,2325,12819,1.0036221523210371,2327 +matmul,8x44x28xf64,linalg_xdsl,10443,12769,12766,0.0,0,9856,10306,0,0.9868811644163554,0.9998059759410167,10308,0,0,0.9870726802642918,0,0,14.559322033898304,14.559322033898304,1,0.0,708,0.8261376896149358,149,0,0,0.014267930671263047,0,2327,12773,1.001340610935555,2329 matmul,8x44x32xf64,baseline,81275,83579,83576,0.0,0,11264,11529,0,0.14185173792679176,0.3359951038964824,34313,0,0,0.42218394340203014,0,0,1.0,1.0,1,0.0,34313,0.42254266926089207,46893,0,0,0.5769670870501384,0,2305,83583,0.9991510304521686,2307 matmul,8x44x32xf64,linalg_xdsl,11979,14319,14316,0.0,0,11264,11778,0,0.9832206361131981,0.999830220713073,11780,0,0,0.9833875949578429,0,0,14.090909090909092,14.090909090909092,1,0.0,836,0.7733580018501388,245,0,0,0.020452458468987394,0,2341,14323,1.0038400534268304,2343 matmul,8x44x36xf64,baseline,91419,93761,93758,0.0,0,12672,12969,0,0.1418632888130476,0.3359757519235253,38601,0,0,0.42224264102648246,0,0,1.0,1.0,1,0.0,38601,0.4225615763546798,52749,0,0,0.5770025924588981,0,2343,93765,0.9992452334853805,2345 -matmul,8x44x36xf64,linalg_xdsl,13467,15808,15805,0.0,0,12672,13250,0,0.983886537461944,0.9998490793842438,13252,0,0,0.98403504863741,0,0,14.097872340425534,14.097872340425532,1,0.0,940,0.7775020678246485,269,0,0,0.019974753100170786,0,2342,15812,1.0040098017375807,2344 +matmul,8x44x36xf64,linalg_xdsl,13413,15790,15787,0.0,0,12672,13250,0,0.9878476105271006,0.9998490793842438,13252,0,0,0.9879967196003877,0,0,14.467248908296945,14.467248908296943,1,0.0,916,0.8230008984725966,197,0,0,0.014687243718780288,0,2378,15794,1.002683963319168,2380 matmul,8x44x40xf64,baseline,101603,103993,103990,0.0,0,14080,14409,0,0.1418166786413787,0.33596026953298047,42889,0,0,0.4221233624991388,0,0,1.0,1.0,1,0.0,42889,0.4224102271160399,58645,0,0,0.5771975236951665,0,2391,103997,0.9993208861943053,2393 -matmul,8x44x40xf64,linalg_xdsl,14955,17321,17318,0.0,0,14080,14722,0,0.9844199264460047,0.99986416734583,14724,0,0,0.9845536609829488,0,0,14.10344827586207,14.10344827586207,1,0.0,1044,0.7808526551982049,293,0,0,0.019592109662320296,0,2367,17325,1.0041457706452692,2369 +matmul,8x44x40xf64,linalg_xdsl,14923,17342,17339,0.0,0,14080,14722,0,0.9865308584064866,0.99986416734583,14724,0,0,0.9866648797158748,0,0,14.32295719844358,14.32295719844358,1,0.0,1028,0.8075412411626081,245,0,0,0.016417610400053607,0,2420,17346,1.0030824901159283,2422 matmul,8x44x44xf64,baseline,111796,114196,114193,0.0,0,15488,15849,0,0.14176714730401804,0.33594760158551834,47177,0,0,0.4219918422841604,0,0,1.0,1.0,1,0.0,47177,0.42225623400103823,64549,0,0,0.5773820172456975,0,2401,114200,0.9993738595298579,2403 matmul,8x44x44xf64,linalg_xdsl,16443,18865,18862,0.0,0,15488,16194,0,0.9848567779602262,0.9998765127191899,16196,0,0,0.9849784102657666,0,0,14.108013937282232,14.10801393728223,1,0.0,1148,0.783617747440273,317,0,0,0.019278720428145716,0,2423,18869,1.0042571306939123,2425 matmul,8x44x48xf64,baseline,121949,124392,124389,0.0,0,16896,17289,0,0.1417723802573207,0.335937044593413,51465,0,0,0.42202068077639016,0,0,1.0,1.0,1,0.0,51465,0.42226652882390586,70413,0,0,0.577397108627377,0,2444,124396,0.9994177894037672,2446 -matmul,8x44x48xf64,linalg_xdsl,17931,20352,20349,0.0,0,16896,17666,0,0.9852211254252412,0.9998868009961512,17668,0,0,0.9853326641012771,0,0,14.111821086261982,14.111821086261982,1,0.0,1252,0.7859384808537351,341,0,0,0.019017344264123586,0,2422,20356,1.0043500083654007,2424 +matmul,8x44x48xf64,linalg_xdsl,17861,20318,20315,0.0,0,16896,17666,0,0.9890823582106265,0.9998868009961512,17668,0,0,0.9891943340238508,0,0,14.481967213114753,14.481967213114753,1,0.0,1220,0.8327645051194539,245,0,0,0.013717037119982085,0,2458,20322,1.0029113711438329,2460 matmul,8x44x4xf64,baseline,10108,12227,12224,0.0,0,1408,1442,0,0.14265927977839335,0.3361305361305361,4290,0,0,0.424416303917689,0,0,1.0,1.0,1,0.0,4290,0.42500495343768574,5804,0,0,0.5741986545310646,0,2120,12231,0.9986149584487536,2122 matmul,8x44x4xf64,linalg_xdsl,1543,3709,3706,0.0,0,1408,1474,0,0.9552819183408944,0.9986449864498645,1476,0,0,0.9565780946208684,0,0,13.666666666666666,13.666666666666666,1,0.0,108,0.631578947368421,63,0,0,0.04082955281918341,0,2167,3713,0.9974076474400518,2169 matmul,8x44x52xf64,baseline,132159,134610,134607,0.0,0,18304,18729,0,0.1417156606814519,0.3359281114917583,55753,0,0,0.4218630588911841,0,0,1.0,1.0,1,0.0,55753,0.422108992898351,76329,0,0,0.5775543095816403,0,2452,134614,0.9994173684728245,2454 matmul,8x44x52xf64,linalg_xdsl,19419,21870,21867,0.0,0,18304,19138,0,0.98552963592358,0.9998955067920585,19140,0,0,0.9856326278387146,0,0,14.11504424778761,14.11504424778761,1,0.0,1356,0.7879140034863451,365,0,0,0.018796024512075803,0,2452,21874,1.0044286523507904,2454 matmul,8x44x56xf64,baseline,142315,144791,144788,0.0,0,19712,20169,0,0.14172083055194462,0.33592045435618995,60041,0,0,0.4218880652074623,0,0,1.0,1.0,1,0.0,60041,0.42211645270602793,82197,0,0,0.5775708814952746,0,2477,144795,0.9994589467027368,2479 -matmul,8x44x56xf64,linalg_xdsl,20907,23383,23380,0.0,0,19712,20610,0,0.9857942315970728,0.9999029691441879,20612,0,0,0.9858898933371598,0,0,14.117808219178082,14.117808219178082,1,0.0,1460,0.7896160086533262,389,0,0,0.01860620844693165,0,2477,23387,1.0044961017840914,2479 +matmul,8x44x56xf64,linalg_xdsl,20811,23312,23309,0.0,0,19712,20610,0,0.9903416462447744,0.9999029691441879,20612,0,0,0.9904377492672145,0,0,14.597733711048159,14.597733711048159,1,0.0,1412,0.852142426071213,245,0,0,0.011772620248906828,0,2502,23316,1.0022103695161213,2504 matmul,8x44x60xf64,baseline,152471,154977,154974,0.0,0,21120,21609,0,0.1417253116986181,0.3359138180291937,64329,0,0,0.42190974021289296,0,0,1.0,1.0,1,0.0,64329,0.422122918225127,88065,0,0,0.577585245718858,0,2507,154981,0.999494985931751,2509 -matmul,8x44x60xf64,linalg_xdsl,22395,24901,24898,0.0,0,21120,22082,0,0.9860236659968743,0.9999094366962507,22084,0,0,0.9861129716454565,0,0,14.120204603580564,14.120204603580563,1,0.0,1564,0.7910976226605969,413,0,0,0.01844161643223934,0,2507,24905,1.0045545880776958,2509 +matmul,8x44x60xf64,linalg_xdsl,22309,24851,24848,0.0,0,21120,22082,0,0.9898247344121207,0.9999094366962507,22084,0,0,0.9899143843291945,0,0,14.490813648293964,14.490813648293964,1,0.0,1524,0.8387451843698404,293,0,0,0.013133712851315612,0,2543,24855,1.0030480971805102,2545 matmul,8x44x64xf64,baseline,162679,165235,165232,0.0,0,22528,23049,0,0.1416839297020513,0.335908011134267,68617,0,0,0.42179383940152076,0,0,1.0,1.0,1,0.0,68617,0.4219624386584181,93997,0,0,0.5778066007290431,0,2557,165239,0.9996004401305638,2559 matmul,8x44x64xf64,linalg_xdsl,23883,26445,26442,0.0,0,22528,23554,0,0.9862245111585647,0.999915095941586,23556,0,0,0.9863082527320688,0,0,14.122302158273381,14.122302158273381,1,0.0,1668,0.7923990498812351,437,0,0,0.018297533810660304,0,2563,26449,1.0046057865427291,2565 matmul,8x44x8xf64,baseline,20211,22382,22379,0.0,0,2816,2882,0,0.1425956162485775,0.3359757519235253,8578,0,0,0.4244223442679729,0,0,1.0,1.0,1,3.0,8578,0.4256649464073045,11574,6,2,0.5726584533175004,2,2172,22386,0.9970807975854733,2174 matmul,8x44x8xf64,linalg_xdsl,3051,5228,5225,0.0,0,2816,2946,0,0.9655850540806293,0.9993215739484396,2948,0,0,0.9662405768600459,0,0,13.905660377358492,13.90566037735849,1,0.0,212,0.6773162939297125,101,0,0,0.03310390036053753,0,2178,5232,0.9993444772205835,2180 matmul,8x48x12xf64,baseline,32879,35092,35089,0.0,0,4608,4706,0,0.14313087381003073,0.3357112284206021,14018,0,0,0.4263511663980048,0,0,1.0,1.0,1,3.7142857142857144,14018,0.4275996705609615,18765,26,7,0.5707290367711914,7,2214,35096,0.9970802031691961,2216 -matmul,8x48x12xf64,linalg_xdsl,4923,7114,7111,0.0,0,4608,4802,0,0.9754214909607962,0.9995836802664446,4804,0,0,0.9758277473085517,0,0,15.202531645569621,15.20253164556962,1,0.0,316,0.7165532879818595,125,0,0,0.025391021734714605,0,2192,7118,1.0012187690432663,2194 +matmul,8x48x12xf64,linalg_xdsl,4901,7127,7124,0.0,0,4608,4802,0,0.9798000408079983,0.9995836802664446,4804,0,0,0.9802081207916752,0,0,15.5974025974026,15.597402597402597,1,0.0,308,0.7530562347188264,101,0,0,0.020608039175678432,0,2227,7131,1.0008161599673535,2229 matmul,8x48x16xf64,baseline,43986,46200,46197,0.0,0,6144,6274,0,0.14263629336607103,0.3356875334403424,18690,0,0,0.42490792524894283,0,0,1.0,1.0,1,3.3,18690,0.4261674571324334,25166,33,10,0.5721365889146547,10,2215,46204,0.9970445141635975,2217 matmul,8x48x16xf64,linalg_xdsl,6539,8755,8752,0.0,0,6144,6402,0,0.9790487842177703,0.9996876951905059,6404,0,0,0.9793546413824744,0,0,15.247619047619047,15.247619047619047,1,0.0,420,0.7381370826010545,149,0,0,0.022786358770454197,0,2217,8759,1.0021410001529285,2219 matmul,8x48x20xf64,baseline,55323,57593,57590,0.0,0,7680,7849,0,0.14187589248594618,0.33587230946981045,23369,0,0,0.422410209135441,0,0,1.0,1.0,1,0.0,23369,0.4229377058674485,31885,0,0,0.5763425699980117,0,2271,57597,0.9987527791334527,2273 -matmul,8x48x20xf64,linalg_xdsl,8155,10439,10436,0.0,0,7680,8002,0,0.9812385039852851,0.9997501249375312,8004,0,0,0.9814837522992029,0,0,15.274809160305344,15.274809160305344,1,0.0,524,0.7517934002869441,173,0,0,0.021213979153893316,0,2285,10443,1.0026977314530963,2287 +matmul,8x48x20xf64,linalg_xdsl,8133,10442,10439,0.0,0,7680,8002,0,0.9838927824910857,0.9997501249375312,8004,0,0,0.9841386942087791,0,0,15.511627906976743,15.511627906976743,1,0.0,516,0.7759398496240602,149,0,0,0.01832042296815443,0,2310,10446,1.0024591171769335,2312 matmul,8x48x24xf64,baseline,66363,68634,68631,0.0,0,9216,9417,0,0.1419013606979793,0.3358296779715417,28041,0,0,0.42253966818859906,0,0,1.0,1.0,1,0.0,28041,0.4229794551543126,38253,0,0,0.5764205958139325,0,2272,68638,0.9989602640025315,2274 -matmul,8x48x24xf64,linalg_xdsl,9766,12039,12036,0.0,0,9216,9602,0,0.9832070448494777,0.9997917534360683,9604,0,0,0.9834118369854598,0,0,15.29299363057325,15.292993630573248,1,0.0,628,0.7612121212121212,197,0,0,0.02017202539422486,0,2274,12043,1.0035838623796847,2276 +matmul,8x48x24xf64,linalg_xdsl,9733,12045,12042,0.0,0,9216,9602,0,0.9865406349532518,0.9997917534360683,9604,0,0,0.9867461214425152,0,0,15.69281045751634,15.69281045751634,1,0.0,612,0.8042049934296978,149,0,0,0.015308743450118154,0,2313,12049,1.0020548648926333,2315 matmul,8x48x28xf64,baseline,77403,79713,79710,0.0,0,10752,10985,0,0.14191956384119478,0.33579922355027053,32713,0,0,0.4226321977184347,0,0,1.0,1.0,1,0.0,32713,0.4230092844027207,44621,0,0,0.576476363965221,0,2311,79717,0.9991085616836557,2313 -matmul,8x48x28xf64,linalg_xdsl,11387,13693,13690,0.0,0,10752,11202,0,0.983753403003425,0.99982149232417,11204,0,0,0.9839290418898744,0,0,15.306010928961749,15.306010928961749,1,0.0,732,0.7681007345225603,221,0,0,0.01940809695266532,0,2307,13697,1.0033371388425398,2309 +matmul,8x48x28xf64,linalg_xdsl,11339,13669,13666,0.0,0,10752,11202,0,0.9879178058029808,0.99982149232417,11204,0,0,0.9880941882000176,0,0,15.824858757062147,15.824858757062147,1,0.0,708,0.8261376896149358,149,0,0,0.013140488579239792,0,2331,13673,1.0012346767792575,2333 matmul,8x48x32xf64,baseline,88443,90767,90764,0.0,0,12288,12553,0,0.1419332225275036,0.3357763809014311,37385,0,0,0.42270162703662245,0,0,1.0,1.0,1,0.0,37385,0.42303166089573857,50989,0,0,0.5765182094682451,0,2325,90771,0.9992198365048675,2327 matmul,8x48x32xf64,linalg_xdsl,13003,15363,15360,0.0,0,12288,12802,0,0.9845420287625932,0.999843798812871,12804,0,0,0.9846958394216719,0,0,15.31578947368421,15.31578947368421,1,0.0,836,0.7733580018501388,245,0,0,0.018841805737137583,0,2361,15367,1.0035376451588096,2363 matmul,8x48x36xf64,baseline,99483,101845,101842,0.0,0,13824,14121,0,0.14194384970296434,0.33575861331050716,42057,0,0,0.42275564669340493,0,0,1.0,1.0,1,0.0,42057,0.42304906753575955,57357,0,0,0.5765507674678085,0,2363,101849,0.9993064141612135,2365 -matmul,8x48x36xf64,linalg_xdsl,14619,16980,16977,0.0,0,13824,14402,0,0.9851563034407278,0.9998611496806442,14404,0,0,0.985293111703947,0,0,15.32340425531915,15.323404255319149,1,0.0,940,0.7775020678246485,269,0,0,0.01840071140296874,0,2362,16984,1.0036938231069157,2364 +matmul,8x48x36xf64,linalg_xdsl,14565,16962,16959,0.0,0,13824,14402,0,0.9888087881908685,0.9998611496806442,14404,0,0,0.9889461036731891,0,0,15.724890829694324,15.724890829694322,1,0.0,916,0.8230008984725966,197,0,0,0.013525575008582218,0,2398,16966,1.0024716786817713,2400 matmul,8x48x40xf64,baseline,110563,112978,112975,0.0,0,15360,15689,0,0.1419009976212657,0.33574439855336086,46729,0,0,0.4226459122853034,0,0,1.0,1.0,1,0.0,46729,0.42290984125834885,63765,0,0,0.5767300091350632,0,2416,112982,0.9993759214203666,2418 -matmul,8x48x40xf64,linalg_xdsl,16235,18631,18628,0.0,0,15360,16002,0,0.9856482907299046,0.9998750312421895,16004,0,0,0.9857714813674161,0,0,15.329501915708812,15.329501915708812,1,0.0,1044,0.7808526551982049,293,0,0,0.018047428395441947,0,2397,18635,1.003818909762858,2399 +matmul,8x48x40xf64,linalg_xdsl,16203,18652,18649,0.0,0,15360,16002,0,0.9875948898352157,0.9998750312421895,16004,0,0,0.9877183237672036,0,0,15.568093385214008,15.568093385214008,1,0.0,1028,0.8075412411626081,245,0,0,0.015120656668518176,0,2450,18656,1.0028389804357218,2452 matmul,8x48x44xf64,baseline,121653,124096,124093,0.0,0,16896,17257,0,0.14185429048194453,0.33573276784498357,51401,0,0,0.4225214339144945,0,0,1.0,1.0,1,0.0,51401,0.4227681729203336,70181,0,0,0.5768949388835458,0,2444,124100,0.9994163727980403,2446 matmul,8x48x44xf64,linalg_xdsl,17851,20272,20269,0.0,0,16896,17602,0,0.986051201613355,0.9998863894569416,17604,0,0,0.9861632401546132,0,0,15.334494773519163,15.334494773519165,1,0.0,1148,0.783617747440273,317,0,0,0.017758108789423563,0,2422,20276,1.0039213489440368,2424 matmul,8x48x48xf64,baseline,132700,135155,135152,0.0,0,18432,18825,0,0.14186134137151468,0.33572307527687123,56073,0,0,0.4225546345139412,0,0,1.0,1.0,1,0.0,56073,0.42277765211490614,76557,0,0,0.5769178598342125,0,2456,135159,0.9994724943481537,2458 -matmul,8x48x48xf64,linalg_xdsl,19467,21949,21946,0.0,0,18432,19202,0,0.9863872193969281,0.9998958550302021,19204,0,0,0.9864899573637438,0,0,15.338658146964857,15.338658146964857,1,0.0,1252,0.7859384808537351,341,0,0,0.01751682334206606,0,2483,21953,1.00400678070581,2485 +matmul,8x48x48xf64,linalg_xdsl,19397,21914,21911,0.0,0,18432,19202,0,0.9899468990050008,0.9998958550302021,19204,0,0,0.9900500077331547,0,0,15.740983606557377,15.740983606557377,1,0.0,1220,0.8327645051194539,245,0,0,0.012630819198845183,0,2518,21918,1.0026808269319998,2520 matmul,8x48x4xf64,baseline,11004,13128,13125,0.0,0,1536,1570,0,0.14267539076699381,0.33590072742832694,4674,0,0,0.4247546346782988,0,0,1.0,1.0,1,0.0,4674,0.42529572338489535,6316,0,0,0.573973100690658,0,2125,13132,0.9987277353689568,2127 matmul,8x48x4xf64,linalg_xdsl,1671,3842,3839,0.0,0,1536,1602,0,0.9587073608617595,0.9987531172069826,1604,0,0,0.959904248952723,0,0,14.851851851851853,14.851851851851851,1,0.0,108,0.631578947368421,63,0,0,0.03770197486535009,0,2172,3846,0.9976062238180731,2174 matmul,8x48x52xf64,baseline,143807,146288,146285,0.0,0,19968,20393,0,0.14180811782458433,0.33571487365215247,60745,0,0,0.4224064197153129,0,0,1.0,1.0,1,0.0,60745,0.4226327141167467,82985,0,0,0.5770581404243187,0,2482,146292,0.9994645601396316,2484 matmul,8x48x52xf64,linalg_xdsl,21083,23564,23561,0.0,0,19968,20802,0,0.9866717260351943,0.9999038646414151,20804,0,0,0.9867665891950861,0,0,15.342182890855456,15.342182890855458,1,0.0,1356,0.7879140034863451,365,0,0,0.01731252668026372,0,2482,23568,1.0040791158753497,2484 matmul,8x48x56xf64,baseline,154854,157381,157378,0.0,0,21504,21961,0,0.14181745385976469,0.33570784352691196,65417,0,0,0.42244307541296966,0,0,1.0,1.0,1,0.0,65417,0.4226395834140921,89365,0,0,0.5770919705012464,0,2528,157385,0.999535045914216,2530 -matmul,8x48x56xf64,linalg_xdsl,22694,25226,25223,0.0,0,21504,22402,0,0.9871331629505596,0.9999107302267453,22404,0,0,0.9872212919714461,0,0,15.345205479452055,15.345205479452055,1,0.0,1460,0.7896160086533262,389,0,0,0.01714109456243941,0,2533,25230,1.0043623865338855,2535 +matmul,8x48x56xf64,linalg_xdsl,22603,25140,25137,0.0,0,21504,22402,0,0.9911073751271955,0.9999107302267453,22404,0,0,0.9911958589567756,0,0,15.86685552407932,15.86685552407932,1,0.0,1412,0.852142426071213,245,0,0,0.010839269123567669,0,2538,25144,1.0020351280803432,2540 matmul,8x48x60xf64,baseline,165911,168476,168473,0.0,0,23040,23529,0,0.1418169982701569,0.33570175063134017,70089,0,0,0.42244938551392014,0,0,1.0,1.0,1,0.0,70089,0.42264553710336844,95745,0,0,0.5770865102374164,0,2566,168480,0.9995358957513365,2568 -matmul,8x48x60xf64,linalg_xdsl,24315,26880,26877,0.0,0,23040,24002,0,0.9871272876825005,0.9999166805532411,24004,0,0,0.987209541435328,0,0,15.347826086956522,15.347826086956522,1,0.0,1564,0.7910976226605969,413,0,0,0.016985399958873125,0,2566,26884,1.004194941394201,2568 +matmul,8x48x60xf64,linalg_xdsl,24229,26814,26811,0.0,0,23040,24002,0,0.9906310619505552,0.9999166805532411,24004,0,0,0.9907136076602419,0,0,15.750656167979002,15.750656167979002,1,0.0,1524,0.8387451843698404,293,0,0,0.012092946469107269,0,2586,26818,1.0028065541293492,2588 matmul,8x48x64xf64,baseline,177015,179611,179608,0.0,0,24576,25097,0,0.14177894528712257,0.3356964192560292,74761,0,0,0.4223427393158772,0,0,1.0,1.0,1,0.0,74761,0.42249788075727607,102189,0,0,0.5772900601643929,0,2597,179615,0.9996327994802701,2599 matmul,8x48x64xf64,linalg_xdsl,25931,28528,28525,0.0,0,24576,25602,0,0.987312483128302,0.9999218872051242,25604,0,0,0.98738961089044,0,0,15.350119904076738,15.350119904076738,1,0.0,1668,0.7923990498812351,437,0,0,0.016852416027148973,0,2598,28532,1.004242026917589,2600 matmul,8x48x8xf64,baseline,22003,24200,24197,0.0,0,3072,3138,0,0.14261691587510794,0.33575861331050716,9346,0,0,0.4247602599645503,0,0,1.0,1.0,1,3.0,9346,0.42590229675537733,12598,6,2,0.5725582875062492,2,2198,24204,0.9973185474707995,2200 matmul,8x48x8xf64,linalg_xdsl,3307,5492,5489,0.0,0,3072,3202,0,0.9682491684306017,0.9993757802746567,3204,0,0,0.9688539461747808,0,0,15.11320754716981,15.11320754716981,1,0.0,212,0.6773162939297125,101,0,0,0.03054127608104022,0,2186,5496,0.999395222255821,2188 matmul,8x4x12xf64,baseline,2435,4529,4526,0.0,0,288,385,0,0.15811088295687886,0.3082465972778223,1249,0,0,0.5129363449691992,0,0,1.0,1.0,1,0.0,1249,0.7282798833819242,466,0,0,0.19137577002053388,0,2095,4533,0.704312114989733,2097 -matmul,8x4x12xf64,linalg_xdsl,700,2809,2806,0.0,0,384,578,0,0.8257142857142857,0.996551724137931,580,0,0,0.8285714285714286,0,0,1.8354430379746836,1.8354430379746836,1,0.0,316,0.7198177676537585,123,0,0,0.1757142857142857,0,2110,2813,1.0042857142857144,2112 +matmul,8x4x12xf64,linalg_xdsl,675,2756,2753,0.0,0,384,578,0,0.8562962962962963,0.996551724137931,580,0,0,0.8592592592592593,0,0,1.8831168831168832,1.8831168831168832,1,0.0,308,0.7567567567567568,99,0,0,0.14666666666666667,0,2082,2760,1.005925925925926,2084 matmul,8x4x16xf64,baseline,3235,5334,5331,0.0,0,384,513,0,0.15857805255023183,0.3081081081081081,1665,0,0,0.5146831530139103,0,0,1.0,1.0,1,0.0,1665,0.7370517928286853,594,0,0,0.18361669242658424,0,2100,5338,0.6982998454404945,2102 matmul,8x4x16xf64,linalg_xdsl,908,3022,3019,0.0,0,512,770,0,0.8480176211453745,0.9974093264248705,772,0,0,0.8502202643171806,0,0,1.838095238095238,1.838095238095238,1,0.0,420,0.7407407407407407,147,0,0,0.1618942731277533,0,2115,3026,1.0121145374449338,2117 matmul,8x4x20xf64,baseline,4035,6144,6141,0.0,0,480,641,0,0.15885997521685255,0.30802498798654493,2081,0,0,0.5157372986369269,0,0,1.0,1.0,1,0.0,2081,0.7424188369603996,722,0,0,0.17893432465923173,0,2110,6148,0.6946716232961586,2112 -matmul,8x4x20xf64,linalg_xdsl,1116,3240,3237,0.0,0,640,962,0,0.8620071684587813,0.9979253112033195,964,0,0,0.8637992831541219,0,0,1.8396946564885495,1.8396946564885497,1,0.0,524,0.753956834532374,171,0,0,0.1532258064516129,0,2125,3244,1.017025089605735,2127 +matmul,8x4x20xf64,linalg_xdsl,1092,3184,3181,0.0,0,640,962,0,0.8809523809523809,0.9979253112033195,964,0,0,0.8827838827838828,0,0,1.8682170542635659,1.8682170542635659,1,0.0,516,0.7782805429864253,147,0,0,0.1346153846153846,0,2093,3188,1.0173992673992673,2095 matmul,8x4x24xf64,baseline,4835,6949,6946,0.0,0,576,769,0,0.15904860392967943,0.3079695634761714,2497,0,0,0.5164426059979318,0,0,1.0,1.0,1,0.0,2497,0.7460412309530923,850,0,0,0.17580144777662876,0,2115,6953,0.6922440537745606,2117 -matmul,8x4x24xf64,linalg_xdsl,1324,3453,3450,0.0,0,768,1154,0,0.8716012084592145,0.9982698961937716,1156,0,0,0.8731117824773413,0,0,1.8407643312101911,1.8407643312101911,1,0.0,628,0.7630619684082625,195,0,0,0.1472809667673716,0,2130,3457,1.020392749244713,2132 +matmul,8x4x24xf64,linalg_xdsl,1283,3384,3381,0.0,0,768,1154,0,0.8994544037412315,0.9982698961937716,1156,0,0,0.9010132501948558,0,0,1.8888888888888888,1.8888888888888888,1,0.0,612,0.8063241106719368,147,0,0,0.11457521434138737,0,2102,3388,1.0155884645362432,2104 matmul,8x4x28xf64,baseline,5635,7754,7751,0.0,0,672,897,0,0.15918367346938775,0.3079299691040165,2913,0,0,0.5169476486246672,0,0,1.0,1.0,1,0.0,2913,0.748650732459522,978,0,0,0.1735581188997338,0,2120,7758,0.6905057675244011,2122 -matmul,8x4x28xf64,linalg_xdsl,1532,3666,3663,0.0,0,896,1346,0,0.8785900783289817,0.9985163204747775,1348,0,0,0.8798955613577023,0,0,1.8415300546448086,1.8415300546448088,1,0.0,732,0.7697160883280757,219,0,0,0.1429503916449086,0,2135,3670,1.0228459530026108,2137 +matmul,8x4x28xf64,linalg_xdsl,1481,3634,3631,0.0,0,896,1346,0,0.9088453747467927,0.9985163204747775,1348,0,0,0.9101958136394328,0,0,1.903954802259887,1.9039548022598871,1,0.0,708,0.8280701754385965,147,0,0,0.09925725860904794,0,2154,3638,1.0094530722484807,2156 matmul,8x4x32xf64,baseline,6435,8577,8574,0.0,0,768,1025,0,0.1592851592851593,0.3079002703514569,3329,0,0,0.5173271173271173,0,0,1.0,1.0,1,0.0,3329,0.750281721884156,1108,0,0,0.17218337218337218,0,2143,8581,0.6895104895104895,2145 matmul,8x4x32xf64,linalg_xdsl,1732,3834,3831,0.0,0,1024,1538,0,0.8879907621247113,0.9987012987012988,1540,0,0,0.8891454965357968,0,0,1.8421052631578947,1.8421052631578947,1,0.0,836,0.7733580018501388,245,0,0,0.14145496535796767,0,2103,3838,1.0306004618937645,2105 matmul,8x4x36xf64,baseline,7235,9370,9367,0.0,0,864,1153,0,0.159364201796821,0.3078771695594125,3745,0,0,0.5176226675881134,0,0,1.0,1.0,1,0.0,3745,0.752159068085961,1234,0,0,0.17055977885279888,0,2136,9374,0.6881824464409123,2138 -matmul,8x4x36xf64,linalg_xdsl,1948,4098,4095,0.0,0,1152,1730,0,0.8880903490759754,0.9988452655889145,1732,0,0,0.8891170431211499,0,0,1.8425531914893618,1.8425531914893618,1,0.0,940,0.7787903893951947,267,0,0,0.1370636550308008,0,2151,4102,1.0261806981519508,2153 +matmul,8x4x36xf64,linalg_xdsl,1891,4012,4009,0.0,0,1152,1730,0,0.9148598625066102,0.9988452655889145,1732,0,0,0.9159175039661555,0,0,1.8908296943231442,1.8908296943231442,1,0.0,916,0.8244824482448245,195,0,0,0.10312004230565838,0,2122,4016,1.0190375462718138,2124 matmul,8x4x40xf64,baseline,8035,10175,10172,0.0,0,960,1281,0,0.15942750466708153,0.30785868781542897,4161,0,0,0.5178593652769135,0,0,1.0,1.0,1,0.0,4161,0.7533948940793047,1362,0,0,0.16950840074673304,0,2141,10179,0.6873677660236465,2143 -matmul,8x4x40xf64,linalg_xdsl,2156,4311,4308,0.0,0,1280,1922,0,0.891465677179963,0.998960498960499,1924,0,0,0.8923933209647495,0,0,1.842911877394636,1.842911877394636,1,0.0,1044,0.7820224719101123,291,0,0,0.1349721706864564,0,2156,4315,1.027365491651206,2158 +matmul,8x4x40xf64,linalg_xdsl,2116,4235,4232,0.0,0,1280,1922,0,0.9083175803402647,0.998960498960499,1924,0,0,0.9092627599243857,0,0,1.8715953307392996,1.8715953307392996,1,0.0,1028,0.8088119590873328,243,0,0,0.11483931947069943,0,2120,4239,1.024102079395085,2122 matmul,8x4x44xf64,baseline,8835,10980,10977,0.0,0,1056,1409,0,0.15947934352009055,0.3078435656543588,4577,0,0,0.5180531975099038,0,0,1.0,1.0,1,0.0,4577,0.7544090984011868,1490,0,0,0.16864742501414828,0,2146,10984,0.6867006225240521,2148 matmul,8x4x44xf64,linalg_xdsl,2364,4524,4521,0.0,0,1408,2114,0,0.8942470389170897,0.999054820415879,2116,0,0,0.8950930626057529,0,0,1.8432055749128922,1.843205574912892,1,0.0,1148,0.784688995215311,315,0,0,0.13324873096446702,0,2161,4528,1.02834179357022,2163 matmul,8x4x48xf64,baseline,9635,11785,11782,0.0,0,1152,1537,0,0.15952257394914374,0.30783096334868815,4993,0,0,0.5182148417228853,0,0,1.0,1.0,1,0.0,4993,0.755256390863712,1618,0,0,0.1679294239750908,0,2151,11789,0.6861442656979762,2153 -matmul,8x4x48xf64,linalg_xdsl,2572,4737,4734,0.0,0,1536,2306,0,0.8965785381026439,0.9991334488734835,2308,0,0,0.8973561430793157,0,0,1.843450479233227,1.843450479233227,1,0.0,1252,0.7869264613450659,339,0,0,0.13180404354587869,0,2166,4741,1.0291601866251943,2168 +matmul,8x4x48xf64,linalg_xdsl,2499,4635,4632,0.0,0,1536,2306,0,0.9227691076430572,0.9991334488734835,2308,0,0,0.9235694277711084,0,0,1.8918032786885246,1.8918032786885246,1,0.0,1220,0.833902939166097,243,0,0,0.09723889555822329,0,2137,4639,1.0208083233293317,2139 matmul,8x4x4xf64,baseline,822,2922,2919,0.0,0,96,129,0,0.15693430656934307,0.30935251798561153,417,0,0,0.5072992700729927,0,0,1.0,1.0,1,0.0,417,0.9084967320261438,42,0,0,0.051094890510948905,0,2101,2926,0.5583941605839416,2103 matmul,8x4x4xf64,linalg_xdsl,263,2337,2334,0.0,0,128,194,0,0.7376425855513308,0.9897959183673469,196,0,0,0.7452471482889734,0,0,1.8148148148148149,1.8148148148148149,1,0.0,108,0.631578947368421,63,0,0,0.23954372623574144,0,2075,2341,0.9847908745247149,2077 matmul,8x4x52xf64,baseline,10435,12595,12592,0.0,0,1248,1665,0,0.1595591758505031,0.30782029950083195,5409,0,0,0.5183517010062291,0,0,1.0,1.0,1,0.0,5409,0.7559748427672957,1746,0,0,0.1673215141351222,0,2161,12599,0.6856732151413513,2163 matmul,8x4x52xf64,linalg_xdsl,2780,4955,4952,0.0,0,1664,2498,0,0.8985611510791367,0.9992,2500,0,0,0.8992805755395683,0,0,1.8436578171091444,1.8436578171091444,1,0.0,1356,0.7888307155322862,363,0,0,0.13057553956834533,0,2176,4959,1.0298561151079135,2178 matmul,8x4x56xf64,baseline,11238,13405,13402,0.0,0,1344,1793,0,0.1595479622708667,0.30781115879828325,5825,0,0,0.5183306638191849,0,0,1.0,1.0,1,0.0,5825,0.756591765164307,1874,0,0,0.16675565047161417,0,2168,13409,0.685086314290799,2170 -matmul,8x4x56xf64,linalg_xdsl,2988,5129,5126,0.0,0,1792,2690,0,0.9002677376171352,0.9992570579494799,2692,0,0,0.9009370816599732,0,0,1.8438356164383563,1.8438356164383563,1,0.0,1460,0.7904710341093666,387,0,0,0.12951807228915663,0,2142,5133,1.0304551539491298,2144 +matmul,8x4x56xf64,linalg_xdsl,2883,5091,5088,0.0,0,1792,2690,0,0.9330558446063129,0.9992570579494799,2692,0,0,0.9337495664238641,0,0,1.906515580736544,1.906515580736544,1,0.0,1412,0.8531722054380665,243,0,0,0.08428720083246619,0,2209,5095,1.0180367672563302,2211 matmul,8x4x60xf64,baseline,12038,14210,14207,0.0,0,1440,1921,0,0.15957800299053,0.3078032366607915,6241,0,0,0.5184416015949493,0,0,1.0,1.0,1,0.0,6241,0.757127259492903,2002,0,0,0.16630669546436286,0,2173,14214,0.6847482970593122,2175 -matmul,8x4x60xf64,linalg_xdsl,3196,5342,5339,0.0,0,1920,2882,0,0.9017521902377973,0.9993065187239945,2884,0,0,0.9023779724655819,0,0,1.8439897698209717,1.843989769820972,1,0.0,1564,0.7918987341772152,411,0,0,0.1285982478097622,0,2147,5346,1.030976220275344,2149 +matmul,8x4x60xf64,linalg_xdsl,3107,5301,5298,0.0,0,1920,2882,0,0.9275828773736724,0.9993065187239945,2884,0,0,0.9282265851303508,0,0,1.8923884514435694,1.8923884514435696,1,0.0,1524,0.8396694214876033,291,0,0,0.0936594785967171,0,2195,5305,1.021886063727068,2197 matmul,8x4x64xf64,baseline,12838,15017,15014,0.0,0,1536,2049,0,0.15960429973516124,0.3077963046417305,6657,0,0,0.5185387131952017,0,0,1.0,1.0,1,0.0,6657,0.7575964493001024,2130,0,0,0.1659136937217635,0,2180,15021,0.6844524069169653,2182 matmul,8x4x64xf64,linalg_xdsl,3404,5598,5595,0.0,0,2048,3074,0,0.9030552291421856,0.9993498049414824,3076,0,0,0.9036427732079906,0,0,1.8441247002398082,1.8441247002398082,1,0.0,1668,0.7931526390870185,435,0,0,0.12779083431257343,0,2195,5602,1.031433607520564,2197 matmul,8x4x8xf64,baseline,1631,3724,3721,0.0,0,192,257,0,0.15757204169221337,0.3085234093637455,833,0,0,0.5107296137339056,0,0,1.0,1.0,1,0.0,833,0.952,42,0,0,0.02575107296137339,0,2094,3728,0.5364806866952789,2096 matmul,8x4x8xf64,linalg_xdsl,492,2585,2582,0.0,0,256,386,0,0.7845528455284553,0.9948453608247423,388,0,0,0.7886178861788617,0,0,1.8301886792452828,1.830188679245283,1,0.0,212,0.6816720257234726,99,0,0,0.20121951219512196,0,2094,2589,0.9898373983739837,2096 matmul,8x52x12xf64,baseline,35567,37790,37787,0.0,0,4992,5090,0,0.14311018640874967,0.3355306526038233,15170,0,0,0.4265189642083954,0,0,1.0,1.0,1,3.7142857142857144,15170,0.427673310591751,20301,26,7,0.5707819045744651,7,2224,37794,0.9973008687828605,2226 -matmul,8x52x12xf64,linalg_xdsl,5307,7508,7505,0.0,0,4992,5186,0,0.97719992462785,0.9996144949884348,5188,0,0,0.9775767853778029,0,0,16.417721518987342,16.417721518987342,1,0.0,316,0.7165532879818595,125,0,0,0.023553796872055777,0,2202,7512,1.0011305822498586,2204 +matmul,8x52x12xf64,linalg_xdsl,5285,7521,7518,0.0,0,4992,5186,0,0.981267738883633,0.9996144949884348,5188,0,0,0.9816461684011353,0,0,16.844155844155843,16.844155844155843,1,0.0,308,0.7530562347188264,101,0,0,0.019110690633869443,0,2237,7525,1.0007568590350047,2239 matmul,8x52x16xf64,baseline,47570,49799,49796,0.0,0,6656,6786,0,0.1426529325204961,0.33550875111242956,20226,0,0,0.4251839394576414,0,0,1.0,1.0,1,3.3,20226,0.42634907251264753,27214,33,10,0.5720832457431154,10,2230,49803,0.9972671852007569,2232 matmul,8x52x16xf64,linalg_xdsl,7051,9282,9279,0.0,0,6656,6914,0,0.9805701318961849,0.9997108155002892,6916,0,0,0.9808537796057297,0,0,16.46666666666667,16.466666666666665,1,0.0,420,0.7381370826010545,149,0,0,0.021131754361083534,0,2232,9286,1.0019855339668133,2234 matmul,8x52x20xf64,baseline,59807,62090,62087,0.0,0,8320,8489,0,0.14193990669988463,0.33567954446597337,25289,0,0,0.42284347986021703,0,0,1.0,1.0,1,0.0,25289,0.42335314304846405,34446,0,0,0.5759526476833815,0,2284,62094,0.9987961275435986,2286 -matmul,8x52x20xf64,linalg_xdsl,8795,11094,11091,0.0,0,8320,8642,0,0.9826037521318931,0.9997686256362796,8644,0,0,0.9828311540648096,0,0,16.49618320610687,16.49618320610687,1,0.0,524,0.7517934002869441,173,0,0,0.019670267197271177,0,2300,11098,1.0025014212620809,2302 +matmul,8x52x20xf64,linalg_xdsl,8773,11097,11094,0.0,0,8320,8642,0,0.9850678217257495,0.9997686256362796,8644,0,0,0.9852957939131426,0,0,16.751937984496124,16.751937984496124,1,0.0,516,0.7759398496240602,149,0,0,0.016983927960788785,0,2325,11101,1.0022797218739314,2327 matmul,8x52x24xf64,baseline,71743,74056,74053,0.0,0,9984,10185,0,0.1419650697629037,0.3356401384083045,30345,0,0,0.42296809444823885,0,0,1.0,1.0,1,0.0,30345,0.4233930041439355,41326,0,0,0.576028323320742,0,2314,74060,0.998996417768981,2316 -matmul,8x52x24xf64,linalg_xdsl,10539,12868,12865,0.0,0,9984,10370,0,0.9839643229907961,0.9998071731585036,10372,0,0,0.9841540943163488,0,0,16.51592356687898,16.515923566878982,1,0.0,628,0.7612121212121212,197,0,0,0.018692475566941834,0,2330,12872,1.0028465698832907,2332 +matmul,8x52x24xf64,linalg_xdsl,10501,12836,12833,0.0,0,9984,10370,0,0.9875249976192744,0.9998071731585036,10372,0,0,0.9877154556708885,0,0,16.947712418300654,16.947712418300654,1,0.0,612,0.8042049934296978,149,0,0,0.014189124845252834,0,2336,12840,1.0019045805161413,2338 matmul,8x52x28xf64,baseline,83679,86027,86024,0.0,0,11648,11881,0,0.14198305429080174,0.3356119883619107,35401,0,0,0.4230571589048626,0,0,1.0,1.0,1,0.0,35401,0.4234214838470463,48206,0,0,0.5760824101626454,0,2349,86031,0.999139569067508,2351 -matmul,8x52x28xf64,linalg_xdsl,12283,14647,14644,0.0,0,11648,12098,0,0.9849385329316942,0.9998347107438017,12100,0,0,0.985101359602703,0,0,16.530054644808743,16.530054644808743,1,0.0,732,0.7681007345225603,221,0,0,0.01799234714646259,0,2365,14651,1.0030937067491656,2367 +matmul,8x52x28xf64,linalg_xdsl,12235,14601,14598,0.0,0,11648,12098,0,0.9888026154474867,0.9998347107438017,12100,0,0,0.9889660809154066,0,0,17.09039548022599,17.09039548022599,1,0.0,708,0.8261376896149358,149,0,0,0.012178177360032693,0,2367,14605,1.0011442582754393,2369 matmul,8x52x32xf64,baseline,95615,97995,97992,0.0,0,13312,13577,0,0.14199654865868327,0.33559087426156164,40457,0,0,0.42312398682215135,0,0,1.0,1.0,1,0.0,40457,0.42344284772301477,55086,0,0,0.5761229932541965,0,2381,97999,0.9992469800763478,2383 matmul,8x52x32xf64,linalg_xdsl,14027,16383,16380,0.0,0,13312,13826,0,0.9856704926213731,0.9998553659242118,13828,0,0,0.9858130747843444,0,0,16.54066985645933,16.54066985645933,1,0.0,836,0.7733580018501388,245,0,0,0.017466314963998003,0,2357,16387,1.0032793897483425,2359 matmul,8x52x36xf64,baseline,107551,109941,109938,0.0,0,14976,15273,0,0.14200704781917417,0.3355744512556852,45513,0,0,0.423175981627321,0,0,1.0,1.0,1,0.0,45513,0.42345946650043265,61966,0,0,0.5761545685302787,0,2391,109945,0.9993305501575998,2393 -matmul,8x52x36xf64,linalg_xdsl,15771,18181,18178,0.0,0,14976,15554,0,0.9862405681313804,0.999871432244793,15556,0,0,0.9863673831716442,0,0,16.548936170212766,16.548936170212766,1,0.0,940,0.7775020678246485,269,0,0,0.017056622915477777,0,2411,18185,1.003424006087122,2413 +matmul,8x52x36xf64,linalg_xdsl,15717,18147,18144,0.0,0,14976,15554,0,0.9896290640707515,0.999871432244793,15556,0,0,0.9897563148183496,0,0,16.982532751091703,16.982532751091703,1,0.0,916,0.8230008984725966,197,0,0,0.012534198638417001,0,2431,18151,1.0022905134567666,2433 matmul,8x52x40xf64,baseline,119527,121965,121962,0.0,0,16640,16969,0,0.1419679235653869,0.3355613122664083,50569,0,0,0.4230759577333991,0,0,1.0,1.0,1,0.0,50569,0.4233309614499184,68886,0,0,0.5763216679076694,0,2439,121969,0.9993976256410685,2441 -matmul,8x52x40xf64,linalg_xdsl,17515,19931,19928,0.0,0,16640,17282,0,0.9866971167570654,0.999884286044897,17284,0,0,0.9868113045960605,0,0,16.555555555555557,16.555555555555557,1,0.0,1044,0.7808526551982049,293,0,0,0.016728518412789037,0,2417,19935,1.0035398230088495,2419 +matmul,8x52x40xf64,linalg_xdsl,17483,19952,19949,0.0,0,16640,17282,0,0.9885031173139621,0.999884286044897,17284,0,0,0.9886175141566093,0,0,16.813229571984436,16.813229571984436,1,0.0,1028,0.8075412411626081,245,0,0,0.01401361322427501,0,2470,19956,1.0026311273808843,2472 matmul,8x52x44xf64,baseline,131516,133967,133964,0.0,0,18304,18665,0,0.14192189543477599,0.33555056179775283,55625,0,0,0.4229523403996472,0,0,1.0,1.0,1,0.0,55625,0.42320011564299786,75814,0,0,0.576462179506676,0,2452,133971,0.9994145199063231,2454 matmul,8x52x44xf64,linalg_xdsl,19259,21710,21707,0.0,0,18304,19010,0,0.9870709798016511,0.9998948032821376,19012,0,0,0.9871748273534452,0,0,16.560975609756095,16.5609756097561,1,0.0,1148,0.783617747440273,317,0,0,0.016459836959343683,0,2452,21714,1.003634664312789,2454 matmul,8x52x48xf64,baseline,143460,145941,145938,0.0,0,19968,20361,0,0.1419280635717273,0.3355416028081277,60681,0,0,0.42298201589293183,0,0,1.0,1.0,1,0.0,60681,0.4232091670560666,82702,0,0,0.5764812491286769,0,2482,145945,0.9994632650216088,2484 -matmul,8x52x48xf64,linalg_xdsl,21003,23484,23481,0.0,0,19968,20738,0,0.987382754844546,0.9999035679845709,20740,0,0,0.9874779793362853,0,0,16.56549520766773,16.56549520766773,1,0.0,1252,0.7859384808537351,341,0,0,0.016235775841546445,0,2482,23488,1.0037137551778317,2484 +matmul,8x52x48xf64,linalg_xdsl,20933,23450,23447,0.0,0,19968,20738,0,0.9906845650408446,0.9999035679845709,20740,0,0,0.9907801079635026,0,0,17.0,17.0,1,0.0,1220,0.8327645051194539,245,0,0,0.011704008025605504,0,2518,23454,1.002484115989108,2520 matmul,8x52x4xf64,baseline,11900,14029,14026,0.0,0,1664,1698,0,0.1426890756302521,0.33570581257413995,5058,0,0,0.4250420168067227,0,0,1.0,1.0,1,0.0,5058,0.425542655224634,6828,0,0,0.5737815126050421,0,2130,14033,0.9988235294117648,2132 matmul,8x52x4xf64,linalg_xdsl,1799,3975,3972,0.0,0,1664,1730,0,0.9616453585325181,0.9988452655889145,1732,0,0,0.962757087270706,0,0,16.037037037037038,16.037037037037038,1,0.0,108,0.631578947368421,63,0,0,0.03501945525291829,0,2177,3979,0.9977765425236242,2179 matmul,8x52x52xf64,baseline,155444,157956,157953,0.0,0,21632,22057,0,0.1418967602480636,0.33553402193589604,65737,0,0,0.42289827847970973,0,0,1.0,1.0,1,0.0,65737,0.4230751903410371,89642,0,0,0.5766835644991122,0,2513,157960,0.9995818429788219,2515 matmul,8x52x52xf64,linalg_xdsl,22747,25282,25279,0.0,0,21632,22466,0,0.9876467226447444,0.999910984511305,22468,0,0,0.9877346463269882,0,0,16.5693215339233,16.569321533923304,1,0.0,1356,0.7879140034863451,365,0,0,0.016046072009495756,0,2536,25286,1.003780718336484,2538 matmul,8x52x56xf64,baseline,167392,169972,169969,0.0,0,23296,23753,0,0.14190044924488626,0.335527523907731,70793,0,0,0.42291746320015294,0,0,1.0,1.0,1,0.0,70793,0.42308175010607973,96534,0,0,0.5766942267252916,0,2581,169976,0.9996116899254446,2583 -matmul,8x52x56xf64,linalg_xdsl,24491,27032,27029,0.0,0,23296,24194,0,0.9878730962394349,0.9999173417093734,24196,0,0,0.9879547588910212,0,0,16.57260273972603,16.572602739726026,1,0.0,1460,0.7896160086533262,389,0,0,0.015883385733534768,0,2542,27036,1.0038381446245561,2544 +matmul,8x52x56xf64,linalg_xdsl,24395,26961,26958,0.0,0,23296,24194,0,0.9917606066816971,0.9999173417093734,24196,0,0,0.9918425906948145,0,0,17.135977337110482,17.135977337110482,1,0.0,1412,0.852142426071213,245,0,0,0.010043041606886656,0,2567,26965,1.0018856323017011,2569 matmul,8x52x60xf64,baseline,179340,181955,181952,0.0,0,24960,25449,0,0.14190364670458347,0.33552189218051653,75849,0,0,0.42293409166945467,0,0,1.0,1.0,1,0.0,75849,0.4230874355041138,103426,0,0,0.5767034682725549,0,2616,181959,0.9996375599420095,2618 -matmul,8x52x60xf64,linalg_xdsl,26235,28811,28808,0.0,0,24960,25922,0,0.9880693729750334,0.9999228514118191,25924,0,0,0.9881456070135315,0,0,16.57544757033248,16.575447570332482,1,0.0,1564,0.7910976226605969,413,0,0,0.01574232894987612,0,2577,28815,1.0038879359634076,2579 +matmul,8x52x60xf64,linalg_xdsl,26149,28761,28758,0.0,0,24960,25922,0,0.9913189796932961,0.9999228514118191,25924,0,0,0.9913954644537076,0,0,17.010498687664043,17.010498687664043,1,0.0,1524,0.8387451843698404,293,0,0,0.011205017400282994,0,2613,28765,1.0026004818539906,2615 matmul,8x52x64xf64,baseline,191354,193962,193959,0.0,0,26624,27145,0,0.1418574997125746,0.3355169643408936,80905,0,0,0.4228027634645735,0,0,1.0,1.0,1,0.0,80905,0.422950853952438,110382,0,0,0.5768471001390094,0,2609,193966,0.9996498636035829,2611 matmul,8x52x64xf64,linalg_xdsl,27979,30611,30608,0.0,0,26624,27650,0,0.9882411808856643,0.9999276725010849,27652,0,0,0.9883126630687301,0,0,16.577937649880095,16.577937649880095,1,0.0,1668,0.7923990498812351,437,0,0,0.015618856999892777,0,2633,30615,1.003931520068623,2635 matmul,8x52x8xf64,baseline,23795,26002,25999,0.0,0,3328,3394,0,0.14263500735448623,0.3355744512556852,10114,0,0,0.42504727884009247,0,0,1.0,1.0,1,3.0,10114,0.42610380856083585,13622,6,2,0.5724732086572809,2,2208,26006,0.9975204874973733,2210 matmul,8x52x8xf64,linalg_xdsl,3563,5753,5750,0.0,0,3328,3458,0,0.9705304518664047,0.999421965317919,3460,0,0,0.9710917765927589,0,0,16.32075471698113,16.32075471698113,1,0.0,212,0.6773162939297125,101,0,0,0.028346898680886894,0,2191,5757,0.9994386752736458,2193 matmul,8x56x12xf64,baseline,38255,40488,40485,0.0,0,5376,5474,0,0.14309240622140898,0.33537556671976476,16322,0,0,0.42666318128349234,0,0,1.0,1.0,1,3.7142857142857144,16322,0.4277365759060772,21837,26,7,0.5708273428310024,7,2234,40492,0.9974905241144948,2236 -matmul,8x56x12xf64,linalg_xdsl,5691,7902,7899,0.0,0,5376,5570,0,0.9787383588121595,0.9996410624551328,5572,0,0,0.9790897908979089,0,0,17.632911392405063,17.632911392405063,1,0.0,316,0.7165532879818595,125,0,0,0.021964505359339307,0,2212,7906,1.0010542962572482,2214 +matmul,8x56x12xf64,linalg_xdsl,5669,7915,7912,0.0,0,5376,5570,0,0.9825366025754101,0.9996410624551328,5572,0,0,0.9828893984829776,0,0,18.09090909090909,18.09090909090909,1,0.0,308,0.7530562347188264,101,0,0,0.017816193332157348,0,2247,7919,1.000705591815135,2249 matmul,8x56x16xf64,baseline,51146,53381,53378,0.0,0,7168,7298,0,0.14268955539045086,0.33535520632294824,21762,0,0,0.42548781918429596,0,0,1.0,1.0,1,3.3,21762,0.4265051740357479,29262,33,10,0.572126852539788,10,2236,53385,0.9976146717240839,2238 matmul,8x56x16xf64,linalg_xdsl,7563,9842,9839,0.0,0,7168,7426,0,0.9818854951738728,0.9997307485191168,7428,0,0,0.9821499404998016,0,0,17.685714285714287,17.685714285714287,1,0.0,420,0.7381370826010545,149,0,0,0.019701176781700382,0,2280,9846,1.0018511172815021,2282 matmul,8x56x20xf64,baseline,64287,66585,66582,0.0,0,8960,9129,0,0.14200382659013486,0.3355139843434158,27209,0,0,0.423242646258186,0,0,1.0,1.0,1,0.0,27209,0.4237172000311454,37006,0,0,0.575637376141366,0,2299,66589,0.998880022399552,2301 -matmul,8x56x20xf64,linalg_xdsl,9435,11749,11746,0.0,0,8960,9282,0,0.9837837837837838,0.9997845756139595,9284,0,0,0.9839957604663487,0,0,17.717557251908396,17.717557251908396,1,0.0,524,0.7517934002869441,173,0,0,0.018335983041865393,0,2315,11753,1.0023317435082142,2317 +matmul,8x56x20xf64,linalg_xdsl,9413,11752,11749,0.0,0,8960,9282,0,0.9860830765961968,0.9997845756139595,9284,0,0,0.9862955487092319,0,0,17.992248062015502,17.992248062015506,1,0.0,516,0.7759398496240602,149,0,0,0.01582917242111973,0,2340,11756,1.0021247211303517,2342 matmul,8x56x24xf64,baseline,77119,79452,79449,0.0,0,10752,10953,0,0.14202725657749712,0.3354773499954057,32649,0,0,0.4233587053774038,0,0,1.0,1.0,1,0.0,32649,0.4237543317715161,44398,0,0,0.5757076725579948,0,2334,79456,0.9990663779353985,2336 -matmul,8x56x24xf64,linalg_xdsl,11307,13656,13653,0.0,0,10752,11138,0,0.9850535066772795,0.9998204667863555,11140,0,0,0.9852303882550633,0,0,17.73885350318471,17.738853503184714,1,0.0,628,0.7612121212121212,197,0,0,0.017422835411691873,0,2350,13660,1.0026532236667551,2352 +matmul,8x56x24xf64,linalg_xdsl,11269,13624,13621,0.0,0,10752,11138,0,0.9883751885704144,0.9998204667863555,11140,0,0,0.9885526666075073,0,0,18.202614379084967,18.202614379084967,1,0.0,612,0.8042049934296978,149,0,0,0.013222113763421776,0,2356,13628,1.0017747803709292,2358 matmul,8x56x28xf64,baseline,89951,92314,92311,0.0,0,12544,12777,0,0.14204400173427756,0.33545118013074643,38089,0,0,0.4234416515658525,0,0,1.0,1.0,1,0.0,38089,0.4237808609352574,51790,0,0,0.5757579126413269,0,2364,92318,0.9991995642071794,2366 -matmul,8x56x28xf64,linalg_xdsl,13179,15558,15555,0.0,0,12544,12994,0,0.9859625161241369,0.9998461064943059,12996,0,0,0.9861142727065787,0,0,17.75409836065574,17.75409836065574,1,0.0,732,0.7681007345225603,221,0,0,0.016769102359814856,0,2380,15562,1.0028833750663935,2382 +matmul,8x56x28xf64,linalg_xdsl,13131,15512,15509,0.0,0,12544,12994,0,0.9895666742822329,0.9998461064943059,12996,0,0,0.9897189856065799,0,0,18.35593220338983,18.35593220338983,1,0.0,708,0.8261376896149358,149,0,0,0.011347193663848907,0,2382,15516,1.0010661792704287,2384 matmul,8x56x32xf64,baseline,102783,105163,105160,0.0,0,14336,14601,0,0.14205656577449577,0.33543155137954006,43529,0,0,0.42350388682953405,0,0,1.0,1.0,1,0.0,43529,0.4238007613595428,59182,0,0,0.5757956082231498,0,2381,105167,0.9992994950526839,2383 matmul,8x56x32xf64,linalg_xdsl,15051,17451,17448,0.0,0,14336,14850,0,0.986645405620889,0.9998653380016159,14852,0,0,0.9867782871569996,0,0,17.76555023923445,17.76555023923445,1,0.0,836,0.7733580018501388,245,0,0,0.016277988173543288,0,2401,17455,1.0030562753305428,2403 matmul,8x56x36xf64,baseline,115615,118050,118047,0.0,0,16128,16425,0,0.14206634087272413,0.33541628377136556,48969,0,0,0.42355230722657095,0,0,1.0,1.0,1,0.0,48969,0.4238162415724016,66574,0,0,0.5758249362106993,0,2436,118054,0.9993772434372703,2438 -matmul,8x56x36xf64,linalg_xdsl,16923,19334,19331,0.0,0,16128,16706,0,0.9871772144418838,0.9998802968637779,16708,0,0,0.9872953967972582,0,0,17.77446808510638,17.77446808510638,1,0.0,940,0.7775020678246485,269,0,0,0.015895526797849082,0,2412,19338,1.0031909235951073,2414 +matmul,8x56x36xf64,linalg_xdsl,16869,19316,19313,0.0,0,16128,16706,0,0.990337305115893,0.9998802968637779,16708,0,0,0.9904558657893177,0,0,18.24017467248908,18.240174672489083,1,0.0,916,0.8230008984725966,197,0,0,0.011678226332325568,0,2448,19320,1.0021340921216433,2450 matmul,8x56x40xf64,baseline,128487,130950,130947,0.0,0,17920,18249,0,0.14202993298932967,0.3354040691797313,54409,0,0,0.4234591826410454,0,0,1.0,1.0,1,0.0,54409,0.4236966086516373,74006,0,0,0.5759804493839844,0,2464,130954,0.9994396320250298,2466 -matmul,8x56x40xf64,linalg_xdsl,18795,21236,21233,0.0,0,17920,18562,0,0.9876030859271083,0.999892264598147,18564,0,0,0.9877094972067039,0,0,17.781609195402297,17.7816091954023,1,0.0,1044,0.7808526551982049,293,0,0,0.01558925246076084,0,2442,21240,1.0032987496674648,2444 +matmul,8x56x40xf64,linalg_xdsl,18763,21257,21254,0.0,0,17920,18562,0,0.9892874273836807,0.999892264598147,18564,0,0,0.9893940201460321,0,0,18.058365758754867,18.058365758754864,1,0.0,1028,0.8075412411626081,245,0,0,0.013057613388050952,0,2495,21261,1.002451633534083,2497 matmul,8x56x44xf64,baseline,141372,143848,143845,0.0,0,19712,20073,0,0.14198709786945082,0.3353940750889739,59849,0,0,0.423344085108791,0,0,1.0,1.0,1,0.0,59849,0.4235747903322835,81446,0,0,0.5761112525818408,0,2477,143852,0.9994553376906319,2479 matmul,8x56x44xf64,linalg_xdsl,20667,23143,23140,0.0,0,19712,20418,0,0.9879518072289156,0.9999020568070519,20420,0,0,0.9880485798616151,0,0,17.78745644599303,17.78745644599303,1,0.0,1148,0.783617747440273,317,0,0,0.015338462282866405,0,2477,23147,1.0033870421444815,2479 matmul,8x56x48xf64,baseline,154212,156723,156720,0.0,0,21504,21897,0,0.14199284102404483,0.3353857464503975,65289,0,0,0.42337172204497703,0,0,1.0,1.0,1,0.0,65289,0.4235832224997567,88846,0,0,0.576128965320468,0,2512,156727,0.9995006873654451,2514 -matmul,8x56x48xf64,linalg_xdsl,22539,25050,25047,0.0,0,21504,22274,0,0.988242601712587,0.9999102172741965,22276,0,0,0.9883313367940015,0,0,17.792332268370604,17.792332268370608,1,0.0,1252,0.7859384808537351,341,0,0,0.015129331381161543,0,2512,25054,1.003460668175163,2514 +matmul,8x56x48xf64,linalg_xdsl,22469,25016,25013,0.0,0,21504,22274,0,0.9913213761182073,0.9999102172741965,22276,0,0,0.9914103876452001,0,0,18.25901639344262,18.25901639344262,1,0.0,1220,0.8327645051194539,245,0,0,0.010903912056611332,0,2548,25020,1.0023142997018113,2550 matmul,8x56x4xf64,baseline,12796,14930,14927,0.0,0,1792,1826,0,0.1427008440137543,0.33553840499816245,5442,0,0,0.42528915286026886,0,0,1.0,1.0,1,0.0,5442,0.42575496792364265,7340,0,0,0.5736167552360113,0,2135,14934,0.9989059080962801,2137 matmul,8x56x4xf64,linalg_xdsl,1927,4108,4105,0.0,0,1792,1858,0,0.964193046185781,0.9989247311827957,1860,0,0,0.9652309289050337,0,0,17.22222222222222,17.22222222222222,1,0.0,108,0.631578947368421,63,0,0,0.03269330565646082,0,2182,4112,0.9979242345614945,2184 matmul,8x56x52xf64,baseline,167092,169672,169669,0.0,0,23296,23721,0,0.14196370861561294,0.33537869897778844,70729,0,0,0.4232937543389271,0,0,1.0,1.0,1,0.0,70729,0.4234584827602723,96298,0,0,0.5763172384075839,0,2581,169676,0.9996109927465109,2583 matmul,8x56x52xf64,linalg_xdsl,24411,26952,26949,0.0,0,23296,24130,0,0.9884887960345746,0.9999171224929554,24132,0,0,0.9885707263119086,0,0,17.79646017699115,17.79646017699115,1,0.0,1356,0.7879140034863451,365,0,0,0.014952275613452951,0,2542,26956,1.0035230019253616,2544 matmul,8x56x56xf64,baseline,179942,182539,182536,0.0,0,25088,25545,0,0.1419624101099243,0.3353726581680211,76169,0,0,0.42329750697446955,0,0,1.0,1.0,1,0.0,76169,0.42346459407019477,103702,0,0,0.5763079214413533,0,2598,182543,0.9996054284158229,2600 -matmul,8x56x56xf64,linalg_xdsl,26278,28877,28874,0.0,0,25088,25986,0,0.9888880432300784,0.9999230414037248,25988,0,0,0.988964152523023,0,0,17.8,17.8,1,0.0,1460,0.7896160086533262,389,0,0,0.014803257477738032,0,2600,28881,1.0037674100007612,2602 +matmul,8x56x56xf64,linalg_xdsl,26180,28787,28784,0.0,0,25088,25986,0,0.9925897631779985,0.9999230414037248,25988,0,0,0.9926661573720397,0,0,18.405099150141645,18.405099150141645,1,0.0,1412,0.852142426071213,245,0,0,0.009358288770053475,0,2608,28791,1.002024446142093,2610 matmul,8x56x60xf64,baseline,192780,195392,195389,0.0,0,26880,27369,0,0.14197012138188608,0.33536742271073045,81609,0,0,0.42332710862122624,0,0,1.0,1.0,1,0.0,81609,0.4234698907713463,111106,0,0,0.5763357194729744,0,2613,195396,0.9996628280942006,2615 -matmul,8x56x60xf64,linalg_xdsl,28155,30790,30787,0.0,0,26880,27842,0,0.9888829692772154,0.9999281712397644,27844,0,0,0.9889540046172971,0,0,17.803069053708438,17.80306905370844,1,0.0,1564,0.7910976226605969,413,0,0,0.014668797726869118,0,2636,30794,1.0036228023441662,2638 +matmul,8x56x60xf64,linalg_xdsl,28069,30724,30721,0.0,0,26880,27842,0,0.9919127863479283,0.9999281712397644,27844,0,0,0.991984039331647,0,0,18.27034120734908,18.27034120734908,1,0.0,1524,0.8387451843698404,293,0,0,0.010438562114788557,0,2656,30728,1.0024226014464357,2658 matmul,8x56x64xf64,baseline,205690,208338,208335,0.0,0,28672,29193,0,0.14192717195780058,0.33536284161793933,87049,0,0,0.42320482279157956,0,0,1.0,1.0,1,0.0,87049,0.4233427194428639,118574,0,0,0.5764694443093976,0,2649,208342,0.9996742671009772,2651 matmul,8x56x64xf64,linalg_xdsl,30027,32699,32696,0.0,0,28672,29698,0,0.9890431944583209,0.9999326599326599,29700,0,0,0.989109801178939,0,0,17.805755395683452,17.805755395683452,1,0.0,1668,0.7923990498812351,437,0,0,0.014553568455057115,0,2673,32703,1.003663369633996,2675 matmul,8x56x8xf64,baseline,25587,27799,27796,0.0,0,3584,3650,0,0.14265056473990698,0.33541628377136556,10882,0,0,0.4252940946574432,0,0,1.0,1.0,1,3.0,10882,0.4262770291444688,14646,6,2,0.5724000468988159,2,2213,27803,0.997694141556259,2215 matmul,8x56x8xf64,linalg_xdsl,3819,6019,6016,0.0,0,3584,3714,0,0.9725058915946583,0.9994617868675996,3716,0,0,0.9730295888976171,0,0,17.528301886792452,17.528301886792452,1,0.0,212,0.6773162939297125,101,0,0,0.026446713799423933,0,2201,6023,0.9994763026970411,2203 matmul,8x60x12xf64,baseline,40943,43186,43183,0.0,0,5760,5858,0,0.1430769606526146,0.3352409293807943,17474,0,0,0.4267884620081577,0,0,1.0,1.0,1,3.7142857142857144,17474,0.42779151467672044,23373,26,7,0.5708668148401436,7,2244,43190,0.9976552768483012,2246 -matmul,8x60x12xf64,linalg_xdsl,6075,8296,8293,0.0,0,5760,5954,0,0.9800823045267489,0.9996642041638684,5956,0,0,0.9804115226337449,0,0,18.848101265822784,18.848101265822784,1,0.0,316,0.7165532879818595,125,0,0,0.0205761316872428,0,2222,8300,1.0009876543209877,2224 +matmul,8x60x12xf64,linalg_xdsl,6053,8309,8306,0.0,0,5760,5954,0,0.9836444738146374,0.9996642041638684,5956,0,0,0.9839748884850488,0,0,19.337662337662337,19.337662337662337,1,0.0,308,0.7530562347188264,101,0,0,0.016685940855773997,0,2257,8313,1.0006608293408228,2259 matmul,8x60x16xf64,baseline,54730,56980,56977,0.0,0,7680,7810,0,0.14270052987392653,0.3352219074598678,23298,0,0,0.4256897496802485,0,0,1.0,1.0,1,3.3,23298,0.4266407852329329,31310,33,10,0.5720811255253061,10,2251,56984,0.9977708752055545,2253 matmul,8x60x16xf64,linalg_xdsl,8075,10369,10366,0.0,0,7680,7938,0,0.9830340557275542,0.9997481108312343,7940,0,0,0.98328173374613,0,0,18.9047619047619,18.904761904761905,1,0.0,420,0.7381370826010545,149,0,0,0.01845201238390093,0,2295,10373,1.0017337461300309,2297 matmul,8x60x20xf64,baseline,68767,71080,71077,0.0,0,9600,9769,0,0.1420594180348132,0.3353702495794569,29129,0,0,0.42358980324865125,0,0,1.0,1.0,1,0.0,29129,0.4240337724725235,39566,0,0,0.5753631829220411,0,2314,71084,0.9989529861706924,2316 -matmul,8x60x20xf64,linalg_xdsl,10075,12404,12401,0.0,0,9600,9922,0,0.9848138957816377,0.9997984683595325,9924,0,0,0.9850124069478908,0,0,18.938931297709924,18.938931297709924,1,0.0,524,0.7517934002869441,173,0,0,0.0171712158808933,0,2330,12408,1.0021836228287841,2332 +matmul,8x60x20xf64,linalg_xdsl,10053,12407,12404,0.0,0,9600,9922,0,0.9869690639610067,0.9997984683595325,9924,0,0,0.9871680095493882,0,0,19.232558139534884,19.232558139534884,1,0.0,516,0.7759398496240602,149,0,0,0.014821446334427535,0,2355,12411,1.0019894558838158,2357 matmul,8x60x24xf64,baseline,82495,84843,84840,0.0,0,11520,11721,0,0.14208133826292502,0.3353360226589992,34953,0,0,0.4236984059639978,0,0,1.0,1.0,1,0.0,34953,0.42406852456231875,47470,0,0,0.5754288138675071,0,2349,84847,0.9991272198315049,2351 -matmul,8x60x24xf64,linalg_xdsl,12075,14439,14436,0.0,0,11520,11906,0,0.9860041407867495,0.9998320456835741,11908,0,0,0.9861697722567287,0,0,18.961783439490446,18.961783439490446,1,0.0,628,0.7612121212121212,197,0,0,0.01631469979296066,0,2365,14443,1.0024844720496895,2367 +matmul,8x60x24xf64,linalg_xdsl,12037,14407,14404,0.0,0,11520,11906,0,0.9891168895904295,0.9998320456835741,11908,0,0,0.9892830439478275,0,0,19.45751633986928,19.45751633986928,1,0.0,612,0.8042049934296978,149,0,0,0.012378499626152695,0,2371,14411,1.0016615435739802,2373 matmul,8x60x28xf64,baseline,96223,98606,98603,0.0,0,13440,13673,0,0.14209700383484197,0.3353115727002967,40777,0,0,0.42377602028621014,0,0,1.0,1.0,1,0.0,40777,0.42409335316325364,55374,0,0,0.5754757178637124,0,2384,98610,0.9992517381499226,2386 -matmul,8x60x28xf64,linalg_xdsl,14075,16474,16471,0.0,0,13440,13890,0,0.9868561278863233,0.9998560322487763,13892,0,0,0.9869982238010657,0,0,18.97814207650273,18.97814207650273,1,0.0,732,0.7681007345225603,221,0,0,0.015701598579040854,0,2400,16478,1.0026998223801065,2402 +matmul,8x60x28xf64,linalg_xdsl,14027,16428,16425,0.0,0,13440,13890,0,0.9902331218364583,0.9998560322487763,13892,0,0,0.9903757039994296,0,0,19.62146892655367,19.62146892655367,1,0.0,708,0.8261376896149358,149,0,0,0.010622371141370214,0,2402,16432,1.0009980751407999,2404 matmul,8x60x32xf64,baseline,109951,112371,112368,0.0,0,15360,15625,0,0.1421087575374485,0.33529323405077144,46601,0,0,0.4238342534401688,0,0,1.0,1.0,1,0.0,46601,0.4241119777209476,63278,0,0,0.5755109094050986,0,2421,112375,0.9993451628452674,2423 matmul,8x60x32xf64,linalg_xdsl,16075,18471,18468,0.0,0,15360,15874,0,0.9874961119751167,0.9998740236835475,15876,0,0,0.9876205287713842,0,0,18.99043062200957,18.99043062200957,1,0.0,836,0.7733580018501388,245,0,0,0.015241057542768274,0,2397,18475,1.0028615863141523,2399 matmul,8x60x36xf64,baseline,123679,126134,126131,0.0,0,17280,17577,0,0.14211790198821142,0.33527896995708156,52425,0,0,0.42387955918142933,0,0,1.0,1.0,1,0.0,52425,0.42412646532963344,71182,0,0,0.5755382886342871,0,2456,126138,0.9994178478157165,2458 -matmul,8x60x36xf64,linalg_xdsl,18075,20506,20503,0.0,0,17280,17858,0,0.9879944674965422,0.9998880179171332,17860,0,0,0.9881051175656985,0,0,19.0,19.0,1,0.0,940,0.7775020678246485,269,0,0,0.014882434301521438,0,2432,20510,1.00298755186722,2434 +matmul,8x60x36xf64,linalg_xdsl,18021,20488,20485,0.0,0,17280,17858,0,0.9909549969480052,0.9998880179171332,17860,0,0,0.9910659785805449,0,0,19.497816593886462,19.497816593886462,1,0.0,916,0.8230008984725966,197,0,0,0.010931690805171744,0,2468,20492,1.0019976693857167,2470 matmul,8x60x40xf64,baseline,137447,139935,139932,0.0,0,19200,19529,0,0.1420838577779071,0.3352675582413432,58249,0,0,0.4237924436328185,0,0,1.0,1.0,1,0.0,58249,0.42401455868971794,79126,0,0,0.5756837180876992,0,2489,139939,0.9994761617205177,2491 -matmul,8x60x40xf64,linalg_xdsl,20075,22541,22538,0.0,0,19200,19842,0,0.9883935242839352,0.9998992138681717,19844,0,0,0.9884931506849315,0,0,19.007662835249043,19.007662835249043,1,0.0,1044,0.7808526551982049,293,0,0,0.014595267745952677,0,2467,22545,1.0030884184308841,2469 +matmul,8x60x40xf64,linalg_xdsl,20043,22562,22559,0.0,0,19200,19842,0,0.9899715611435413,0.9998992138681717,19844,0,0,0.9900713466047997,0,0,19.303501945525294,19.30350194552529,1,0.0,1028,0.8075412411626081,245,0,0,0.012223719004141096,0,2520,22566,1.0022950656089407,2522 matmul,8x60x44xf64,baseline,151228,153734,153731,0.0,0,21120,21481,0,0.14204380141243686,0.33525822109156744,64073,0,0,0.42368476737112176,0,0,1.0,1.0,1,0.0,64073,0.42390060270854973,87078,0,0,0.5758060676594281,0,2507,153738,0.9994908350305498,2509 matmul,8x60x44xf64,linalg_xdsl,22075,24581,24578,0.0,0,21120,21826,0,0.9887202718006795,0.9999083745647792,21828,0,0,0.9888108720271801,0,0,19.013937282229964,19.013937282229964,1,0.0,1148,0.783617747440273,317,0,0,0.01436013590033975,0,2507,24585,1.0031710079275198,2509 matmul,8x60x48xf64,baseline,164964,167505,167502,0.0,0,23040,23433,0,0.14204917436531606,0.3352504399330443,69897,0,0,0.42371062777333235,0,0,1.0,1.0,1,0.0,69897,0.4239084949086344,94990,0,0,0.5758226037195995,0,2542,167509,0.9995332314929318,2544 -matmul,8x60x48xf64,linalg_xdsl,24075,26616,26613,0.0,0,23040,23810,0,0.9889927310488058,0.9999160087350916,23812,0,0,0.9890758047767394,0,0,19.01916932907348,19.01916932907348,1,0.0,1252,0.7859384808537351,341,0,0,0.014164070612668743,0,2542,26620,1.003239875389408,2544 +matmul,8x60x48xf64,linalg_xdsl,24005,26582,26579,0.0,0,23040,23810,0,0.9918766923557593,0.9999160087350916,23812,0,0,0.9919600083315976,0,0,19.518032786885247,19.518032786885247,1,0.0,1220,0.8327645051194539,245,0,0,0.010206207040199958,0,2578,26586,1.0021662153717976,2580 matmul,8x60x4xf64,baseline,13692,15831,15828,0.0,0,1920,1954,0,0.14271107215892492,0.3353930655681428,5826,0,0,0.4255039439088519,0,0,1.0,1.0,1,0.0,5826,0.42593946483404005,7852,0,0,0.5734735612036226,0,2140,15835,0.9989775051124745,2142 matmul,8x60x4xf64,linalg_xdsl,2055,4241,4238,0.0,0,1920,1986,0,0.9664233576642336,0.9989939637826962,1988,0,0,0.9673965936739659,0,0,18.40740740740741,18.40740740740741,1,0.0,108,0.631578947368421,63,0,0,0.030656934306569343,0,2187,4245,0.9980535279805353,2189 matmul,8x60x52xf64,baseline,178740,181355,181352,0.0,0,24960,25385,0,0.14202193129685578,0.33524385573354815,75721,0,0,0.42363768602439295,0,0,1.0,1.0,1,0.0,75721,0.4237918007555618,102954,0,0,0.5759986572675394,0,2616,181359,0.9996363432919324,2618 matmul,8x60x52xf64,linalg_xdsl,26075,28651,28648,0.0,0,24960,25794,0,0.9892233940556088,0.999922468599783,25796,0,0,0.9893000958772771,0,0,19.023598820058996,19.023598820058996,1,0.0,1356,0.7879140034863451,365,0,0,0.013998082454458294,0,2577,28655,1.0032981783317354,2579 matmul,8x60x56xf64,baseline,192480,195130,195127,0.0,0,26880,27337,0,0.1420251454696592,0.3352382120301674,81545,0,0,0.4236544056525353,0,0,1.0,1.0,1,0.0,81545,0.4237975209832913,110870,0,0,0.5760078969243557,0,2651,195134,0.999662302576891,2653 -matmul,8x60x56xf64,linalg_xdsl,28075,30686,30683,0.0,0,26880,27778,0,0.9894211932324132,0.9999280057595392,27780,0,0,0.9894924309884239,0,0,19.027397260273975,19.027397260273972,1,0.0,1460,0.7896160086533262,389,0,0,0.01385574354407836,0,2612,30690,1.0033481745325021,2614 +matmul,8x60x56xf64,linalg_xdsl,27979,30615,30612,0.0,0,26880,27778,0,0.99281604060188,0.9999280057595392,27780,0,0,0.9928875227849459,0,0,19.674220963172804,19.674220963172804,1,0.0,1412,0.852142426071213,245,0,0,0.008756567425569177,0,2637,30619,1.001644090210515,2639 matmul,8x60x60xf64,baseline,206220,208867,208864,0.0,0,28800,29289,0,0.14202793133546698,0.33523332074305534,87369,0,0,0.42366889729415186,0,0,1.0,1.0,1,0.0,87369,0.42380247871746984,118786,0,0,0.5760159053438075,0,2648,208871,0.9996848026379594,2650 -matmul,8x60x60xf64,linalg_xdsl,30075,32745,32742,0.0,0,28800,29762,0,0.989592684954281,0.999932804730547,29764,0,0,0.9896591853699086,0,0,19.0306905370844,19.0306905370844,1,0.0,1564,0.7910976226605969,413,0,0,0.013732335827098919,0,2671,32749,1.0033915211970075,2673 +matmul,8x60x60xf64,linalg_xdsl,29989,32679,32676,0.0,0,28800,29762,0,0.9924305578712195,0.999932804730547,29764,0,0,0.9924972489912968,0,0,19.53018372703412,19.53018372703412,1,0.0,1524,0.8387451843698404,293,0,0,0.00977024909133349,0,2691,32683,1.0022674980826303,2693 matmul,8x60x64xf64,baseline,220026,222709,222706,0.0,0,30720,31241,0,0.14198776508230845,0.335229040807786,93193,0,0,0.4235544890149346,0,0,1.0,1.0,1,0.0,93193,0.4236835046531399,126766,0,0,0.5761410015180024,0,2684,222713,0.9996954905329369,2686 matmul,8x60x64xf64,linalg_xdsl,32075,34782,34779,0.0,0,30720,31746,0,0.989742790335152,0.9999370039057578,31748,0,0,0.989805144193297,0,0,19.03357314148681,19.033573141486812,1,0.0,1668,0.7923990498812351,437,0,0,0.013624318004676539,0,2708,34786,1.0034294621979736,2710 matmul,8x60x8xf64,baseline,27379,29601,29598,0.0,0,3840,3906,0,0.1426640856130611,0.33527896995708156,11650,0,0,0.4255086014828883,0,0,1.0,1.0,1,3.0,11650,0.4264275256222548,15670,6,2,0.572336462252091,2,2223,29605,0.9978450637349794,2225 matmul,8x60x8xf64,linalg_xdsl,4075,6285,6282,0.0,0,3840,3970,0,0.9742331288343559,0.999496475327291,3972,0,0,0.9747239263803681,0,0,18.735849056603772,18.735849056603772,1,0.0,212,0.6773162939297125,101,0,0,0.024785276073619633,0,2211,6289,0.9995092024539878,2213 matmul,8x64x12xf64,baseline,43631,45880,45877,0.0,0,6144,6242,0,0.14306341821182186,0.3351229464189842,18626,0,0,0.42689830625014324,0,0,1.0,1.0,1,3.7142857142857144,18626,0.4278396692316527,24909,26,7,0.5709014232999473,7,2250,45884,0.9977997295500906,2252 -matmul,8x64x12xf64,linalg_xdsl,6459,8706,8703,0.0,0,6144,6338,0,0.9812664499148475,0.9996845425867508,6340,0,0,0.9815760953708005,0,0,20.063291139240505,20.063291139240505,1,0.0,316,0.7165532879818595,125,0,0,0.01935284099705837,0,2248,8710,1.0009289363678588,2250 +matmul,8x64x12xf64,linalg_xdsl,6437,8705,8702,0.0,0,6144,6338,0,0.9846201646729843,0.9996845425867508,6340,0,0,0.9849308684169644,0,0,20.584415584415584,20.584415584415584,1,0.0,308,0.7530562347188264,101,0,0,0.015690539070995806,0,2269,8709,1.0006214074879602,2271 matmul,8x64x16xf64,baseline,58314,60597,60594,0.0,0,8192,8322,0,0.14271015536577839,0.33510509784972214,24834,0,0,0.42586685873032204,0,0,1.0,1.0,1,3.3,24834,0.4267596920538906,33358,33,10,0.5720410193092568,10,2284,60601,0.9979078780395788,2286 matmul,8x64x16xf64,linalg_xdsl,8581,10849,10846,0.0,0,8192,8450,0,0.9847337140193451,0.9997633696166588,8452,0,0,0.984966787087752,0,0,20.123809523809523,20.123809523809523,1,0.0,420,0.7381370826010545,149,0,0,0.017363943596317447,0,2269,10853,1.0023307306840694,2271 matmul,8x64x20xf64,baseline,73247,75548,75545,0.0,0,10240,10409,0,0.1421082092099335,0.3352442912815228,31049,0,0,0.4238944939724494,0,0,1.0,1.0,1,0.0,31049,0.4243115818243936,42126,0,0,0.5751225306155884,0,2302,75552,0.9990170245880378,2304 -matmul,8x64x20xf64,linalg_xdsl,10715,13037,13034,0.0,0,10240,10562,0,0.9857209519365375,0.9998106777735706,10564,0,0,0.9859076061595894,0,0,20.16030534351145,20.16030534351145,1,0.0,524,0.7517934002869441,173,0,0,0.0161455902939804,0,2323,13041,1.0020531964535697,2325 +matmul,8x64x20xf64,linalg_xdsl,10699,13039,13036,0.0,0,10240,10562,0,0.987195064959342,0.9998106777735706,10564,0,0,0.9873819983175998,0,0,20.472868217054263,20.472868217054263,1,0.0,516,0.7759398496240602,149,0,0,0.013926535190204693,0,2341,13043,1.0013085335078045,2343 matmul,8x64x24xf64,baseline,87877,90208,90205,0.0,0,12288,12489,0,0.14211909828510305,0.3352121748933086,37257,0,0,0.4239675910647837,0,0,1.0,1.0,1,0.0,37257,0.42434424082278843,50542,0,0,0.5751448046701639,0,2332,90212,0.9991123957349477,2334 -matmul,8x64x24xf64,linalg_xdsl,12837,15180,15177,0.0,0,12288,12674,0,0.9873023292046428,0.9998422215209846,12676,0,0,0.9874581288463037,0,0,20.18471337579618,20.18471337579618,1,0.0,628,0.7612121212121212,197,0,0,0.015346264703591182,0,2344,15184,1.002804393549895,2346 +matmul,8x64x24xf64,linalg_xdsl,12811,15202,15199,0.0,0,12288,12674,0,0.9893060651003044,0.9998422215209846,12676,0,0,0.9894621809382562,0,0,20.712418300653592,20.712418300653596,1,0.0,612,0.8042049934296978,149,0,0,0.011630629927406134,0,2392,15206,1.0010928108656623,2394 matmul,8x64x28xf64,baseline,102495,104871,104868,0.0,0,14336,14569,0,0.14214351919605833,0.3351892327159784,43465,0,0,0.4240694668032587,0,0,1.0,1.0,1,0.0,43465,0.42436757368950334,58958,0,0,0.5752280599053612,0,2377,104875,0.9992975267086199,2379 -matmul,8x64x28xf64,linalg_xdsl,14971,17368,17365,0.0,0,14336,14786,0,0.9876427760336651,0.9998647552069245,14788,0,0,0.9877763676441119,0,0,20.202185792349727,20.202185792349727,1,0.0,732,0.7681007345225603,221,0,0,0.014761872954378466,0,2398,17372,1.0025382405984904,2400 +matmul,8x64x28xf64,linalg_xdsl,14923,17319,17316,0.0,0,14336,14786,0,0.9908195403069088,0.9998647552069245,14788,0,0,0.990953561616297,0,0,20.887005649717516,20.887005649717516,1,0.0,708,0.8261376896149358,149,0,0,0.009984587549420358,0,2397,17323,1.0009381491657174,2399 matmul,8x64x32xf64,baseline,117125,119569,119566,0.0,0,16384,16649,0,0.14214727854855924,0.33517202504378635,49673,0,0,0.424102454642476,0,0,1.0,1.0,1,0.0,49673,0.4243850760805488,67374,0,0,0.5752315901814301,0,2445,119573,0.9993340448239061,2447 matmul,8x64x32xf64,linalg_xdsl,17093,19495,19492,0.0,0,16384,16898,0,0.9885918212133622,0.9998816568047337,16900,0,0,0.9887088281752764,0,0,20.215311004784688,20.215311004784688,1,0.0,836,0.7733580018501388,245,0,0,0.014333352834493652,0,2403,19499,1.00304218100977,2405 matmul,8x64x36xf64,baseline,131743,134186,134183,0.0,0,18432,18729,0,0.14216315098335394,0.3351586406828797,55881,0,0,0.42416674889747463,0,0,1.0,1.0,1,0.0,55881,0.42439869067600305,75790,0,0,0.5752867325019166,0,2444,134190,0.9994534813993913,2446 -matmul,8x64x36xf64,linalg_xdsl,19227,21706,21703,0.0,0,18432,19010,0,0.9887137879024289,0.9998948032821376,19012,0,0,0.9888178082904249,0,0,20.225531914893615,20.22553191489362,1,0.0,940,0.7775020678246485,269,0,0,0.013990742185468351,0,2480,21710,1.0028085504758932,2482 +matmul,8x64x36xf64,linalg_xdsl,19173,21689,21686,0.0,0,18432,19010,0,0.9914984613779795,0.9998948032821376,19012,0,0,0.9916027747353049,0,0,20.75545851528384,20.75545851528384,1,0.0,916,0.8230008984725966,197,0,0,0.010274865696552444,0,2517,21693,1.0018776404318572,2519 matmul,8x64x40xf64,baseline,146413,148894,148891,0.0,0,20480,20809,0,0.1421253577209674,0.33514793280613314,62089,0,0,0.42406753498664734,0,0,1.0,1.0,1,0.0,62089,0.42429357296613934,84246,0,0,0.5753997254342169,0,2482,148898,0.9994672604208643,2484 -matmul,8x64x40xf64,linalg_xdsl,21349,23826,23823,0.0,0,20480,21122,0,0.9893671834746358,0.9999053209619391,21124,0,0,0.9894608646775025,0,0,20.233716475095783,20.233716475095786,1,0.0,1044,0.7808526551982049,293,0,0,0.013724296219963465,0,2478,23830,1.003185160897466,2480 +matmul,8x64x40xf64,linalg_xdsl,21317,23836,23833,0.0,0,20480,21122,0,0.9908523713468124,0.9999053209619391,21124,0,0,0.9909461931791528,0,0,20.548638132295718,20.54863813229572,1,0.0,1028,0.8075412411626081,245,0,0,0.011493174461697236,0,2520,23840,1.00243936764085,2522 matmul,8x64x44xf64,baseline,161084,163638,163635,0.0,0,22528,22889,0,0.142093566089742,0.3351391715595121,68297,0,0,0.42398376002582505,0,0,1.0,1.0,1,0.0,68297,0.42418652605166235,92710,0,0,0.5755382285018996,0,2555,163642,0.9995219885277247,2557 matmul,8x64x44xf64,linalg_xdsl,23483,26037,26034,0.0,0,22528,23234,0,0.9893965847634459,0.999913926665519,23236,0,0,0.9894817527573138,0,0,20.2404181184669,20.2404181184669,1,0.0,1148,0.783617747440273,317,0,0,0.013499127028062854,0,2555,26041,1.0029808797853765,2557 matmul,8x64x48xf64,baseline,175710,178262,178259,0.0,0,24576,24969,0,0.14210346593819362,0.3351318703442722,74505,0,0,0.42402253713505206,0,0,1.0,1.0,1,0.0,74505,0.4241939432586157,101134,0,0,0.5755733879688123,0,2553,178266,0.9995959251038644,2555 -matmul,8x64x48xf64,linalg_xdsl,25605,28152,28149,0.0,0,24576,25346,0,0.9898847881273188,0.9999210983115039,25348,0,0,0.9899628978715095,0,0,20.246006389776355,20.24600638977636,1,0.0,1252,0.7859384808537351,341,0,0,0.013317711384495216,0,2548,28156,1.0032806092560047,2550 +matmul,8x64x48xf64,linalg_xdsl,25547,28151,28148,0.0,0,24576,25346,0,0.9921321485888754,0.9999210983115039,25348,0,0,0.992210435667593,0,0,20.777049180327868,20.777049180327868,1,0.0,1220,0.8327645051194539,245,0,0,0.009590167142913062,0,2605,28155,1.0018006028105062,2607 matmul,8x64x4xf64,baseline,14594,16741,16738,0.0,0,2048,2082,0,0.14266136768535015,0.3352657004830918,6210,0,0,0.42551733589146223,0,0,1.0,1.0,1,0.0,6210,0.4261012762453685,8364,0,0,0.5731122379059888,0,2148,16745,0.998629573797451,2150 matmul,8x64x4xf64,linalg_xdsl,2183,4335,4332,0.0,0,2048,2114,0,0.9683921209344938,0.999054820415879,2116,0,0,0.9693082913421897,0,0,19.59259259259259,19.59259259259259,1,0.0,108,0.631578947368421,63,0,0,0.02885936784241869,0,2153,4339,0.9981676591846084,2155 matmul,8x64x52xf64,baseline,190388,193018,193015,0.0,0,26624,27049,0,0.14207302981280331,0.3351256922676644,80713,0,0,0.42393953400424395,0,0,1.0,1.0,1,0.0,80713,0.4240843198142106,109610,0,0,0.5757190579238187,0,2631,193022,0.9996585919280627,2633 matmul,8x64x52xf64,linalg_xdsl,27739,30368,30365,0.0,0,26624,27458,0,0.9898698583222179,0.9999271667880554,27460,0,0,0.9899419589747287,0,0,20.250737463126843,20.250737463126843,1,0.0,1356,0.7879140034863451,365,0,0,0.013158369083240203,0,2630,30372,1.003100328057969,2632 matmul,8x64x56xf64,baseline,205040,207683,207680,0.0,0,28672,29129,0,0.14206496293406165,0.33512039668204463,86921,0,0,0.42392216152945766,0,0,1.0,1.0,1,0.0,86921,0.4240896959879781,118038,0,0,0.5756827936012485,0,2644,207687,0.9996049551307062,2646 -matmul,8x64x56xf64,linalg_xdsl,29861,32483,32480,0.0,0,28672,29570,0,0.9902548474598976,0.9999323684566482,29572,0,0,0.9903218244533003,0,0,20.254794520547943,20.254794520547946,1,0.0,1460,0.7896160086533262,389,0,0,0.013027025216838016,0,2623,32487,1.0033488496701384,2625 +matmul,8x64x56xf64,linalg_xdsl,29764,32434,32431,0.0,0,28672,29570,0,0.9934820588630561,0.9999323684566482,29572,0,0,0.993549254132509,0,0,20.943342776203966,20.943342776203966,1,0.0,1412,0.852142426071213,245,0,0,0.008231420507996237,0,2671,32438,1.0017806746405054,2673 matmul,8x64x60xf64,baseline,219660,222365,222362,0.0,0,30720,31209,0,0.14207866703086589,0.3351158071062719,93129,0,0,0.4239688609669489,0,0,1.0,1.0,1,0.0,93129,0.42409435551811286,126466,0,0,0.5757352271692616,0,2706,222369,0.9997040881362105,2708 -matmul,8x64x60xf64,linalg_xdsl,31995,34699,34696,0.0,0,30720,31682,0,0.9902172214408501,0.9999368766569877,31684,0,0,0.9902797312080013,0,0,20.25831202046036,20.25831202046036,1,0.0,1564,0.7910976226605969,413,0,0,0.012908266916705735,0,2705,34703,1.003187998124707,2707 +matmul,8x64x60xf64,linalg_xdsl,31909,34650,34647,0.0,0,30720,31682,0,0.9928860196182895,0.9999368766569877,31684,0,0,0.9929486978595381,0,0,20.790026246719158,20.79002624671916,1,0.0,1524,0.8387451843698404,293,0,0,0.009182362342912658,0,2742,34654,1.0021310602024507,2744 matmul,8x64x64xf64,baseline,234370,237093,237090,0.0,0,32768,33289,0,0.14203609677006443,0.3351117911754935,99337,0,0,0.423846908734053,0,0,1.0,1.0,1,0.0,99337,0.42398258605604044,134958,0,0,0.5758330844391347,0,2724,237097,0.9996799931731877,2726 matmul,8x64x64xf64,linalg_xdsl,34124,36825,36822,0.0,0,32768,33794,0,0.9903293869417419,0.9999408213989821,33796,0,0,0.9903879967178525,0,0,20.26139088729017,20.26139088729017,1,0.0,1668,0.7923990498812351,437,0,0,0.012806236080178173,0,2702,36829,1.0031942327980308,2704 matmul,8x64x8xf64,baseline,29163,31376,31373,0.0,0,4096,4162,0,0.14271508418201145,0.3351586406828797,12418,0,0,0.4258135308438775,0,0,1.0,1.0,1,3.0,12418,0.42655949436658425,16694,6,2,0.5724376778795048,2,2214,31380,0.9982512087233824,2216 matmul,8x64x8xf64,linalg_xdsl,4325,6510,6507,0.0,0,4096,4226,0,0.9771098265895953,0.9995269631031221,4228,0,0,0.9775722543352601,0,0,19.943396226415093,19.943396226415093,1,0.0,212,0.6773162939297125,101,0,0,0.023352601156069363,0,2186,6514,1.0009248554913295,2188 matmul,8x8x12xf64,baseline,4458,6538,6535,0.0,0,672,769,0,0.17249887842081651,0.3202832153269471,2401,0,0,0.5385823239120682,0,0,1.0,1.0,1,4.0,2401,0.8270754392008267,502,4,1,0.11260655002243158,1,2081,6542,0.6511888739344998,2083 -matmul,8x8x12xf64,linalg_xdsl,1084,3187,3184,0.0,0,768,962,0,0.8874538745387454,0.9979253112033195,964,0,0,0.8892988929889298,0,0,3.050632911392405,3.050632911392405,1,0.0,316,0.7198177676537585,123,0,0,0.11346863468634687,0,2104,3191,1.0027675276752768,2106 +matmul,8x8x12xf64,linalg_xdsl,1059,3174,3171,0.0,0,768,962,0,0.9084041548630784,0.9979253112033195,964,0,0,0.9102927289896129,0,0,3.12987012987013,3.1298701298701297,1,0.0,308,0.7567567567567568,99,0,0,0.09348441926345609,0,2116,3178,1.003777148253069,2118 matmul,8x8x16xf64,baseline,5930,8020,8017,0.0,0,896,1025,0,0.17284991568296795,0.3202124336144955,3201,0,0,0.5397976391231029,0,0,1.0,1.0,1,4.0,3201,0.8355520751761942,630,4,1,0.10623946037099494,1,2091,8024,0.6460370994940978,2093 matmul,8x8x16xf64,linalg_xdsl,1420,3528,3525,0.0,0,1024,1282,0,0.9028169014084507,0.9984423676012462,1284,0,0,0.9042253521126761,0,0,3.057142857142857,3.057142857142857,1,0.0,420,0.7407407407407407,147,0,0,0.10352112676056338,0,2109,3532,1.0077464788732395,2111 matmul,8x8x20xf64,baseline,7402,9497,9494,0.0,0,1120,1281,0,0.1730613347743853,0.3201699575106223,4001,0,0,0.5405295865982167,0,0,1.0,1.0,1,4.0,4001,0.8407228409329691,758,4,1,0.10240475547149419,1,2096,9501,0.6429343420697109,2098 -matmul,8x8x20xf64,linalg_xdsl,1760,3878,3875,0.0,0,1280,1602,0,0.9102272727272728,0.9987531172069826,1604,0,0,0.9113636363636364,0,0,3.061068702290076,3.0610687022900764,1,0.0,524,0.753956834532374,171,0,0,0.0971590909090909,0,2119,3882,1.0085227272727273,2121 +matmul,8x8x20xf64,linalg_xdsl,1732,3826,3823,0.0,0,1280,1602,0,0.9249422632794457,0.9987531172069826,1604,0,0,0.9260969976905312,0,0,3.108527131782946,3.108527131782946,1,0.0,516,0.7782805429864253,147,0,0,0.0848729792147806,0,2095,3830,1.0109699769053118,2097 matmul,8x8x24xf64,baseline,8868,10973,10970,0.0,0,1344,1537,0,0.17331980153360396,0.32014163715892524,4801,0,0,0.5413847541723049,0,0,1.0,1.0,1,4.0,4801,0.8442060840513451,886,4,1,0.09990978800180424,1,2106,10977,0.6412945421741092,2108 -matmul,8x8x24xf64,linalg_xdsl,2092,4236,4233,0.0,0,1536,1922,0,0.9187380497131931,0.998960498960499,1924,0,0,0.9196940726577438,0,0,3.0636942675159236,3.0636942675159236,1,0.0,628,0.7630619684082625,195,0,0,0.09321223709369025,0,2145,4240,1.0129063097514341,2147 +matmul,8x8x24xf64,linalg_xdsl,2051,4167,4164,0.0,0,1536,1922,0,0.9371038517796197,0.998960498960499,1924,0,0,0.9380789858605558,0,0,3.1437908496732025,3.1437908496732025,1,0.0,612,0.8063241106719368,147,0,0,0.07167235494880546,0,2117,4171,1.0097513408093612,2119 matmul,8x8x28xf64,baseline,10340,12455,12452,0.0,0,1568,1793,0,0.17340425531914894,0.3201214068916265,5601,0,0,0.5416827852998066,0,0,1.0,1.0,1,4.0,5601,0.8467120181405896,1014,4,1,0.09806576402321084,1,2116,12459,0.6397485493230175,2118 -matmul,8x8x28xf64,linalg_xdsl,2428,4577,4574,0.0,0,1792,2242,0,0.9233937397034596,0.9991087344028521,2244,0,0,0.9242174629324547,0,0,3.0655737704918034,3.0655737704918034,1,0.0,732,0.7697160883280757,219,0,0,0.09019769357495881,0,2150,4581,1.0144151565074135,2152 +matmul,8x8x28xf64,linalg_xdsl,2377,4549,4546,0.0,0,1792,2242,0,0.9432057214976861,0.9991087344028521,2244,0,0,0.944047118216239,0,0,3.1694915254237284,3.169491525423729,1,0.0,708,0.8280701754385965,147,0,0,0.06184265881363063,0,2173,4553,1.0058897770298696,2175 matmul,8x8x32xf64,baseline,11812,13934,13931,0.0,0,1792,2049,0,0.17346766000677277,0.3201062334010311,6401,0,0,0.5419065357263799,0,0,1.0,1.0,1,4.0,6401,0.8486013522471165,1142,4,1,0.09668134100914325,1,2123,13938,0.6385878767355232,2125 matmul,8x8x32xf64,linalg_xdsl,2764,4923,4920,0.0,0,2048,2562,0,0.926917510853835,0.999219968798752,2564,0,0,0.9276410998552822,0,0,3.0669856459330145,3.0669856459330145,1,0.0,836,0.7747914735866543,243,0,0,0.08791606367583213,0,2160,4927,1.0155571635311142,2162 matmul,8x8x36xf64,baseline,13284,15411,15408,0.0,0,2016,2305,0,0.17351701294790725,0.3200944313289821,7201,0,0,0.5420806985847636,0,0,1.0,1.0,1,4.0,7201,0.8500767323810648,1270,4,1,0.09560373381511593,1,2128,15415,0.6376844323998795,2130 -matmul,8x8x36xf64,linalg_xdsl,3099,5230,5227,0.0,0,2304,2882,0,0.9299774120684091,0.9993065187239945,2884,0,0,0.930622781542433,0,0,3.068085106382979,3.068085106382979,1,0.0,940,0.7781456953642384,268,0,0,0.08647950951919975,0,2132,5234,1.0171022910616327,2134 +matmul,8x8x36xf64,linalg_xdsl,3044,5223,5220,0.0,0,2304,2882,0,0.9467805519053877,0.9993065187239945,2884,0,0,0.9474375821287779,0,0,3.148471615720524,3.148471615720524,1,0.0,916,0.8237410071942446,196,0,0,0.06438896189224705,0,2180,5227,1.011826544021025,2182 matmul,8x8x40xf64,baseline,14756,16893,16890,0.0,0,2240,2561,0,0.17355651938194633,0.32008498937632796,8001,0,0,0.5422201138519924,0,0,1.0,1.0,1,4.0,8001,0.8512607724225981,1398,4,1,0.09474112225535375,1,2138,16897,0.6369612361073462,2140 -matmul,8x8x40xf64,linalg_xdsl,3430,5567,5564,0.0,0,2560,3202,0,0.933527696793003,0.9993757802746567,3204,0,0,0.9341107871720117,0,0,3.068965517241379,3.0689655172413794,1,0.0,1044,0.7808526551982049,293,0,0,0.08542274052478134,0,2138,5571,1.019533527696793,2140 +matmul,8x8x40xf64,linalg_xdsl,3397,5567,5564,0.0,0,2560,3202,0,0.9425964085958198,0.9993757802746567,3204,0,0,0.9431851633794525,0,0,3.1167315175097277,3.1167315175097277,1,0.0,1028,0.8075412411626081,245,0,0,0.07212246099499559,0,2171,5571,1.015307624374448,2173 matmul,8x8x44xf64,baseline,16228,18370,18367,0.0,0,2464,2817,0,0.1735888587626325,0.3200772639472787,8801,0,0,0.5423342371210254,0,0,1.0,1.0,1,4.0,8801,0.8522320131693618,1526,4,1,0.09403500123243776,1,2143,18374,0.6363692383534632,2145 matmul,8x8x44xf64,linalg_xdsl,3766,5908,5905,0.0,0,2816,3522,0,0.9352097716409984,0.9994324631101021,3524,0,0,0.935740839086564,0,0,3.0696864111498257,3.0696864111498257,1,0.0,1148,0.783617747440273,317,0,0,0.08417419012214551,0,2143,5912,1.0199150292087096,2145 matmul,8x8x48xf64,baseline,17700,19852,19849,0.0,0,2688,3073,0,0.17361581920903954,0.32007082595562963,9601,0,0,0.5424293785310734,0,0,1.0,1.0,1,4.0,9601,0.8530430919591293,1654,4,1,0.09344632768361581,1,2153,19856,0.6358757062146893,2155 -matmul,8x8x48xf64,linalg_xdsl,4102,6254,6251,0.0,0,3072,3842,0,0.9366162847391516,0.9994797086368367,3844,0,0,0.9371038517796197,0,0,3.070287539936102,3.070287539936102,1,0.0,1252,0.7859384808537351,341,0,0,0.08313018039980498,0,2153,6258,1.0202340321794248,2155 +matmul,8x8x48xf64,linalg_xdsl,4043,6244,6241,0.0,0,3072,3842,0,0.9502844422458571,0.9994797086368367,3844,0,0,0.950779124412565,0,0,3.1508196721311474,3.1508196721311474,1,0.0,1220,0.8327645051194539,245,0,0,0.060598565421716544,0,2202,6248,1.0113776898342814,2204 matmul,8x8x4xf64,baseline,1492,3611,3608,0.0,0,224,257,0,0.1722520107238606,0.3208489388264669,801,0,0,0.5368632707774799,0,0,1.0,1.0,1,0.0,801,0.9513064133016627,41,0,0,0.027479892761394103,0,2120,3615,0.5643431635388739,2122 matmul,8x8x4xf64,linalg_xdsl,391,2465,2462,0.0,0,256,322,0,0.8235294117647058,0.9938271604938271,324,0,0,0.8286445012787724,0,0,3.0,3.0,1,0.0,108,0.631578947368421,63,0,0,0.16112531969309463,0,2075,2469,0.989769820971867,2077 matmul,8x8x52xf64,baseline,19172,21329,21326,0.0,0,2912,3329,0,0.17363863968287085,0.32006537832900683,10401,0,0,0.5425099102858335,0,0,1.0,1.0,1,4.0,10401,0.8537306082245752,1782,4,1,0.09294804923847277,1,2158,21333,0.6354579595243063,2160 matmul,8x8x52xf64,linalg_xdsl,4450,6607,6604,0.0,0,3328,4162,0,0.9352808988764045,0.9995196926032661,4164,0,0,0.9357303370786517,0,0,3.070796460176991,3.0707964601769913,1,0.0,1356,0.7879140034863451,365,0,0,0.08202247191011236,0,2158,6611,1.0177528089887642,2160 matmul,8x8x56xf64,baseline,20650,22821,22818,0.0,0,3136,3585,0,0.17360774818401936,0.3200607088652799,11201,0,0,0.5424213075060532,0,0,1.0,1.0,1,4.0,11201,0.8543207993288079,1910,4,1,0.09249394673123487,1,2172,22825,0.6349152542372881,2174 -matmul,8x8x56xf64,linalg_xdsl,4780,6951,6948,0.0,0,3584,4482,0,0.9376569037656903,0.9995539696699376,4484,0,0,0.9380753138075314,0,0,3.0712328767123287,3.0712328767123287,1,0.0,1460,0.7896160086533262,389,0,0,0.08138075313807532,0,2172,6955,1.0194560669456068,2174 +matmul,8x8x56xf64,linalg_xdsl,4676,6900,6897,0.0,0,3584,4482,0,0.9585115483319077,0.9995539696699376,4484,0,0,0.9589392643284859,0,0,3.1756373937677056,3.1756373937677056,1,0.0,1412,0.852142426071213,245,0,0,0.05239520958083832,0,2225,6904,1.0113344739093242,2227 matmul,8x8x60xf64,baseline,22115,24296,24293,0.0,0,3360,3841,0,0.17368302057427085,0.32005666194483795,12001,0,0,0.5426633506669681,0,0,1.0,1.0,1,4.0,12001,0.8548329653109196,2038,4,1,0.09215464616775944,1,2182,24300,0.6348179968347276,2184 -matmul,8x8x60xf64,linalg_xdsl,5109,7290,7287,0.0,0,3840,4802,0,0.9399099628107261,0.9995836802664446,4804,0,0,0.9403014288510472,0,0,3.0716112531969313,3.071611253196931,1,0.0,1564,0.7910976226605969,413,0,0,0.08083773732628695,0,2182,7294,1.0211391661773341,2184 +matmul,8x8x60xf64,linalg_xdsl,5035,7260,7257,0.0,0,3840,4802,0,0.9537239324726912,0.9995836802664446,4804,0,0,0.9541211519364449,0,0,3.152230971128609,3.152230971128609,1,0.0,1524,0.8387451843698404,293,0,0,0.058192651439920556,0,2226,7264,1.0123138033763655,2228 matmul,8x8x64xf64,baseline,23596,25800,25797,0.0,0,3584,4097,0,0.17363112391930835,0.3200531208499336,12801,0,0,0.542507204610951,0,0,1.0,1.0,1,3.0,12801,0.8543682840552627,2182,3,1,0.09247330055941685,1,2205,25804,0.6349805051703679,2207 matmul,8x8x64xf64,linalg_xdsl,5452,7647,7644,0.0,0,4096,5122,0,0.9394717534849596,0.9996096799375488,5124,0,0,0.9398385913426266,0,0,3.0719424460431655,3.0719424460431655,1,0.0,1668,0.7923990498812351,437,0,0,0.0801540719002201,0,2196,7651,1.0199926632428467,2198 matmul,8x8x8xf64,baseline,2976,5066,5063,0.0,0,448,513,0,0.17237903225806453,0.3204247345409119,1601,0,0,0.5379704301075269,0,0,1.0,1.0,1,0.0,1601,0.9744370054777846,42,0,0,0.014112903225806451,0,2091,5070,0.5520833333333334,2093 @@ -1743,13 +2130,13 @@ matmul_transb,1x4x40xf32,snitch_stream,295,2693,2690,0.0,0,0,162,0,0.54915254237 matmul_transb,1x8x40xf32,snitch_stream,336,2787,2784,0.0,0,0,242,0,0.7202380952380952,0.852112676056338,284,0,0,0.8452380952380952,0,0,1.327102803738318,1.3271028037383177,1,0.0,214,0.7062706270627063,89,0,0,0.2648809523809524,0,2452,2791,1.1101190476190477,2454 pooling_nchw_max_d1_s2_3x3,12x12xf64,baseline,4761,6940,6937,0.0,0,0,1522,0,0.3196807393404747,0.4737005913476502,3213,0,0,0.6748582230623819,0,0,1.0,1.0,1,0.0,3213,0.8101361573373677,753,0,0,0.1581600504095778,0,2180,6944,0.8330182734719597,2182 pooling_nchw_max_d1_s2_3x3,12x12xf64,linalg,4532,6636,6633,0.0,0,0,1297,0,0.2861871138570168,0.4501909059354391,2881,0,0,0.6357016769638129,0,0,1.0,1.0,1,0.0,2881,0.7446368570690101,988,0,0,0.21800529567519858,288,2105,6640,0.8537069726390114,2107 -pooling_nchw_max_d1_s2_3x3,12x12xf64,linalg_xdsl,2211,4341,4338,0.0,0,0,1586,0,0.7173224785165083,0.9850931677018634,1610,0,0,0.7281772953414745,0,0,3.259109311740891,3.2591093117408905,1,0.0,494,0.45614035087719296,589,0,0,0.2663952962460425,0,2131,4345,0.994572591587517,2133 +pooling_nchw_max_d1_s2_3x3,12x12xf64,linalg_xdsl,2223,4360,4357,0.0,0,0,1586,0,0.7134502923976608,0.9850931677018634,1610,0,0,0.7242465137201979,0,0,3.3402489626556013,3.340248962655602,1,0.0,482,0.46570048309178746,553,0,0,0.24876293297345928,0,2138,4364,0.9730094466936572,2140 pooling_nchw_max_d1_s2_3x3,12x16xf64,baseline,6221,8428,8425,0.0,0,0,1990,0,0.31988426298022826,0.4736967388716972,4201,0,0,0.6752933611959492,0,0,1.0,1.0,1,0.0,4201,0.8138318481208834,961,0,0,0.15447677222311526,0,2208,8432,0.8297701334190645,2210 pooling_nchw_max_d1_s2_3x3,12x16xf64,linalg,6026,8134,8131,0.0,0,0,1729,0,0.28692333222701627,0.4501431918771153,3841,0,0,0.6374045801526718,0,0,1.0,1.0,1,0.0,3841,0.7506351377760406,1276,0,0,0.21174908728841685,384,2109,8138,0.8491536674410887,2111 pooling_nchw_max_d1_s2_3x3,12x16xf64,linalg_xdsl,2739,4866,4863,0.0,0,0,2114,0,0.7718145308506754,0.9887745556594949,2138,0,0,0.7805768528660095,0,0,3.2892307692307687,3.289230769230769,1,0.0,650,0.5098039215686274,625,0,0,0.22818546914932458,0,2128,4870,1.0087623220153341,2130 pooling_nchw_max_d1_s2_3x3,12x20xf64,baseline,7677,9899,9896,0.0,0,0,2458,0,0.32017715253354173,0.4736943534399692,5189,0,0,0.6759150709912727,0,0,1.0,1.0,1,0.0,5189,0.8161371500471847,1169,0,0,0.15227302331639964,0,2223,9903,0.8281880943076723,2225 pooling_nchw_max_d1_s2_3x3,12x20xf64,linalg,7515,9664,9661,0.0,0,0,2161,0,0.28755821689953426,0.45011455946677775,4801,0,0,0.638855622089155,0,0,1.0,1.0,1,0.0,4801,0.754281225451689,1564,0,0,0.2081170991350632,480,2150,9668,0.8469727212242182,2152 -pooling_nchw_max_d1_s2_3x3,12x20xf64,linalg_xdsl,3267,5409,5406,0.0,0,0,2642,0,0.8086929905111724,0.9909977494373593,2666,0,0,0.8160391796755433,0,0,3.307692307692308,3.3076923076923075,1,0.0,806,0.5494205862304021,661,0,0,0.20232629323538415,0,2143,5413,1.0183654729109275,2145 +pooling_nchw_max_d1_s2_3x3,12x20xf64,linalg_xdsl,3271,5425,5422,0.0,0,0,2642,0,0.8077040660348517,0.9909977494373593,2666,0,0,0.8150412717823295,0,0,3.3576826196473553,3.3576826196473553,1,0.0,794,0.5595489781536294,625,0,0,0.19107306634056864,0,2155,5429,1.0061143381228983,2157 pooling_nchw_max_d1_s2_3x3,12x4xf64,baseline,1790,3925,3922,0.0,0,0,586,0,0.32737430167597764,0.4737267582861762,1237,0,0,0.6910614525139664,0,0,1.0,1.0,1,0.0,1237,0.9508070714834742,64,0,0,0.035754189944134075,0,2136,3929,0.7268156424581005,2138 pooling_nchw_max_d1_s2_3x3,12x4xf64,linalg,1155,3230,3227,0.0,0,0,433,0,0.3748917748917749,0.5812080536912752,745,0,0,0.645021645021645,0,0,1.0,1.0,1,0.0,745,0.8268590455049944,156,0,0,0.13506493506493505,96,2076,3234,0.7800865800865802,2078 pooling_nchw_max_d1_s2_3x3,12x4xf64,linalg_xdsl,582,2665,2662,0.0,0,0,530,0,0.9106529209621993,0.9962406015037594,532,0,0,0.9140893470790378,0,0,3.325,3.325,1,0.0,160,0.6866952789699571,73,0,0,0.1254295532646048,0,2084,2669,1.0395189003436425,2086 @@ -1758,13 +2145,13 @@ pooling_nchw_max_d1_s2_3x3,12x8xf64,linalg,2739,4833,4830,0.0,0,0,865,0,0.315808 pooling_nchw_max_d1_s2_3x3,12x8xf64,linalg_xdsl,1683,3798,3795,0.0,0,0,1058,0,0.6286393345216874,0.977818853974122,1082,0,0,0.6428995840760546,0,0,3.201183431952663,3.201183431952663,1,0.0,338,0.3793490460157127,553,0,0,0.3285799168152109,0,2116,3802,0.9714795008912656,2118 pooling_nchw_max_d1_s2_3x3,16x12xf64,baseline,6221,8428,8425,0.0,0,0,1990,0,0.31988426298022826,0.4736967388716972,4201,0,0,0.6752933611959492,0,0,1.0,1.0,1,0.0,4201,0.810690852952528,981,0,0,0.15769168943899695,0,2208,8432,0.8329850506349461,2210 pooling_nchw_max_d1_s2_3x3,16x12xf64,linalg,6039,8173,8170,0.0,0,0,1729,0,0.2863056797483027,0.4501431918771153,3841,0,0,0.6360324557045869,0,0,1.0,1.0,1,0.0,3841,0.745391034348923,1312,0,0,0.21725451233647955,384,2135,8177,0.8532869680410664,2137 -pooling_nchw_max_d1_s2_3x3,16x12xf64,linalg_xdsl,2939,5066,5063,0.0,0,0,2114,0,0.7192922762844505,0.9850885368126747,2146,0,0,0.7301803334467506,0,0,3.2613981762917934,3.2613981762917934,1,0.0,658,0.4572619874913134,781,0,0,0.26573664511738687,0,2128,5070,0.9959169785641375,2130 +pooling_nchw_max_d1_s2_3x3,16x12xf64,linalg_xdsl,2944,5070,5067,0.0,0,0,2114,0,0.7180706521739131,0.9850885368126747,2146,0,0,0.7289402173913043,0,0,3.3426791277258565,3.3426791277258565,1,0.0,642,0.4669090909090909,733,0,0,0.24898097826086957,0,2127,5074,0.9779211956521738,2129 pooling_nchw_max_d1_s2_3x3,16x16xf64,baseline,8121,10354,10351,0.0,0,0,2602,0,0.32040389114641055,0.4736937920990351,5493,0,0,0.6763945326930181,0,0,1.0,1.0,1,0.0,5493,0.8142603024014231,1253,0,0,0.154291343430612,0,2234,10358,0.8306858761236301,2236 pooling_nchw_max_d1_s2_3x3,16x16xf64,linalg,8024,10151,10148,0.0,0,0,2305,0,0.2872632103688933,0.45010740089826207,5121,0,0,0.6382103688933201,0,0,1.0,1.0,1,0.0,5121,0.7511000293341156,1697,0,0,0.21149052841475574,512,2128,10155,0.8497008973080757,2130 pooling_nchw_max_d1_s2_3x3,16x16xf64,linalg_xdsl,3643,5798,5795,0.0,0,0,2818,0,0.7735382926159758,0.9887719298245614,2850,0,0,0.7823222618720834,0,0,3.2909930715935336,3.2909930715935336,1,0.0,866,0.5109144542772861,829,0,0,0.2275597035410376,0,2156,5802,1.009881965413121,2158 pooling_nchw_max_d1_s2_3x3,16x20xf64,baseline,10025,12273,12270,0.0,0,0,3214,0,0.32059850374064836,0.4736919675755343,6785,0,0,0.6768079800498753,0,0,1.0,1.0,1,0.0,6785,0.8164861612515042,1525,0,0,0.15211970074812967,0,2249,12277,0.8289276807980049,2251 pooling_nchw_max_d1_s2_3x3,16x20xf64,linalg,9999,12161,12158,0.0,0,0,2881,0,0.2881288128812881,0.4500859240743634,6401,0,0,0.6401640164016401,0,0,1.0,1.0,1,0.0,6401,0.7548349056603774,2079,0,0,0.2079207920792079,640,2163,12165,0.848084808480848,2165 -pooling_nchw_max_d1_s2_3x3,16x20xf64,linalg_xdsl,4347,6517,6514,0.0,0,0,3522,0,0.8102139406487232,0.9909960607765897,3554,0,0,0.8175753393144698,0,0,3.3091247672253257,3.3091247672253257,1,0.0,1074,0.5504869297796002,877,0,0,0.2017483321831148,0,2171,6521,1.0193236714975846,2173 +pooling_nchw_max_d1_s2_3x3,16x20xf64,linalg_xdsl,4351,6522,6519,0.0,0,0,3522,0,0.8094690875660767,0.9909960607765897,3554,0,0,0.8168237186853596,0,0,3.3591682419659734,3.3591682419659734,1,0.0,1058,0.5606783253842077,829,0,0,0.19053091243392323,0,2172,6526,1.007354631119283,2174 pooling_nchw_max_d1_s2_3x3,16x4xf64,baseline,2334,4474,4471,0.0,0,0,766,0,0.3281919451585261,0.47371675943104513,1617,0,0,0.6928020565552699,0,0,1.0,1.0,1,0.0,1617,0.952857984678845,80,0,0,0.03427592116538132,0,2141,4478,0.7270779777206513,2143 pooling_nchw_max_d1_s2_3x3,16x4xf64,linalg,1527,3607,3604,0.0,0,0,577,0,0.37786509495743287,0.581067472306143,993,0,0,0.650294695481336,0,0,1.0,1.0,1,0.0,993,0.8295739348370927,204,0,0,0.13359528487229863,128,2081,3611,0.7838899803536347,2083 pooling_nchw_max_d1_s2_3x3,16x4xf64,linalg_xdsl,758,2846,2843,0.0,0,0,706,0,0.9313984168865436,0.9971751412429378,708,0,0,0.9340369393139841,0,0,3.339622641509434,3.339622641509434,1,0.0,212,0.7138047138047138,85,0,0,0.11213720316622691,0,2089,2850,1.0461741424802111,2091 @@ -1773,13 +2160,13 @@ pooling_nchw_max_d1_s2_3x3,16x8xf64,linalg,3639,5748,5745,0.0,0,0,1153,0,0.31684 pooling_nchw_max_d1_s2_3x3,16x8xf64,linalg_xdsl,2235,4360,4357,0.0,0,0,1410,0,0.6308724832214765,0.9778085991678225,1442,0,0,0.6451901565995526,0,0,3.2044444444444444,3.2044444444444444,1,0.0,450,0.3803888419273035,733,0,0,0.32796420581655483,0,2126,4364,0.9731543624161074,2128 pooling_nchw_max_d1_s2_3x3,20x12xf64,baseline,7677,9899,9896,0.0,0,0,2458,0,0.32017715253354173,0.4736943534399692,5189,0,0,0.6759150709912727,0,0,1.0,1.0,1,0.0,5189,0.8110346983432323,1209,0,0,0.15748339194998046,0,2223,9903,0.8333984629412532,2225 pooling_nchw_max_d1_s2_3x3,20x12xf64,linalg,7539,9688,9685,0.0,0,0,2161,0,0.2866427908210638,0.45011455946677775,4801,0,0,0.6368218596630852,0,0,1.0,1.0,1,0.0,4801,0.7458443374242659,1636,0,0,0.21700490781270726,480,2150,9692,0.8538267674757924,2152 -pooling_nchw_max_d1_s2_3x3,20x12xf64,linalg_xdsl,3667,5809,5806,0.0,0,0,2642,0,0.720479956367603,0.9850857568978374,2682,0,0,0.7313880556313063,0,0,3.2627737226277373,3.2627737226277373,1,0.0,822,0.45793871866295266,973,0,0,0.26533951458958277,0,2143,5813,0.9967275702208891,2145 +pooling_nchw_max_d1_s2_3x3,20x12xf64,linalg_xdsl,3672,5813,5810,0.0,0,0,2642,0,0.7194989106753813,0.9850857568978374,2682,0,0,0.7303921568627451,0,0,3.344139650872818,3.344139650872818,1,0.0,802,0.46763848396501456,913,0,0,0.24863834422657952,0,2142,5817,0.9790305010893245,2144 pooling_nchw_max_d1_s2_3x3,20x16xf64,baseline,10025,12273,12270,0.0,0,0,3214,0,0.32059850374064836,0.4736919675755343,6785,0,0,0.6768079800498753,0,0,1.0,1.0,1,0.0,6785,0.8145258103241296,1545,0,0,0.1541147132169576,0,2249,12277,0.8309226932668329,2251 pooling_nchw_max_d1_s2_3x3,20x16xf64,linalg,10017,12189,12186,0.0,0,0,2881,0,0.28761106119596686,0.4500859240743634,6401,0,0,0.6390136767495258,0,0,1.0,1.0,1,0.0,6401,0.7516439643024895,2115,0,0,0.21114106019766396,640,2173,12193,0.8501547369471898,2175 pooling_nchw_max_d1_s2_3x3,20x16xf64,linalg_xdsl,4547,6717,6714,0.0,0,0,3522,0,0.7745766439410601,0.9887703537338574,3562,0,0,0.7833736529579943,0,0,3.292051756007394,3.292051756007394,1,0.0,1082,0.5115839243498818,1033,0,0,0.2271827578623268,0,2171,6721,1.010556410820321,2173 pooling_nchw_max_d1_s2_3x3,20x20xf64,baseline,12377,14627,14624,0.0,0,0,3970,0,0.32075624141552883,0.47369049039494093,8381,0,0,0.67714308798578,0,0,1.0,1.0,1,0.0,8381,0.8167023971935296,1881,0,0,0.15197543831299992,0,2251,14631,0.8291185262987799,2253 pooling_nchw_max_d1_s2_3x3,20x20xf64,linalg,12491,14676,14673,0.0,0,0,3601,0,0.28828756704827474,0.45006874140732406,8001,0,0,0.6405411896565527,0,0,1.0,1.0,1,0.0,8001,0.7550962627406569,2595,0,0,0.20774957969738211,800,2186,14680,0.8482907693539348,2188 -pooling_nchw_max_d1_s2_3x3,20x20xf64,linalg_xdsl,5426,7633,7630,0.0,0,0,4402,0,0.8112790269074824,0.9909950472760019,4442,0,0,0.8186509399189089,0,0,3.3099850968703426,3.3099850968703426,1,0.0,1342,0.551129363449692,1093,0,0,0.20143752303722817,0,2208,7637,1.020088462956137,2210 +pooling_nchw_max_d1_s2_3x3,20x20xf64,linalg_xdsl,5429,7623,7620,0.0,0,0,4402,0,0.8108307238902192,0.9909950472760019,4442,0,0,0.8181985632713207,0,0,3.3600605143721634,3.3600605143721634,1,0.0,1322,0.5613588110403397,1033,0,0,0.19027445201694604,0,2195,7627,1.0084730152882666,2197 pooling_nchw_max_d1_s2_3x3,20x4xf64,baseline,2878,5023,5020,0.0,0,0,946,0,0.32870048644892286,0.47371056584877314,1997,0,0,0.6938846421125782,0,0,1.0,1.0,1,0.0,1997,0.9541328236980411,96,0,0,0.03335649756775538,0,2146,5027,0.7272411396803335,2148 pooling_nchw_max_d1_s2_3x3,20x4xf64,linalg,1899,3989,3986,0.0,0,0,721,0,0.3796735123749342,0.580983078162772,1241,0,0,0.6535018430753028,0,0,1.0,1.0,1,0.0,1241,0.8312123241795043,252,0,0,0.13270142180094788,160,2091,3993,0.7862032648762507,2093 pooling_nchw_max_d1_s2_3x3,20x4xf64,linalg_xdsl,934,3032,3029,0.0,0,0,882,0,0.9443254817987152,0.997737556561086,884,0,0,0.9464668094218416,0,0,3.348484848484848,3.3484848484848486,1,0.0,264,0.7313019390581718,97,0,0,0.10385438972162742,0,2099,3036,1.050321199143469,2101 @@ -1788,13 +2175,13 @@ pooling_nchw_max_d1_s2_3x3,20x8xf64,linalg,4539,6653,6650,0.0,0,0,1441,0,0.31747 pooling_nchw_max_d1_s2_3x3,20x8xf64,linalg_xdsl,2787,4922,4919,0.0,0,0,1762,0,0.6322210261930391,0.9778024417314095,1802,0,0,0.6465733763903839,0,0,3.206405693950178,3.206405693950178,1,0.0,562,0.38101694915254236,913,0,0,0.32759239325439543,0,2136,4926,0.9741657696447794,2138 pooling_nchw_max_d1_s2_3x3,4x12xf64,baseline,1851,3992,3989,0.0,0,0,586,0,0.3165856293895192,0.4737267582861762,1237,0,0,0.6682874122096164,0,0,1.0,1.0,1,0.0,1237,0.8116797900262467,287,0,0,0.15505132360886006,0,2142,3996,0.8233387358184765,2144 pooling_nchw_max_d1_s2_3x3,4x12xf64,linalg,1482,3631,3628,0.0,0,0,433,0,0.2921727395411606,0.4557894736842105,950,0,0,0.6410256410256411,0,0,1.0,1.0,1,0.0,950,0.7474429583005507,321,0,0,0.2165991902834008,96,2150,3635,0.8576248313090419,2152 -pooling_nchw_max_d1_s2_3x3,4x12xf64,linalg_xdsl,755,2860,2857,0.0,0,0,530,0,0.7019867549668874,0.9851301115241635,538,0,0,0.7125827814569536,0,0,3.240963855421687,3.2409638554216866,1,0.0,166,0.4474393530997305,205,0,0,0.271523178807947,0,2106,2864,0.9841059602649007,2108 +pooling_nchw_max_d1_s2_3x3,4x12xf64,linalg_xdsl,767,2879,2876,0.0,0,0,530,0,0.6910039113428944,0.9851301115241635,538,0,0,0.7014341590612777,0,0,3.3209876543209877,3.3209876543209877,1,0.0,162,0.4563380281690141,193,0,0,0.2516297262059974,0,2113,2883,0.953063885267275,2115 pooling_nchw_max_d1_s2_3x3,4x16xf64,baseline,2411,4557,4554,0.0,0,0,766,0,0.3177104935711323,0.47371675943104513,1617,0,0,0.6706760680215678,0,0,1.0,1.0,1,0.0,1617,0.8150201612903226,367,0,0,0.15221899626710908,0,2147,4561,0.8228950642886769,2149 pooling_nchw_max_d1_s2_3x3,4x16xf64,linalg,2000,4089,4086,0.0,0,0,577,0,0.2885,0.4557661927330174,1266,0,0,0.633,0,0,1.0,1.0,1,0.0,1266,0.7576301615798923,405,0,0,0.2025,128,2090,4093,0.8355,2092 pooling_nchw_max_d1_s2_3x3,4x16xf64,linalg_xdsl,931,3041,3038,0.0,0,0,706,0,0.7583243823845328,0.988795518207283,714,0,0,0.7669172932330827,0,0,3.275229357798165,3.2752293577981653,1,0.0,218,0.5011494252873563,217,0,0,0.23308270676691728,0,2111,3045,1.0,2113 pooling_nchw_max_d1_s2_3x3,4x20xf64,baseline,2971,5127,5124,0.0,0,0,946,0,0.3184113093234601,0.47371056584877314,1997,0,0,0.6721642544597779,0,0,1.0,1.0,1,0.0,1997,0.8171031096563012,447,0,0,0.15045439246045103,0,2157,5131,0.8226186469202289,2159 pooling_nchw_max_d1_s2_3x3,4x20xf64,linalg,2494,4588,4585,0.0,0,0,721,0,0.28909382518043303,0.4557522123893805,1582,0,0,0.6343223736968725,0,0,1.0,1.0,1,0.0,1582,0.7594815170427268,501,0,0,0.20088211708099438,160,2095,4592,0.8352044907778668,2097 -pooling_nchw_max_d1_s2_3x3,4x20xf64,linalg_xdsl,1107,3222,3219,0.0,0,0,882,0,0.7967479674796748,0.9910112359550561,890,0,0,0.8039747064137308,0,0,3.2962962962962963,3.2962962962962963,1,0.0,270,0.5410821643286573,229,0,0,0.2068654019873532,0,2116,3226,1.010840108401084,2118 +pooling_nchw_max_d1_s2_3x3,4x20xf64,linalg_xdsl,1106,3208,3205,0.0,0,0,882,0,0.7974683544303798,0.9910112359550561,890,0,0,0.8047016274864376,0,0,3.3458646616541357,3.345864661654135,1,0.0,266,0.5507246376811594,217,0,0,0.1962025316455696,0,2103,3212,1.0009041591320071,2105 pooling_nchw_max_d1_s2_3x3,4x4xf64,baseline,711,2854,2851,0.0,0,0,226,0,0.3178621659634318,0.47379454926624737,477,0,0,0.6708860759493671,0,0,1.0,1.0,1,0.0,477,0.93713163064833,32,0,0,0.0450070323488045,0,2144,2858,0.7158931082981717,2146 pooling_nchw_max_d1_s2_3x3,4x4xf64,linalg,396,2536,2533,0.0,0,0,145,0,0.3661616161616162,0.5823293172690763,249,0,0,0.6287878787878788,0,0,1.0,1.0,1,0.0,249,0.8527397260273972,43,0,0,0.10858585858585859,32,2141,2540,0.7373737373737373,2143 pooling_nchw_max_d1_s2_3x3,4x4xf64,linalg_xdsl,224,2269,2266,0.0,0,0,178,0,0.7946428571428571,0.9888888888888889,180,0,0,0.8035714285714286,0,0,3.214285714285714,3.2142857142857144,1,0.0,56,0.5333333333333333,49,0,0,0.21875,0,2046,2273,1.0223214285714286,2048 @@ -1803,13 +2190,13 @@ pooling_nchw_max_d1_s2_3x3,4x8xf64,linalg,752,2892,2889,0.0,0,0,289,0,0.38430851 pooling_nchw_max_d1_s2_3x3,4x8xf64,linalg_xdsl,579,2674,2671,0.0,0,0,354,0,0.6113989637305699,0.9779005524861878,362,0,0,0.6252158894645942,0,0,3.175438596491228,3.175438596491228,1,0.0,114,0.3713355048859935,193,0,0,0.3333333333333333,0,2096,2678,0.9585492227979275,2098 pooling_nchw_max_d1_s2_3x3,8x12xf64,baseline,3305,5469,5466,0.0,0,0,1054,0,0.318910741301059,0.4737078651685393,2225,0,0,0.6732223903177005,0,0,1.0,1.0,1,0.0,2225,0.8090909090909091,525,0,0,0.1588502269288956,0,2165,5473,0.8320726172465961,2167 pooling_nchw_max_d1_s2_3x3,8x12xf64,linalg,3015,5120,5117,0.0,0,0,865,0,0.28689883913764513,0.4502863092139511,1921,0,0,0.6371475953565506,0,0,1.0,1.0,1,0.0,1921,0.7506838608831575,638,0,0,0.21160862354892207,192,2106,5124,0.8487562189054727,2108 -pooling_nchw_max_d1_s2_3x3,8x12xf64,linalg_xdsl,1483,3598,3595,0.0,0,0,1058,0,0.7134187457855697,0.9851024208566108,1074,0,0,0.7242076871207013,0,0,3.2545454545454544,3.2545454545454544,1,0.0,330,0.45392022008253097,397,0,0,0.2677006068779501,0,2116,3602,0.9919082939986514,2118 +pooling_nchw_max_d1_s2_3x3,8x12xf64,linalg_xdsl,1495,3617,3614,0.0,0,0,1058,0,0.7076923076923077,0.9851024208566108,1074,0,0,0.7183946488294315,0,0,3.3354037267080745,3.3354037267080745,1,0.0,322,0.4633093525179856,373,0,0,0.24949832775919734,0,2123,3621,0.9678929765886288,2125 pooling_nchw_max_d1_s2_3x3,8x16xf64,baseline,4313,6487,6484,0.0,0,0,1378,0,0.31949918849988407,0.4737023031969749,2909,0,0,0.6744725249246464,0,0,1.0,1.0,1,0.0,2909,0.8130240357741755,669,0,0,0.1551124507303501,0,2175,6491,0.8295849756549964,2177 pooling_nchw_max_d1_s2_3x3,8x16xf64,linalg,4022,6137,6134,0.0,0,0,1153,0,0.28667329686723025,0.45021475985942994,2561,0,0,0.6367478866235704,0,0,1.0,1.0,1,0.0,2561,0.7552344441167798,830,0,0,0.20636499254102436,256,2116,6141,0.8431128791645948,2118 pooling_nchw_max_d1_s2_3x3,8x16xf64,linalg_xdsl,1835,3960,3957,0.0,0,0,1410,0,0.7683923705722071,0.9887798036465638,1426,0,0,0.7771117166212534,0,0,3.2857142857142856,3.2857142857142856,1,0.0,434,0.5076023391812865,421,0,0,0.22942779291553134,0,2126,3964,1.0065395095367848,2128 pooling_nchw_max_d1_s2_3x3,8x20xf64,baseline,5321,7505,7502,0.0,0,0,1702,0,0.31986468708889304,0.4736988588922906,3593,0,0,0.6752490133433565,0,0,1.0,1.0,1,0.0,3593,0.8154788924194281,813,0,0,0.15279082879158054,0,2185,7509,0.8280398421349371,2187 pooling_nchw_max_d1_s2_3x3,8x20xf64,linalg,4999,7124,7121,0.0,0,0,1441,0,0.2882576515303061,0.45017182130584193,3201,0,0,0.6403280656131226,0,0,1.0,1.0,1,0.0,3201,0.7579919488515273,1022,0,0,0.20444088817763553,320,2126,7128,0.8447689537907581,2128 -pooling_nchw_max_d1_s2_3x3,8x20xf64,linalg_xdsl,2187,4322,4319,0.0,0,0,1762,0,0.8056698673982624,0.9910011248593926,1778,0,0,0.8129858253315043,0,0,3.3048327137546467,3.3048327137546467,1,0.0,538,0.5473041709053916,445,0,0,0.2034750800182899,0,2136,4326,1.0164609053497942,2138 +pooling_nchw_max_d1_s2_3x3,8x20xf64,linalg_xdsl,2186,4308,4305,0.0,0,0,1762,0,0.8060384263494969,0.9910011248593926,1778,0,0,0.8133577310155535,0,0,3.3547169811320754,3.3547169811320754,1,0.0,530,0.5573080967402734,421,0,0,0.19258920402561758,0,2123,4312,1.0059469350411712,2125 pooling_nchw_max_d1_s2_3x3,8x4xf64,baseline,1246,3371,3368,0.0,0,0,406,0,0.3258426966292135,0.47374562427071176,857,0,0,0.687800963081862,0,0,1.0,1.0,1,0.0,857,0.9469613259668508,48,0,0,0.038523274478330656,0,2126,3375,0.7263242375601927,2128 pooling_nchw_max_d1_s2_3x3,8x4xf64,linalg,783,2853,2850,0.0,0,0,289,0,0.36909323116219667,0.5814889336016097,497,0,0,0.6347381864623244,0,0,1.0,1.0,1,0.0,497,0.8214876033057851,108,0,0,0.13793103448275862,64,2071,2857,0.772669220945083,2073 pooling_nchw_max_d1_s2_3x3,8x4xf64,linalg_xdsl,406,2484,2481,0.0,0,0,354,0,0.8719211822660099,0.9943820224719101,356,0,0,0.8768472906403941,0,0,3.2962962962962963,3.2962962962962963,1,0.0,108,0.6390532544378699,61,0,0,0.15024630541871922,0,2079,2488,1.0270935960591134,2081 @@ -1818,13 +2205,13 @@ pooling_nchw_max_d1_s2_3x3,8x8xf64,linalg,1799,3864,3861,0.0,0,0,577,0,0.3207337 pooling_nchw_max_d1_s2_3x3,8x8xf64,linalg_xdsl,1131,3236,3233,0.0,0,0,706,0,0.6242263483642794,0.9778393351800554,722,0,0,0.6383731211317418,0,0,3.194690265486726,3.1946902654867255,1,0.0,226,0.3772954924874791,373,0,0,0.3297966401414677,0,2106,3240,0.9681697612732095,2108 pooling_nchw_sum_d1_s2_3x3,12x12xf64,baseline,6622,8731,8728,0.0,0,0,1353,0,0.20431893687707642,0.4446270128162997,3043,0,0,0.4595288432497735,0,0,1.0,1.0,1,0.0,3043,0.8020558777016341,751,0,0,0.1134098459679855,0,2110,8735,0.572938689217759,2112 pooling_nchw_sum_d1_s2_3x3,12x12xf64,linalg,6706,8786,8783,0.0,0,0,1297,0,0.19340888756337607,0.4501909059354391,2881,0,0,0.4296152699075455,0,0,1.0,1.0,1,4.0,2881,0.715598609041232,1145,12,3,0.17074261855055176,303,2081,8790,0.6003578884580972,2083 -pooling_nchw_sum_d1_s2_3x3,12x12xf64,linalg_xdsl,2281,4390,4387,0.0,0,0,1586,0,0.6953090749671197,0.9850931677018634,1610,0,0,0.7058307759754494,0,0,3.259109311740891,3.2591093117408905,1,0.0,494,0.4569842738205365,587,0,0,0.25734327049539674,0,2110,4394,0.9631740464708461,2112 +pooling_nchw_sum_d1_s2_3x3,12x12xf64,linalg_xdsl,2258,4374,4371,0.0,0,0,1586,0,0.7023914968999114,0.9850931677018634,1610,0,0,0.7130203720106288,0,0,3.3402489626556013,3.340248962655602,1,0.0,482,0.4666021297192643,551,0,0,0.24402125775022143,0,2117,4378,0.9570416297608503,2119 pooling_nchw_sum_d1_s2_3x3,12x16xf64,baseline,8645,10800,10797,0.0,0,0,1769,0,0.20462695199537304,0.4445840663483287,3979,0,0,0.46026604973973395,0,0,1.0,1.0,1,0.0,3979,0.8057918185500202,959,0,0,0.11093117408906883,0,2156,10804,0.5711972238288028,2158 pooling_nchw_sum_d1_s2_3x3,12x16xf64,linalg,8914,11025,11022,0.0,0,0,1729,0,0.193964550145838,0.4501431918771153,3841,0,0,0.4308952210006731,0,0,1.0,1.0,1,4.0,3841,0.7217211574596016,1481,12,3,0.16614314561364146,399,2112,11029,0.5970383666143146,2114 pooling_nchw_sum_d1_s2_3x3,12x16xf64,linalg_xdsl,2833,4988,4985,0.0,0,0,2114,0,0.7462054359336393,0.9887745556594949,2138,0,0,0.7546770208259795,0,0,3.2892307692307687,3.289230769230769,1,0.0,650,0.5106048703849175,623,0,0,0.21990822449699965,0,2156,4992,0.9745852453229792,2158 pooling_nchw_sum_d1_s2_3x3,12x20xf64,baseline,10673,12843,12840,0.0,0,0,2185,0,0.20472219619600862,0.44455747711088506,4915,0,0,0.46050782347980884,0,0,1.0,1.0,1,0.0,4915,0.8081223281815192,1167,0,0,0.10934132858615198,0,2171,12847,0.5698491520659608,2173 pooling_nchw_sum_d1_s2_3x3,12x20xf64,linalg,11122,13248,13245,0.0,0,0,2161,0,0.19429958640532277,0.45011455946677775,4801,0,0,0.4316669663729545,0,0,1.0,1.0,1,4.0,4801,0.7254457540042308,1817,12,3,0.16336989750044956,495,2127,13252,0.595036863873404,2129 -pooling_nchw_sum_d1_s2_3x3,12x20xf64,linalg_xdsl,3385,5555,5552,0.0,0,0,2642,0,0.7805022156573117,0.9909977494373593,2666,0,0,0.7875923190546529,0,0,3.307692307692308,3.3076923076923075,1,0.0,806,0.5501706484641639,659,0,0,0.1946824224519941,0,2171,5559,0.982274741506647,2173 +pooling_nchw_sum_d1_s2_3x3,12x20xf64,linalg_xdsl,3360,5514,5511,0.0,0,0,2642,0,0.7863095238095238,0.9909977494373593,2666,0,0,0.7934523809523809,0,0,3.3576826196473553,3.3576826196473553,1,0.0,794,0.5603387438249824,623,0,0,0.18541666666666667,0,2155,5518,0.9788690476190476,2157 pooling_nchw_sum_d1_s2_3x3,12x4xf64,baseline,2532,4615,4612,0.0,0,0,521,0,0.20576619273301738,0.4449188727583262,1171,0,0,0.46248025276461296,0,0,1.0,1.0,1,0.0,1171,0.9497161394971614,62,0,0,0.02448657187993681,0,2084,4619,0.48696682464454977,2086 pooling_nchw_sum_d1_s2_3x3,12x4xf64,linalg,2068,4125,4122,0.0,0,0,433,0,0.20938104448742748,0.5812080536912752,745,0,0,0.3602514506769826,0,0,1.0,1.0,1,4.0,745,0.745,255,12,3,0.12330754352030948,111,2058,4129,0.4835589941972921,2060 pooling_nchw_sum_d1_s2_3x3,12x4xf64,linalg_xdsl,612,2710,2707,0.0,0,0,530,0,0.8660130718954249,0.9962406015037594,532,0,0,0.869281045751634,0,0,3.325,3.325,1,0.0,160,0.6926406926406926,71,0,0,0.11601307189542484,0,2099,2714,0.9852941176470589,2101 @@ -1833,13 +2220,13 @@ pooling_nchw_sum_d1_s2_3x3,12x8xf64,linalg,4169,6276,6273,0.0,0,0,865,0,0.207483 pooling_nchw_sum_d1_s2_3x3,12x8xf64,linalg_xdsl,1729,3823,3820,0.0,0,0,1058,0,0.6119144013880856,0.977818853974122,1082,0,0,0.6257952573742047,0,0,3.201183431952663,3.201183431952663,1,0.0,338,0.38020247469066365,551,0,0,0.31868131868131866,0,2095,3827,0.9444765760555234,2097 pooling_nchw_sum_d1_s2_3x3,16x12xf64,baseline,8645,10800,10797,0.0,0,0,1769,0,0.20462695199537304,0.4445840663483287,3979,0,0,0.46026604973973395,0,0,1.0,1.0,1,0.0,3979,0.8025413473174667,979,0,0,0.11324465008675536,0,2156,10804,0.5735106998264893,2158 pooling_nchw_sum_d1_s2_3x3,16x12xf64,linalg,8914,11025,11022,0.0,0,0,1729,0,0.193964550145838,0.4501431918771153,3841,0,0,0.4308952210006731,0,0,1.0,1.0,1,4.0,3841,0.7184811073699963,1505,12,3,0.16883553960062822,399,2112,11029,0.5997307606013014,2114 -pooling_nchw_sum_d1_s2_3x3,16x12xf64,linalg_xdsl,3033,5188,5185,0.0,0,0,2114,0,0.6969996702934388,0.9850885368126747,2146,0,0,0.707550280250577,0,0,3.2613981762917934,3.2613981762917934,1,0.0,658,0.45789839944328464,779,0,0,0.25684141114408177,0,2156,5192,0.9643916913946587,2158 +pooling_nchw_sum_d1_s2_3x3,16x12xf64,linalg_xdsl,3001,5160,5157,0.0,0,0,2114,0,0.704431856047984,0.9850885368126747,2146,0,0,0.7150949683438854,0,0,3.3426791277258565,3.3426791277258565,1,0.0,642,0.4675892206846322,731,0,0,0.24358547150949683,0,2160,5164,0.9586804398533822,2162 pooling_nchw_sum_d1_s2_3x3,16x16xf64,baseline,11305,13471,13468,0.0,0,0,2313,0,0.2045997346306944,0.44455122044974055,5203,0,0,0.4602388323750553,0,0,1.0,1.0,1,0.0,5203,0.8061667183142237,1251,0,0,0.11065900044228218,0,2167,13475,0.5708978328173375,2169 pooling_nchw_sum_d1_s2_3x3,16x16xf64,linalg,11871,14012,14009,0.0,0,0,2305,0,0.1941706680144891,0.45010740089826207,5121,0,0,0.4313874147081122,0,0,1.0,1.0,1,4.0,5121,0.7238162544169612,1954,12,3,0.16460281357931092,527,2142,14016,0.5959902282874231,2144 pooling_nchw_sum_d1_s2_3x3,16x16xf64,linalg_xdsl,3777,5943,5940,0.0,0,0,2818,0,0.7460947842202806,0.9887719298245614,2850,0,0,0.7545671167593329,0,0,3.2909930715935336,3.2909930715935336,1,0.0,866,0.5115180153573539,827,0,0,0.2189568440561292,0,2167,5947,0.973523960815462,2169 pooling_nchw_sum_d1_s2_3x3,16x20xf64,baseline,13957,16138,16135,0.0,0,0,2857,0,0.2047001504621337,0.4445308853275245,6427,0,0,0.46048577774593397,0,0,1.0,1.0,1,0.0,6427,0.8084276729559748,1523,0,0,0.10912087124740273,0,2182,16142,0.5696066489933367,2184 pooling_nchw_sum_d1_s2_3x3,16x20xf64,linalg,14815,16971,16968,0.0,0,0,2881,0,0.19446506918663517,0.4500859240743634,6401,0,0,0.4320620992237597,0,0,1.0,1.0,1,4.0,6401,0.7271384755197092,2402,12,3,0.16213297333783327,655,2157,16975,0.594195072561593,2159 -pooling_nchw_sum_d1_s2_3x3,16x20xf64,linalg_xdsl,4513,6694,6691,0.0,0,0,3522,0,0.7804121426988699,0.9909960607765897,3554,0,0,0.787502769776202,0,0,3.3091247672253257,3.3091247672253257,1,0.0,1074,0.5510518214468958,875,0,0,0.19388433414580103,0,2182,6698,0.981387103922003,2184 +pooling_nchw_sum_d1_s2_3x3,16x20xf64,linalg_xdsl,4472,6634,6631,0.0,0,0,3522,0,0.787567084078712,0.9909960607765897,3554,0,0,0.7947227191413238,0,0,3.3591682419659734,3.3591682419659734,1,0.0,1058,0.5612732095490717,827,0,0,0.18492844364937389,0,2163,6638,0.9796511627906976,2165 pooling_nchw_sum_d1_s2_3x3,16x4xf64,baseline,3304,5392,5389,0.0,0,0,681,0,0.20611380145278452,0.4448073154800784,1531,0,0,0.4633777239709443,0,0,1.0,1.0,1,0.0,1531,0.9515226848974518,78,0,0,0.02360774818401937,0,2089,5396,0.4869854721549637,2091 pooling_nchw_sum_d1_s2_3x3,16x4xf64,linalg,2732,4794,4791,0.0,0,0,577,0,0.21120058565153735,0.581067472306143,993,0,0,0.36346998535871156,0,0,1.0,1.0,1,4.0,993,0.756859756097561,319,12,3,0.11676427525622254,143,2063,4798,0.4802342606149341,2065 pooling_nchw_sum_d1_s2_3x3,16x4xf64,linalg_xdsl,796,2899,2896,0.0,0,0,706,0,0.8869346733668342,0.9971751412429378,708,0,0,0.8894472361809045,0,0,3.339622641509434,3.339622641509434,1,0.0,212,0.7186440677966102,83,0,0,0.10427135678391959,0,2104,2903,0.9937185929648241,2106 @@ -1848,13 +2235,13 @@ pooling_nchw_sum_d1_s2_3x3,16x8xf64,linalg,5533,7650,7647,0.0,0,0,1153,0,0.20838 pooling_nchw_sum_d1_s2_3x3,16x8xf64,linalg_xdsl,2297,4401,4398,0.0,0,0,1410,0,0.6138441445363517,0.9778085991678225,1442,0,0,0.6277753591641271,0,0,3.2044444444444444,3.2044444444444444,1,0.0,450,0.3810330228619814,731,0,0,0.3182411841532434,0,2105,4405,0.9460165433173704,2107 pooling_nchw_sum_d1_s2_3x3,20x12xf64,baseline,10673,12843,12840,0.0,0,0,2185,0,0.20472219619600862,0.44455747711088506,4915,0,0,0.46050782347980884,0,0,1.0,1.0,1,0.0,4915,0.8028422084286181,1207,0,0,0.11308910334488897,0,2171,12847,0.5735969268246979,2173 pooling_nchw_sum_d1_s2_3x3,20x12xf64,linalg,11122,13248,13245,0.0,0,0,2161,0,0.19429958640532277,0.45011455946677775,4801,0,0,0.4316669663729545,0,0,1.0,1.0,1,4.0,4801,0.7202220222022202,1865,12,3,0.1676856680453156,495,2127,13252,0.59935263441827,2129 -pooling_nchw_sum_d1_s2_3x3,20x12xf64,linalg_xdsl,3785,5955,5952,0.0,0,0,2642,0,0.6980184940554822,0.9850857568978374,2682,0,0,0.7085865257595773,0,0,3.2627737226277373,3.2627737226277373,1,0.0,822,0.45844952593418853,971,0,0,0.25653896961690886,0,2171,5959,0.9651254953764861,2173 +pooling_nchw_sum_d1_s2_3x3,20x12xf64,linalg_xdsl,3745,5919,5916,0.0,0,0,2642,0,0.7054739652870494,0.9850857568978374,2682,0,0,0.716154873164219,0,0,3.344139650872818,3.344139650872818,1,0.0,802,0.46818447168709865,911,0,0,0.24325767690253672,0,2175,5923,0.9594125500667557,2177 pooling_nchw_sum_d1_s2_3x3,20x16xf64,baseline,13957,16138,16135,0.0,0,0,2857,0,0.2047001504621337,0.4445308853275245,6427,0,0,0.46048577774593397,0,0,1.0,1.0,1,0.0,6427,0.8063989962358845,1543,0,0,0.11055384394927277,0,2182,16142,0.5710396216952067,2184 pooling_nchw_sum_d1_s2_3x3,20x16xf64,linalg,14815,16971,16968,0.0,0,0,2881,0,0.19446506918663517,0.4500859240743634,6401,0,0,0.4320620992237597,0,0,1.0,1.0,1,4.0,6401,0.7251614365016427,2426,12,3,0.1637529530880864,655,2157,16975,0.5958150523118462,2159 pooling_nchw_sum_d1_s2_3x3,20x16xf64,linalg_xdsl,4713,6894,6891,0.0,0,0,3522,0,0.7472947167409294,0.9887703537338574,3562,0,0,0.7557818799066413,0,0,3.292051756007394,3.292051756007394,1,0.0,1082,0.5120681495504023,1031,0,0,0.21875663059622322,0,2182,6898,0.9745385105028644,2184 pooling_nchw_sum_d1_s2_3x3,20x20xf64,baseline,17233,19418,19415,0.0,0,0,3529,0,0.2047815238205768,0.444514422471344,7939,0,0,0.46068589334416526,0,0,1.0,1.0,1,0.0,7939,0.808616826237523,1879,0,0,0.10903499100562873,0,2186,19422,0.569720884349794,2188 pooling_nchw_sum_d1_s2_3x3,20x20xf64,linalg,18495,20671,20668,0.0,0,0,3601,0,0.19470127061367937,0.45006874140732406,8001,0,0,0.43260340632603406,0,0,1.0,1.0,1,4.0,8001,0.7282242650405024,2986,12,3,0.16144904028115706,815,2177,20675,0.5940524466071911,2179 -pooling_nchw_sum_d1_s2_3x3,20x20xf64,linalg_xdsl,5633,7818,7815,0.0,0,0,4402,0,0.7814663589561512,0.9909950472760019,4442,0,0,0.7885673708503462,0,0,3.3099850968703426,3.3099850968703426,1,0.0,1342,0.5515824085491163,1091,0,0,0.19368009941416653,0,2186,7822,0.9822474702645128,2188 +pooling_nchw_sum_d1_s2_3x3,20x20xf64,linalg_xdsl,5584,7769,7766,0.0,0,0,4402,0,0.788323782234957,0.9909950472760019,4442,0,0,0.795487106017192,0,0,3.3600605143721634,3.3600605143721634,1,0.0,1322,0.5618359541011475,1031,0,0,0.18463467048710602,0,2186,7773,0.980121776504298,2188 pooling_nchw_sum_d1_s2_3x3,20x4xf64,baseline,4076,6174,6171,0.0,0,0,841,0,0.2063297350343474,0.44473823373876253,1891,0,0,0.4639352306182532,0,0,1.0,1.0,1,0.0,1891,0.9526448362720403,94,0,0,0.023061825318940136,0,2099,6178,0.48699705593719333,2101 pooling_nchw_sum_d1_s2_3x3,20x4xf64,linalg,3396,5463,5460,0.0,0,0,721,0,0.2123085983510012,0.580983078162772,1241,0,0,0.3654299175500589,0,0,1.0,1.0,1,4.0,1241,0.7641625615763546,383,12,3,0.11277974087161366,175,2068,5467,0.4782096584216725,2070 pooling_nchw_sum_d1_s2_3x3,20x4xf64,linalg_xdsl,980,3088,3085,0.0,0,0,882,0,0.9,0.997737556561086,884,0,0,0.9020408163265307,0,0,3.348484848484848,3.3484848484848486,1,0.0,264,0.7353760445682451,95,0,0,0.09693877551020408,0,2109,3092,0.9989795918367348,2111 @@ -1863,13 +2250,13 @@ pooling_nchw_sum_d1_s2_3x3,20x8xf64,linalg,6897,9024,9021,0.0,0,0,1441,0,0.20893 pooling_nchw_sum_d1_s2_3x3,20x8xf64,linalg_xdsl,2865,4979,4976,0.0,0,0,1762,0,0.6150087260034904,0.9778024417314095,1802,0,0,0.6289703315881326,0,0,3.206405693950178,3.206405693950178,1,0.0,562,0.38153428377460963,911,0,0,0.31797556719022685,0,2115,4983,0.9469458987783594,2117 pooling_nchw_sum_d1_s2_3x3,4x12xf64,baseline,2558,4663,4660,0.0,0,0,521,0,0.20367474589523066,0.4449188727583262,1171,0,0,0.4577795152462862,0,0,1.0,1.0,1,0.0,1171,0.8042582417582418,285,0,0,0.11141516810007819,0,2106,4667,0.5691946833463644,2108 pooling_nchw_sum_d1_s2_3x3,4x12xf64,linalg,2281,4368,4365,0.0,0,0,434,0,0.19026742656729503,0.4568421052631579,950,0,0,0.41648399824638316,0,0,1.0,1.0,1,3.0,950,0.6944444444444444,418,9,3,0.1832529592284086,111,2088,4372,0.5997369574747917,2090 -pooling_nchw_sum_d1_s2_3x3,4x12xf64,linalg_xdsl,777,2861,2858,0.0,0,0,530,0,0.6821106821106822,0.9851301115241635,538,0,0,0.6924066924066924,0,0,3.240963855421687,3.2409638554216866,1,0.0,166,0.44986449864498645,203,0,0,0.26126126126126126,0,2085,2865,0.9536679536679536,2087 +pooling_nchw_sum_d1_s2_3x3,4x12xf64,linalg_xdsl,770,2861,2858,0.0,0,0,530,0,0.6883116883116883,0.9851301115241635,538,0,0,0.6987012987012987,0,0,3.3209876543209877,3.3209876543209877,1,0.0,162,0.45892351274787535,191,0,0,0.24805194805194805,0,2092,2865,0.9467532467532468,2094 pooling_nchw_sum_d1_s2_3x3,4x16xf64,baseline,3338,5448,5445,0.0,0,0,681,0,0.20401437986818455,0.4448073154800784,1531,0,0,0.45865787896944277,0,0,1.0,1.0,1,0.0,1531,0.8074894514767933,365,0,0,0.10934691431995207,0,2111,5452,0.5680047932893948,2113 pooling_nchw_sum_d1_s2_3x3,4x16xf64,linalg,3013,5105,5102,0.0,0,0,578,0,0.1918353800199137,0.4565560821484992,1266,0,0,0.4201792233654165,0,0,1.0,1.0,1,3.0,1266,0.7033333333333334,534,9,3,0.17723199468967807,143,2093,5109,0.5974112180550946,2095 pooling_nchw_sum_d1_s2_3x3,4x16xf64,linalg_xdsl,961,3050,3047,0.0,0,0,706,0,0.7346514047866806,0.988795518207283,714,0,0,0.7429760665972945,0,0,3.275229357798165,3.2752293577981653,1,0.0,218,0.5034642032332564,215,0,0,0.22372528616024975,0,2090,3054,0.9667013527575443,2092 pooling_nchw_sum_d1_s2_3x3,4x20xf64,baseline,4118,6233,6230,0.0,0,0,841,0,0.20422535211267606,0.44473823373876253,1891,0,0,0.4592034968431277,0,0,1.0,1.0,1,0.0,1891,0.8095034246575342,445,0,0,0.10806216610004857,0,2116,6237,0.5672656629431763,2118 pooling_nchw_sum_d1_s2_3x3,4x20xf64,linalg,3745,5842,5839,0.0,0,0,722,0,0.19279038718291056,0.4563843236409608,1582,0,0,0.4224299065420561,0,0,1.0,1.0,1,3.0,1582,0.7087813620071685,650,9,3,0.17356475300400534,175,2098,5846,0.5959946595460615,2100 -pooling_nchw_sum_d1_s2_3x3,4x20xf64,linalg_xdsl,1145,3239,3236,0.0,0,0,882,0,0.7703056768558952,0.9910112359550561,890,0,0,0.777292576419214,0,0,3.2962962962962963,3.2962962962962963,1,0.0,270,0.5432595573440644,227,0,0,0.19825327510917032,0,2095,3243,0.9755458515283844,2097 +pooling_nchw_sum_d1_s2_3x3,4x20xf64,linalg_xdsl,1137,3235,3232,0.0,0,0,882,0,0.7757255936675461,0.9910112359550561,890,0,0,0.7827616534740546,0,0,3.3458646616541357,3.345864661654135,1,0.0,266,0.553014553014553,215,0,0,0.18909410729991205,0,2099,3239,0.9718557607739666,2101 pooling_nchw_sum_d1_s2_3x3,4x4xf64,baseline,982,3027,3024,0.0,0,0,201,0,0.20468431771894094,0.44567627494456763,451,0,0,0.4592668024439919,0,0,1.0,1.0,1,0.0,451,0.9376299376299376,30,0,0,0.03054989816700611,0,2046,3031,0.48981670061099797,2048 pooling_nchw_sum_d1_s2_3x3,4x4xf64,linalg,728,2799,2796,0.0,0,0,145,0,0.19917582417582416,0.5823293172690763,249,0,0,0.34203296703296704,0,0,1.0,1.0,1,4.0,249,0.6974789915966386,108,12,3,0.14835164835164835,47,2072,2803,0.4903846153846154,2074 pooling_nchw_sum_d1_s2_3x3,4x4xf64,linalg_xdsl,230,2273,2270,0.0,0,0,178,0,0.7739130434782608,0.9888888888888889,180,0,0,0.782608695652174,0,0,3.214285714285714,3.2142857142857144,1,0.0,56,0.5436893203883495,47,0,0,0.20434782608695654,0,2044,2277,0.9869565217391305,2046 @@ -1878,13 +2265,13 @@ pooling_nchw_sum_d1_s2_3x3,4x8xf64,linalg,1349,3413,3410,0.0,0,0,283,0,0.2097850 pooling_nchw_sum_d1_s2_3x3,4x8xf64,linalg_xdsl,593,2667,2664,0.0,0,0,354,0,0.596964586846543,0.9779005524861878,362,0,0,0.6104553119730185,0,0,3.175438596491228,3.175438596491228,1,0.0,114,0.3737704918032787,191,0,0,0.3220910623946037,0,2075,2671,0.9325463743676222,2077 pooling_nchw_sum_d1_s2_3x3,8x12xf64,baseline,4594,6688,6685,0.0,0,0,937,0,0.2039616891597736,0.44470811580446135,2107,0,0,0.4586417065737919,0,0,1.0,1.0,1,0.0,2107,0.8011406844106463,523,0,0,0.11384414453635176,0,2095,6692,0.5724858511101436,2097 pooling_nchw_sum_d1_s2_3x3,8x12xf64,linalg,4498,6563,6560,0.0,0,0,865,0,0.19230769230769232,0.4502863092139511,1921,0,0,0.42707870164517564,0,0,1.0,1.0,1,4.0,1921,0.7099039172209904,785,12,3,0.1745220097821254,207,2066,6567,0.601600711427301,2068 -pooling_nchw_sum_d1_s2_3x3,8x12xf64,linalg_xdsl,1529,3623,3620,0.0,0,0,1058,0,0.6919555264879006,0.9851024208566108,1074,0,0,0.7024198822759974,0,0,3.2545454545454544,3.2545454545454544,1,0.0,330,0.45517241379310347,395,0,0,0.25833878351863965,0,2095,3627,0.960758665794637,2097 +pooling_nchw_sum_d1_s2_3x3,8x12xf64,linalg_xdsl,1514,3615,3612,0.0,0,0,1058,0,0.6988110964332893,0.9851024208566108,1074,0,0,0.7093791281373845,0,0,3.3354037267080745,3.3354037267080745,1,0.0,322,0.46464646464646464,371,0,0,0.2450462351387054,0,2102,3619,0.9544253632760898,2104 pooling_nchw_sum_d1_s2_3x3,8x16xf64,baseline,5998,8102,8099,0.0,0,0,1225,0,0.20423474491497165,0.44464609800362975,2755,0,0,0.4593197732577526,0,0,1.0,1.0,1,0.0,2755,0.8050847457627118,667,0,0,0.11120373457819273,0,2105,8106,0.5705235078359453,2107 pooling_nchw_sum_d1_s2_3x3,8x16xf64,linalg,5970,8045,8042,0.0,0,0,1153,0,0.1931323283082077,0.45021475985942994,2561,0,0,0.4289782244556114,0,0,1.0,1.0,1,4.0,2561,0.7173669467787115,1009,12,3,0.16901172529313233,271,2076,8049,0.5979899497487438,2078 pooling_nchw_sum_d1_s2_3x3,8x16xf64,linalg_xdsl,1897,4001,3998,0.0,0,0,1410,0,0.7432788613600422,0.9887798036465638,1426,0,0,0.7517132314180285,0,0,3.2857142857142856,3.2857142857142856,1,0.0,434,0.5087924970691676,419,0,0,0.22087506589351608,0,2105,4005,0.9725882973115445,2107 pooling_nchw_sum_d1_s2_3x3,8x20xf64,baseline,7402,9516,9513,0.0,0,0,1513,0,0.2044042150770062,0.4446076990890391,3403,0,0,0.45974061064577143,0,0,1.0,1.0,1,0.0,3403,0.807546274323683,811,0,0,0.10956498243717915,0,2115,9520,0.5693055930829506,2117 pooling_nchw_sum_d1_s2_3x3,8x20xf64,linalg,7442,9527,9524,0.0,0,0,1441,0,0.19363074442354206,0.45017182130584193,3201,0,0,0.430126310131685,0,0,1.0,1.0,1,4.0,3201,0.7219215155615697,1233,12,3,0.16568126847621606,335,2086,9531,0.5958075786079011,2088 -pooling_nchw_sum_d1_s2_3x3,8x20xf64,linalg_xdsl,2265,4379,4376,0.0,0,0,1762,0,0.7779249448123621,0.9910011248593926,1778,0,0,0.7849889624724061,0,0,3.3048327137546467,3.3048327137546467,1,0.0,538,0.5484199796126402,443,0,0,0.1955849889624724,0,2115,4383,0.9805739514348786,2117 +pooling_nchw_sum_d1_s2_3x3,8x20xf64,linalg_xdsl,2249,4367,4364,0.0,0,0,1762,0,0.7834593152512228,0.9910011248593926,1778,0,0,0.7905735882614495,0,0,3.3547169811320754,3.3547169811320754,1,0.0,530,0.5584826132771338,419,0,0,0.18630502445531347,0,2119,4371,0.976878612716763,2121 pooling_nchw_sum_d1_s2_3x3,8x4xf64,baseline,1760,3838,3835,0.0,0,0,361,0,0.20511363636363636,0.44512946979038226,811,0,0,0.46079545454545456,0,0,1.0,1.0,1,0.0,811,0.9463243873978997,46,0,0,0.026136363636363635,0,2079,3842,0.4869318181818182,2081 pooling_nchw_sum_d1_s2_3x3,8x4xf64,linalg,1404,3451,3448,0.0,0,0,289,0,0.20584045584045585,0.5814889336016097,497,0,0,0.353988603988604,0,0,1.0,1.0,1,4.0,497,0.7223837209302325,191,12,3,0.13603988603988604,79,2048,3455,0.49002849002849,2050 pooling_nchw_sum_d1_s2_3x3,8x4xf64,linalg_xdsl,428,2516,2513,0.0,0,0,354,0,0.8271028037383178,0.9943820224719101,356,0,0,0.8317757009345794,0,0,3.2962962962962963,3.2962962962962963,1,0.0,108,0.6467065868263473,59,0,0,0.1378504672897196,0,2089,2520,0.969626168224299,2091 diff --git a/results/pivoted.all.csv b/results/pivoted.all.csv index 75693677..d4c0222e 100644 --- a/results/pivoted.all.csv +++ b/results/pivoted.all.csv @@ -1,27 +1,27 @@ kernels,baseline,linalg,linalg_xdsl,snitch_stream,snrt -conv2d_d1_s1_3x3 12x12xf64,7373,6726,2482,, +conv2d_d1_s1_3x3 12x12xf64,7373,6726,2449,, conv2d_d1_s1_3x3 12x16xf64,9817,8934,3034,, -conv2d_d1_s1_3x3 12x20xf64,12265,11149,3578,, +conv2d_d1_s1_3x3 12x20xf64,12265,11149,3554,, conv2d_d1_s1_3x3 12x4xf64,2445,2084,628,, conv2d_d1_s1_3x3 12x8xf64,4925,4518,1930,, -conv2d_d1_s1_3x3 16x12xf64,9817,8934,3298,, +conv2d_d1_s1_3x3 16x12xf64,9817,8934,3257,, conv2d_d1_s1_3x3 16x16xf64,13081,11885,4026,, -conv2d_d1_s1_3x3 16x20xf64,16345,14829,4762,, +conv2d_d1_s1_3x3 16x20xf64,16345,14829,4730,, conv2d_d1_s1_3x3 16x4xf64,3258,2748,812,, conv2d_d1_s1_3x3 16x8xf64,6557,5990,2562,, -conv2d_d1_s1_3x3 20x12xf64,12265,11149,4106,, +conv2d_d1_s1_3x3 20x12xf64,12265,11149,4066,, conv2d_d1_s1_3x3 20x16xf64,16345,14829,5026,, -conv2d_d1_s1_3x3 20x20xf64,20425,18509,5946,, +conv2d_d1_s1_3x3 20x20xf64,20425,18509,5906,, conv2d_d1_s1_3x3 20x4xf64,4061,3412,996,, conv2d_d1_s1_3x3 20x8xf64,8189,7462,3194,, -conv2d_d1_s1_3x3 4x12xf64,2479,2303,850,, +conv2d_d1_s1_3x3 4x12xf64,2479,2303,833,, conv2d_d1_s1_3x3 4x16xf64,3295,3035,1034,, -conv2d_d1_s1_3x3 4x20xf64,4111,3767,1218,, +conv2d_d1_s1_3x3 4x20xf64,4111,3767,1202,, conv2d_d1_s1_3x3 4x4xf64,825,752,248,, conv2d_d1_s1_3x3 4x8xf64,1663,1436,666,, -conv2d_d1_s1_3x3 8x12xf64,4925,4518,1666,, +conv2d_d1_s1_3x3 8x12xf64,4925,4518,1641,, conv2d_d1_s1_3x3 8x16xf64,6557,5990,2034,, -conv2d_d1_s1_3x3 8x20xf64,8189,7462,2402,, +conv2d_d1_s1_3x3 8x20xf64,8189,7462,2378,, conv2d_d1_s1_3x3 8x4xf64,1642,1420,444,, conv2d_d1_s1_3x3 8x8xf64,3293,3046,1298,, ddot 128xf64,924,924,,177,546 @@ -34,27 +34,30 @@ exp_macro 384xf64,,,,,6582 exp_macro 448xf64,,,,,7523 exp_macro 512xf64,,,,,8453 exp_macro 64xf64,,,,,1897 -exp_micro 106xf16,10632,,,, -exp_micro 106xf32,9994,,,, -exp_micro 106xf64,11380,,,, -exp_micro 122xf16,12232,,,, -exp_micro 122xf32,11498,,,, -exp_micro 122xf64,13092,,,, -exp_micro 26xf16,2641,,,, -exp_micro 26xf32,2487,,,, -exp_micro 26xf64,2815,,,, -exp_micro 42xf16,4232,,,, -exp_micro 42xf32,3992,,,, -exp_micro 42xf64,4536,,,, -exp_micro 58xf16,5832,,,, -exp_micro 58xf32,5482,,,, -exp_micro 58xf64,6244,,,, -exp_micro 74xf16,7432,,,, -exp_micro 74xf32,6986,,,, -exp_micro 74xf64,7956,,,, -exp_micro 90xf16,9032,,,, -exp_micro 90xf32,8490,,,, -exp_micro 90xf64,9668,,,, +exp_micro 112xf16,11232,,,, +exp_micro 112xf32,10558,,,, +exp_micro 112xf64,12014,,,, +exp_micro 128xf16,12832,,,, +exp_micro 128xf32,12062,,,, +exp_micro 128xf64,13726,,,, +exp_micro 16xf16,1628,,,, +exp_micro 16xf32,1535,,,, +exp_micro 16xf64,1750,,,, +exp_micro 32xf16,3229,,,, +exp_micro 32xf32,3039,,,, +exp_micro 32xf64,3463,,,, +exp_micro 48xf16,4832,,,, +exp_micro 48xf32,4544,,,, +exp_micro 48xf64,5177,,,, +exp_micro 64xf16,6432,,,, +exp_micro 64xf32,6046,,,, +exp_micro 64xf64,6878,,,, +exp_micro 80xf16,8032,,,, +exp_micro 80xf32,7550,,,, +exp_micro 80xf64,8590,,,, +exp_micro 96xf16,9632,,,, +exp_micro 96xf32,9054,,,, +exp_micro 96xf64,10302,,,, fill 12x12xf64,201,201,175,, fill 12x16xf64,242,242,223,, fill 12x20xf64,289,289,271,, @@ -80,773 +83,773 @@ fill 8x16xf64,141,141,159,, fill 8x20xf64,173,173,191,, fill 8x4xf64,43,43,63,, fill 8x8xf64,75,75,95,, -matmul 1x12x12xf64,821,,228,, +matmul 1x12x12xf64,821,,224,, matmul 1x12x16xf64,1087,,286,, -matmul 1x12x20xf64,1355,,344,, +matmul 1x12x20xf64,1355,,342,, matmul 1x12x24xf64,1639,,414,, -matmul 1x12x28xf64,1900,,484,, +matmul 1x12x28xf64,1900,,476,, matmul 1x12x32xf64,2171,,524,, -matmul 1x12x36xf64,2439,,582,, -matmul 1x12x40xf64,2708,,640,, +matmul 1x12x36xf64,2439,,585,, +matmul 1x12x40xf64,2708,,642,, matmul 1x12x44xf64,2980,,698,, -matmul 1x12x48xf64,3248,,756,, +matmul 1x12x48xf64,3248,,757,, matmul 1x12x4xf64,286,,97,, matmul 1x12x52xf64,3516,,814,, -matmul 1x12x56xf64,3784,,872,, -matmul 1x12x60xf64,4052,,930,, +matmul 1x12x56xf64,3784,,861,, +matmul 1x12x60xf64,4052,,929,, matmul 1x12x64xf64,4320,,988,, matmul 1x12x8xf64,551,,170,, -matmul 1x16x12xf64,1073,,276,, +matmul 1x16x12xf64,1073,,272,, matmul 1x16x16xf64,1430,,355,, -matmul 1x16x20xf64,1788,,430,, +matmul 1x16x20xf64,1788,,437,, matmul 1x16x24xf64,2133,,510,, -matmul 1x16x28xf64,2504,,596,, +matmul 1x16x28xf64,2504,,588,, matmul 1x16x32xf64,2838,,652,, -matmul 1x16x36xf64,3190,,726,, -matmul 1x16x40xf64,3554,,800,, +matmul 1x16x36xf64,3190,,729,, +matmul 1x16x40xf64,3554,,802,, matmul 1x16x44xf64,3907,,874,, -matmul 1x16x48xf64,4259,,948,, +matmul 1x16x48xf64,4259,,949,, matmul 1x16x4xf64,370,,113,, matmul 1x16x52xf64,4606,,1022,, -matmul 1x16x56xf64,4958,,1096,, -matmul 1x16x60xf64,5310,,1170,, +matmul 1x16x56xf64,4958,,1085,, +matmul 1x16x60xf64,5310,,1169,, matmul 1x16x64xf64,5662,,1244,, matmul 1x16x8xf64,721,,202,, matmul 1x200x5xf64,,,1056,, -matmul 1x20x12xf64,1329,,344,, +matmul 1x20x12xf64,1329,,337,, matmul 1x20x16xf64,1771,,435,, -matmul 1x20x20xf64,2202,,516,, -matmul 1x20x24xf64,2653,,600,, -matmul 1x20x28xf64,3090,,696,, +matmul 1x20x20xf64,2202,,517,, +matmul 1x20x24xf64,2653,,598,, +matmul 1x20x28xf64,3090,,700,, matmul 1x20x32xf64,3513,,780,, -matmul 1x20x36xf64,3949,,870,, -matmul 1x20x40xf64,4382,,960,, +matmul 1x20x36xf64,3949,,873,, +matmul 1x20x40xf64,4382,,962,, matmul 1x20x44xf64,4834,,1051,, -matmul 1x20x48xf64,5270,,1140,, +matmul 1x20x48xf64,5270,,1141,, matmul 1x20x4xf64,458,,129,, matmul 1x20x52xf64,5701,,1230,, -matmul 1x20x56xf64,6137,,1320,, -matmul 1x20x60xf64,6573,,1410,, +matmul 1x20x56xf64,6137,,1309,, +matmul 1x20x60xf64,6573,,1409,, matmul 1x20x64xf64,7012,,1500,, matmul 1x20x8xf64,894,,234,, -matmul 1x24x12xf64,1592,,386,, +matmul 1x24x12xf64,1592,,389,, matmul 1x24x16xf64,2105,,499,, -matmul 1x24x20xf64,2623,,590,, -matmul 1x24x24xf64,3145,,714,, -matmul 1x24x28xf64,3681,,808,, +matmul 1x24x20xf64,2623,,598,, +matmul 1x24x24xf64,3145,,702,, +matmul 1x24x28xf64,3681,,812,, matmul 1x24x32xf64,4182,,908,, -matmul 1x24x36xf64,4710,,1014,, -matmul 1x24x40xf64,5232,,1120,, +matmul 1x24x36xf64,4710,,1017,, +matmul 1x24x40xf64,5232,,1122,, matmul 1x24x44xf64,5754,,1226,, -matmul 1x24x48xf64,6274,,1332,, +matmul 1x24x48xf64,6274,,1333,, matmul 1x24x4xf64,535,,145,, matmul 1x24x52xf64,6799,,1438,, -matmul 1x24x56xf64,7319,,1544,, -matmul 1x24x60xf64,7839,,1650,, +matmul 1x24x56xf64,7319,,1533,, +matmul 1x24x60xf64,7839,,1649,, matmul 1x24x64xf64,8370,,1756,, matmul 1x24x8xf64,1059,,266,, -matmul 1x28x12xf64,1844,,434,, +matmul 1x28x12xf64,1844,,437,, matmul 1x28x16xf64,2449,,563,, -matmul 1x28x20xf64,3047,,685,, -matmul 1x28x24xf64,3656,,810,, -matmul 1x28x28xf64,4269,,941,, +matmul 1x28x20xf64,3047,,679,, +matmul 1x28x24xf64,3656,,800,, +matmul 1x28x28xf64,4269,,924,, matmul 1x28x32xf64,4864,,1036,, -matmul 1x28x36xf64,5463,,1158,, -matmul 1x28x40xf64,6079,,1280,, +matmul 1x28x36xf64,5463,,1161,, +matmul 1x28x40xf64,6079,,1282,, matmul 1x28x44xf64,6683,,1402,, -matmul 1x28x48xf64,7294,,1524,, +matmul 1x28x48xf64,7294,,1525,, matmul 1x28x4xf64,619,,161,, matmul 1x28x52xf64,7900,,1646,, -matmul 1x28x56xf64,8504,,1768,, -matmul 1x28x60xf64,9107,,1890,, +matmul 1x28x56xf64,8504,,1757,, +matmul 1x28x60xf64,9107,,1889,, matmul 1x28x64xf64,9714,,2012,, matmul 1x28x8xf64,1227,,298,, -matmul 1x32x12xf64,2100,,482,, +matmul 1x32x12xf64,2100,,485,, matmul 1x32x16xf64,2781,,612,, -matmul 1x32x20xf64,3476,,765,, -matmul 1x32x24xf64,4164,,906,, -matmul 1x32x28xf64,4861,,1032,, +matmul 1x32x20xf64,3476,,759,, +matmul 1x32x24xf64,4164,,896,, +matmul 1x32x28xf64,4861,,1036,, matmul 1x32x32xf64,5534,,1170,, -matmul 1x32x36xf64,6225,,1302,, -matmul 1x32x40xf64,6920,,1440,, +matmul 1x32x36xf64,6225,,1305,, +matmul 1x32x40xf64,6920,,1442,, matmul 1x32x44xf64,7624,,1578,, -matmul 1x32x48xf64,8312,,1716,, +matmul 1x32x48xf64,8312,,1717,, matmul 1x32x4xf64,705,,177,, matmul 1x32x52xf64,9009,,1854,, -matmul 1x32x56xf64,9697,,1992,, -matmul 1x32x60xf64,10386,,2130,, +matmul 1x32x56xf64,9697,,1981,, +matmul 1x32x60xf64,10386,,2129,, matmul 1x32x64xf64,11070,,2268,, matmul 1x32x8xf64,1398,,335,, -matmul 1x36x12xf64,3087,,530,, +matmul 1x36x12xf64,3087,,533,, matmul 1x36x16xf64,4111,,691,, -matmul 1x36x20xf64,5241,,845,, -matmul 1x36x24xf64,6286,,1002,, -matmul 1x36x28xf64,7330,,1144,, +matmul 1x36x20xf64,5241,,832,, +matmul 1x36x24xf64,6286,,992,, +matmul 1x36x28xf64,7330,,1148,, matmul 1x36x32xf64,8374,,1292,, -matmul 1x36x36xf64,9418,,1446,, -matmul 1x36x40xf64,10462,,1600,, +matmul 1x36x36xf64,9418,,1449,, +matmul 1x36x40xf64,10462,,1602,, matmul 1x36x44xf64,11506,,1754,, -matmul 1x36x48xf64,12550,,1908,, +matmul 1x36x48xf64,12550,,1909,, matmul 1x36x4xf64,997,,193,, matmul 1x36x52xf64,13594,,2062,, -matmul 1x36x56xf64,14638,,2216,, -matmul 1x36x60xf64,15682,,2370,, +matmul 1x36x56xf64,14638,,2205,, +matmul 1x36x60xf64,15682,,2369,, matmul 1x36x64xf64,16726,,2524,, matmul 1x36x8xf64,2041,,368,, -matmul 1x40x12xf64,3502,,585,, +matmul 1x40x12xf64,3502,,572,, matmul 1x40x16xf64,4670,,755,, -matmul 1x40x20xf64,5802,,926,, -matmul 1x40x24xf64,6958,,1098,, -matmul 1x40x28xf64,8114,,1256,, +matmul 1x40x20xf64,5802,,919,, +matmul 1x40x24xf64,6958,,1088,, +matmul 1x40x28xf64,8114,,1260,, matmul 1x40x32xf64,9270,,1420,, -matmul 1x40x36xf64,10426,,1590,, -matmul 1x40x40xf64,11582,,1760,, +matmul 1x40x36xf64,10426,,1593,, +matmul 1x40x40xf64,11582,,1755,, matmul 1x40x44xf64,12738,,1930,, -matmul 1x40x48xf64,13894,,2100,, +matmul 1x40x48xf64,13894,,2101,, matmul 1x40x4xf64,1170,,209,, matmul 1x40x52xf64,15050,,2272,, -matmul 1x40x56xf64,16206,,2440,, -matmul 1x40x60xf64,17362,,2610,, +matmul 1x40x56xf64,16206,,2429,, +matmul 1x40x60xf64,17362,,2609,, matmul 1x40x64xf64,18518,,2780,, matmul 1x40x8xf64,2340,,400,, -matmul 1x44x12xf64,3838,,633,, +matmul 1x44x12xf64,3838,,620,, matmul 1x44x16xf64,5118,,819,, -matmul 1x44x20xf64,6362,,1005,, -matmul 1x44x24xf64,7630,,1194,, -matmul 1x44x28xf64,8898,,1368,, +matmul 1x44x20xf64,6362,,999,, +matmul 1x44x24xf64,7630,,1184,, +matmul 1x44x28xf64,8898,,1372,, matmul 1x44x32xf64,10166,,1548,, -matmul 1x44x36xf64,11434,,1734,, -matmul 1x44x40xf64,12702,,1920,, +matmul 1x44x36xf64,11434,,1737,, +matmul 1x44x40xf64,12702,,1922,, matmul 1x44x44xf64,13970,,2106,, -matmul 1x44x48xf64,15238,,2292,, +matmul 1x44x48xf64,15238,,2293,, matmul 1x44x4xf64,1282,,225,, matmul 1x44x52xf64,16506,,2478,, -matmul 1x44x56xf64,17774,,2664,, -matmul 1x44x60xf64,19042,,2850,, +matmul 1x44x56xf64,17774,,2653,, +matmul 1x44x60xf64,19042,,2849,, matmul 1x44x64xf64,20310,,3036,, matmul 1x44x8xf64,2564,,432,, -matmul 1x48x12xf64,4174,,681,, +matmul 1x48x12xf64,4174,,668,, matmul 1x48x16xf64,5566,,883,, -matmul 1x48x20xf64,6922,,1070,, -matmul 1x48x24xf64,8302,,1290,, -matmul 1x48x28xf64,9682,,1480,, +matmul 1x48x20xf64,6922,,1079,, +matmul 1x48x24xf64,8302,,1280,, +matmul 1x48x28xf64,9682,,1484,, matmul 1x48x32xf64,11062,,1676,, -matmul 1x48x36xf64,12442,,1878,, -matmul 1x48x40xf64,13822,,2080,, +matmul 1x48x36xf64,12442,,1881,, +matmul 1x48x40xf64,13822,,2082,, matmul 1x48x44xf64,15202,,2282,, -matmul 1x48x48xf64,16582,,2484,, +matmul 1x48x48xf64,16582,,2485,, matmul 1x48x4xf64,1394,,241,, matmul 1x48x52xf64,17962,,2686,, -matmul 1x48x56xf64,19342,,2888,, -matmul 1x48x60xf64,20722,,3090,, +matmul 1x48x56xf64,19342,,2877,, +matmul 1x48x60xf64,20722,,3089,, matmul 1x48x64xf64,22102,,3292,, matmul 1x48x8xf64,2788,,464,, -matmul 1x4x12xf64,322,,132,, +matmul 1x4x12xf64,322,,128,, matmul 1x4x16xf64,422,,158,, -matmul 1x4x20xf64,522,,184,, -matmul 1x4x24xf64,622,,215,, -matmul 1x4x28xf64,716,,241,, +matmul 1x4x20xf64,522,,182,, +matmul 1x4x24xf64,622,,214,, +matmul 1x4x28xf64,716,,250,, matmul 1x4x32xf64,823,,273,, -matmul 1x4x36xf64,923,,299,, -matmul 1x4x40xf64,1023,,325,, +matmul 1x4x36xf64,923,,293,, +matmul 1x4x40xf64,1023,,314,, matmul 1x4x44xf64,1123,,351,, -matmul 1x4x48xf64,1223,,377,, +matmul 1x4x48xf64,1223,,369,, matmul 1x4x4xf64,121,,65,, matmul 1x4x52xf64,1323,,403,, -matmul 1x4x56xf64,1423,,429,, -matmul 1x4x60xf64,1523,,455,, +matmul 1x4x56xf64,1423,,420,, +matmul 1x4x60xf64,1523,,445,, matmul 1x4x64xf64,1621,,475,, matmul 1x4x8xf64,213,,106,, -matmul 1x52x12xf64,4510,,729,, +matmul 1x52x12xf64,4510,,716,, matmul 1x52x16xf64,6014,,947,, -matmul 1x52x20xf64,7482,,1165,, -matmul 1x52x24xf64,8974,,1386,, -matmul 1x52x28xf64,10466,,1592,, +matmul 1x52x20xf64,7482,,1159,, +matmul 1x52x24xf64,8974,,1374,, +matmul 1x52x28xf64,10466,,1596,, matmul 1x52x32xf64,11958,,1804,, -matmul 1x52x36xf64,13450,,2022,, -matmul 1x52x40xf64,14942,,2240,, +matmul 1x52x36xf64,13450,,2025,, +matmul 1x52x40xf64,14942,,2242,, matmul 1x52x44xf64,16434,,2459,, -matmul 1x52x48xf64,17926,,2676,, +matmul 1x52x48xf64,17926,,2677,, matmul 1x52x4xf64,1523,,262,, matmul 1x52x52xf64,19418,,2894,, -matmul 1x52x56xf64,20910,,3112,, -matmul 1x52x60xf64,22402,,3330,, +matmul 1x52x56xf64,20910,,3101,, +matmul 1x52x60xf64,22402,,3329,, matmul 1x52x64xf64,23894,,3548,, matmul 1x52x8xf64,3012,,496,, -matmul 1x56x12xf64,4846,,777,, +matmul 1x56x12xf64,4846,,764,, matmul 1x56x16xf64,6462,,1011,, -matmul 1x56x20xf64,8042,,1245,, -matmul 1x56x24xf64,9646,,1482,, -matmul 1x56x28xf64,11250,,1704,, +matmul 1x56x20xf64,8042,,1239,, +matmul 1x56x24xf64,9646,,1472,, +matmul 1x56x28xf64,11250,,1708,, matmul 1x56x32xf64,12854,,1932,, -matmul 1x56x36xf64,14458,,2166,, -matmul 1x56x40xf64,16062,,2400,, +matmul 1x56x36xf64,14458,,2169,, +matmul 1x56x40xf64,16062,,2402,, matmul 1x56x44xf64,17666,,2634,, -matmul 1x56x48xf64,19270,,2868,, +matmul 1x56x48xf64,19270,,2869,, matmul 1x56x4xf64,1635,,278,, matmul 1x56x52xf64,20874,,3102,, -matmul 1x56x56xf64,22478,,3336,, -matmul 1x56x60xf64,24082,,3570,, +matmul 1x56x56xf64,22478,,3324,, +matmul 1x56x60xf64,24082,,3569,, matmul 1x56x64xf64,25686,,3804,, matmul 1x56x8xf64,3236,,528,, -matmul 1x60x12xf64,5182,,825,, +matmul 1x60x12xf64,5182,,812,, matmul 1x60x16xf64,6910,,1060,, -matmul 1x60x20xf64,8602,,1325,, -matmul 1x60x24xf64,10318,,1578,, -matmul 1x60x28xf64,12034,,1816,, +matmul 1x60x20xf64,8602,,1319,, +matmul 1x60x24xf64,10318,,1568,, +matmul 1x60x28xf64,12034,,1820,, matmul 1x60x32xf64,13750,,2060,, -matmul 1x60x36xf64,15466,,2310,, -matmul 1x60x40xf64,17182,,2560,, +matmul 1x60x36xf64,15466,,2313,, +matmul 1x60x40xf64,17182,,2562,, matmul 1x60x44xf64,18898,,2810,, -matmul 1x60x48xf64,20614,,3060,, +matmul 1x60x48xf64,20614,,3061,, matmul 1x60x4xf64,1747,,294,, matmul 1x60x52xf64,22330,,3310,, -matmul 1x60x56xf64,24046,,3560,, -matmul 1x60x60xf64,25762,,3810,, +matmul 1x60x56xf64,24046,,3549,, +matmul 1x60x60xf64,25762,,3809,, matmul 1x60x64xf64,27478,,4060,, matmul 1x60x8xf64,3462,,575,, -matmul 1x64x12xf64,5518,,873,, +matmul 1x64x12xf64,5518,,860,, matmul 1x64x16xf64,7358,,1124,, -matmul 1x64x20xf64,9162,,1405,, -matmul 1x64x24xf64,10990,,1674,, -matmul 1x64x28xf64,12818,,1928,, +matmul 1x64x20xf64,9162,,1399,, +matmul 1x64x24xf64,10990,,1662,, +matmul 1x64x28xf64,12818,,1932,, matmul 1x64x32xf64,14646,,2188,, -matmul 1x64x36xf64,16474,,2454,, -matmul 1x64x40xf64,18302,,2720,, +matmul 1x64x36xf64,16474,,2457,, +matmul 1x64x40xf64,18302,,2715,, matmul 1x64x44xf64,20130,,2986,, -matmul 1x64x48xf64,21958,,3252,, +matmul 1x64x48xf64,21958,,3253,, matmul 1x64x4xf64,1859,,316,, matmul 1x64x52xf64,23786,,3518,, -matmul 1x64x56xf64,25614,,3784,, -matmul 1x64x60xf64,27442,,4050,, +matmul 1x64x56xf64,25614,,3772,, +matmul 1x64x60xf64,27442,,4049,, matmul 1x64x64xf64,29270,,4322,, matmul 1x64x8xf64,3686,,592,, -matmul 1x8x12xf64,567,,180,, +matmul 1x8x12xf64,567,,176,, matmul 1x8x16xf64,755,,222,, -matmul 1x8x20xf64,935,,265,, -matmul 1x8x24xf64,1130,,311,, -matmul 1x8x28xf64,1312,,368,, +matmul 1x8x20xf64,935,,262,, +matmul 1x8x24xf64,1130,,310,, +matmul 1x8x28xf64,1312,,353,, matmul 1x8x32xf64,1495,,395,, -matmul 1x8x36xf64,1679,,437,, -matmul 1x8x40xf64,1863,,480,, +matmul 1x8x36xf64,1679,,440,, +matmul 1x8x40xf64,1863,,482,, matmul 1x8x44xf64,2047,,522,, -matmul 1x8x48xf64,2231,,564,, +matmul 1x8x48xf64,2231,,565,, matmul 1x8x4xf64,202,,81,, matmul 1x8x52xf64,2415,,608,, -matmul 1x8x56xf64,2599,,648,, -matmul 1x8x60xf64,2783,,690,, +matmul 1x8x56xf64,2599,,637,, +matmul 1x8x60xf64,2783,,689,, matmul 1x8x64xf64,2972,,732,, matmul 1x8x8xf64,381,,138,, -matmul 4x12x12xf64,3277,,772,, +matmul 4x12x12xf64,3277,,755,, matmul 4x12x16xf64,4344,,1004,, -matmul 4x12x20xf64,5423,,1236,, -matmul 4x12x24xf64,6495,,1462,, -matmul 4x12x28xf64,7567,,1694,, +matmul 4x12x20xf64,5423,,1220,, +matmul 4x12x24xf64,6495,,1445,, +matmul 4x12x28xf64,7567,,1668,, matmul 4x12x32xf64,8641,,1926,, -matmul 4x12x36xf64,9713,,2158,, -matmul 4x12x40xf64,10786,,2390,, +matmul 4x12x36xf64,9713,,2133,, +matmul 4x12x40xf64,10786,,2373,, matmul 4x12x44xf64,11852,,2622,, -matmul 4x12x48xf64,12924,,2854,, +matmul 4x12x48xf64,12924,,2821,, matmul 4x12x4xf64,1088,,290,, matmul 4x12x52xf64,13996,,3086,, -matmul 4x12x56xf64,15068,,3318,, -matmul 4x12x60xf64,16140,,3550,, +matmul 4x12x56xf64,15068,,3268,, +matmul 4x12x60xf64,16140,,3509,, matmul 4x12x64xf64,17212,,3782,, matmul 4x12x8xf64,2200,,540,, -matmul 4x16x12xf64,4288,,964,, +matmul 4x16x12xf64,4288,,947,, matmul 4x16x16xf64,5696,,1260,, -matmul 4x16x20xf64,7104,,1550,, -matmul 4x16x24xf64,8520,,1846,, -matmul 4x16x28xf64,9928,,2142,, +matmul 4x16x20xf64,7104,,1541,, +matmul 4x16x24xf64,8520,,1829,, +matmul 4x16x28xf64,9928,,2116,, matmul 4x16x32xf64,11329,,2437,, -matmul 4x16x36xf64,12743,,2734,, -matmul 4x16x40xf64,14159,,3030,, +matmul 4x16x36xf64,12743,,2709,, +matmul 4x16x40xf64,14159,,3013,, matmul 4x16x44xf64,15568,,3326,, -matmul 4x16x48xf64,16976,,3622,, +matmul 4x16x48xf64,16976,,3589,, matmul 4x16x4xf64,1424,,354,, matmul 4x16x52xf64,18379,,3918,, -matmul 4x16x56xf64,19787,,4214,, -matmul 4x16x60xf64,21195,,4510,, +matmul 4x16x56xf64,19787,,4164,, +matmul 4x16x60xf64,21195,,4475,, matmul 4x16x64xf64,22605,,4805,, matmul 4x16x8xf64,2880,,668,, -matmul 4x20x12xf64,5342,,1156,, +matmul 4x20x12xf64,5342,,1139,, matmul 4x20x16xf64,7102,,1510,, -matmul 4x20x20xf64,8825,,1870,, -matmul 4x20x24xf64,10574,,2230,, -matmul 4x20x28xf64,12331,,2590,, +matmul 4x20x20xf64,8825,,1861,, +matmul 4x20x24xf64,10574,,2213,, +matmul 4x20x28xf64,12331,,2564,, matmul 4x20x32xf64,14092,,2950,, -matmul 4x20x36xf64,15843,,3310,, -matmul 4x20x40xf64,17578,,3670,, +matmul 4x20x36xf64,15843,,3285,, +matmul 4x20x40xf64,17578,,3653,, matmul 4x20x44xf64,19330,,4030,, -matmul 4x20x48xf64,21074,,4390,, +matmul 4x20x48xf64,21074,,4357,, matmul 4x20x4xf64,1852,,418,, matmul 4x20x52xf64,22895,,4750,, -matmul 4x20x56xf64,24639,,5110,, -matmul 4x20x60xf64,26383,,5470,, +matmul 4x20x56xf64,24639,,5060,, +matmul 4x20x60xf64,26383,,5429,, matmul 4x20x64xf64,28147,,5830,, matmul 4x20x8xf64,3598,,796,, -matmul 4x24x12xf64,6405,,1342,, +matmul 4x24x12xf64,6405,,1333,, matmul 4x24x16xf64,8490,,1766,, -matmul 4x24x20xf64,10570,,2190,, -matmul 4x24x24xf64,12726,,2613,, -matmul 4x24x28xf64,14800,,3038,, +matmul 4x24x20xf64,10570,,2181,, +matmul 4x24x24xf64,12726,,2603,, +matmul 4x24x28xf64,14800,,3019,, matmul 4x24x32xf64,16809,,3462,, -matmul 4x24x36xf64,19069,,3886,, -matmul 4x24x40xf64,22109,,4310,, +matmul 4x24x36xf64,19069,,3861,, +matmul 4x24x40xf64,22109,,4293,, matmul 4x24x44xf64,23509,,4734,, -matmul 4x24x48xf64,25628,,5158,, +matmul 4x24x48xf64,25628,,5125,, matmul 4x24x4xf64,2229,,482,, matmul 4x24x52xf64,28804,,5582,, -matmul 4x24x56xf64,30995,,6006,, -matmul 4x24x60xf64,33187,,6430,, +matmul 4x24x56xf64,30995,,5956,, +matmul 4x24x60xf64,33187,,6395,, matmul 4x24x64xf64,36914,,6853,, matmul 4x24x8xf64,4325,,924,, -matmul 4x28x12xf64,7498,,1534,, +matmul 4x28x12xf64,7498,,1525,, matmul 4x28x16xf64,9914,,2022,, -matmul 4x28x20xf64,12845,,2510,, -matmul 4x28x24xf64,15357,,2998,, -matmul 4x28x28xf64,17874,,3485,, +matmul 4x28x20xf64,12845,,2501,, +matmul 4x28x24xf64,15357,,2981,, +matmul 4x28x28xf64,17874,,3460,, matmul 4x28x32xf64,21742,,3974,, -matmul 4x28x36xf64,24439,,4462,, -matmul 4x28x40xf64,26559,,4950,, +matmul 4x28x36xf64,24439,,4437,, +matmul 4x28x40xf64,26559,,4933,, matmul 4x28x44xf64,30074,,5438,, -matmul 4x28x48xf64,32784,,5926,, +matmul 4x28x48xf64,32784,,5893,, matmul 4x28x4xf64,2661,,546,, matmul 4x28x52xf64,37580,,6414,, -matmul 4x28x56xf64,40444,,6902,, -matmul 4x28x60xf64,43776,,7390,, +matmul 4x28x56xf64,40444,,6852,, +matmul 4x28x60xf64,43776,,7349,, matmul 4x28x64xf64,46207,,7878,, matmul 4x28x8xf64,5082,,1052,, -matmul 4x32x12xf64,10822,,1726,, +matmul 4x32x12xf64,10822,,1723,, matmul 4x32x16xf64,14581,,2277,, -matmul 4x32x20xf64,17480,,2830,, -matmul 4x32x24xf64,20955,,3382,, -matmul 4x32x28xf64,24448,,3934,, +matmul 4x32x20xf64,17480,,2827,, +matmul 4x32x24xf64,20955,,3365,, +matmul 4x32x28xf64,24448,,3908,, matmul 4x32x32xf64,27936,,4485,, -matmul 4x32x36xf64,31411,,5038,, -matmul 4x32x40xf64,34908,,5590,, +matmul 4x32x36xf64,31411,,5013,, +matmul 4x32x40xf64,34908,,5573,, matmul 4x32x44xf64,38413,,6142,, -matmul 4x32x48xf64,41897,,6693,, +matmul 4x32x48xf64,41897,,6667,, matmul 4x32x4xf64,3302,,608,, matmul 4x32x52xf64,45385,,7246,, -matmul 4x32x56xf64,48869,,7798,, -matmul 4x32x60xf64,52357,,8350,, +matmul 4x32x56xf64,48869,,7748,, +matmul 4x32x60xf64,52357,,8315,, matmul 4x32x64xf64,55841,,8901,, matmul 4x32x8xf64,7141,,1172,, -matmul 4x36x12xf64,12455,,1918,, +matmul 4x36x12xf64,12455,,1909,, matmul 4x36x16xf64,16678,,2534,, -matmul 4x36x20xf64,20955,,3150,, -matmul 4x36x24xf64,25131,,3766,, -matmul 4x36x28xf64,29307,,4382,, +matmul 4x36x20xf64,20955,,3147,, +matmul 4x36x24xf64,25131,,3749,, +matmul 4x36x28xf64,29307,,4356,, matmul 4x36x32xf64,33483,,4998,, -matmul 4x36x36xf64,37653,,5614,, -matmul 4x36x40xf64,41835,,6230,, +matmul 4x36x36xf64,37653,,5596,, +matmul 4x36x40xf64,41835,,6213,, matmul 4x36x44xf64,46011,,6846,, -matmul 4x36x48xf64,50187,,7462,, +matmul 4x36x48xf64,50187,,7429,, matmul 4x36x4xf64,4120,,672,, matmul 4x36x52xf64,54363,,8078,, -matmul 4x36x56xf64,58539,,8694,, -matmul 4x36x60xf64,62715,,9310,, +matmul 4x36x56xf64,58539,,8644,, +matmul 4x36x60xf64,62715,,9269,, matmul 4x36x64xf64,66891,,9926,, matmul 4x36x8xf64,8352,,1302,, -matmul 4x40x12xf64,13799,,2110,, +matmul 4x40x12xf64,13799,,2101,, matmul 4x40x16xf64,18470,,2790,, -matmul 4x40x20xf64,23195,,3472,, -matmul 4x40x24xf64,27819,,4150,, -matmul 4x40x28xf64,32443,,4830,, +matmul 4x40x20xf64,23195,,3461,, +matmul 4x40x24xf64,27819,,4133,, +matmul 4x40x28xf64,32443,,4811,, matmul 4x40x32xf64,37067,,5510,, -matmul 4x40x36xf64,41691,,6190,, -matmul 4x40x40xf64,46309,,6869,, +matmul 4x40x36xf64,41691,,6165,, +matmul 4x40x40xf64,46309,,6853,, matmul 4x40x44xf64,50939,,7550,, -matmul 4x40x48xf64,55563,,8230,, +matmul 4x40x48xf64,55563,,8197,, matmul 4x40x4xf64,4643,,736,, matmul 4x40x52xf64,60187,,8916,, -matmul 4x40x56xf64,64811,,9590,, -matmul 4x40x60xf64,69429,,10270,, +matmul 4x40x56xf64,64811,,9547,, +matmul 4x40x60xf64,69429,,10235,, matmul 4x40x64xf64,74053,,10949,, matmul 4x40x8xf64,9248,,1430,, -matmul 4x44x12xf64,15143,,2302,, +matmul 4x44x12xf64,15143,,2293,, matmul 4x44x16xf64,20262,,3046,, -matmul 4x44x20xf64,25435,,3790,, -matmul 4x44x24xf64,30507,,4534,, -matmul 4x44x28xf64,35579,,5278,, +matmul 4x44x20xf64,25435,,3781,, +matmul 4x44x24xf64,30507,,4517,, +matmul 4x44x28xf64,35579,,5259,, matmul 4x44x32xf64,40651,,6022,, -matmul 4x44x36xf64,45723,,6766,, -matmul 4x44x40xf64,50795,,7510,, +matmul 4x44x36xf64,45723,,6741,, +matmul 4x44x40xf64,50795,,7499,, matmul 4x44x44xf64,55861,,8253,, -matmul 4x44x48xf64,60939,,8998,, +matmul 4x44x48xf64,60939,,8965,, matmul 4x44x4xf64,5091,,800,, matmul 4x44x52xf64,66011,,9742,, -matmul 4x44x56xf64,71083,,10486,, -matmul 4x44x60xf64,76155,,11230,, +matmul 4x44x56xf64,71083,,10436,, +matmul 4x44x60xf64,76155,,11189,, matmul 4x44x64xf64,81227,,11974,, matmul 4x44x8xf64,10147,,1558,, -matmul 4x48x12xf64,16487,,2494,, +matmul 4x48x12xf64,16487,,2485,, matmul 4x48x16xf64,22054,,3302,, -matmul 4x48x20xf64,27675,,4110,, -matmul 4x48x24xf64,33195,,4918,, -matmul 4x48x28xf64,38709,,5726,, +matmul 4x48x20xf64,27675,,4101,, +matmul 4x48x24xf64,33195,,4901,, +matmul 4x48x28xf64,38709,,5700,, matmul 4x48x32xf64,44229,,6533,, -matmul 4x48x36xf64,49755,,7342,, -matmul 4x48x40xf64,55275,,8150,, +matmul 4x48x36xf64,49755,,7317,, +matmul 4x48x40xf64,55275,,8133,, matmul 4x48x44xf64,60795,,8958,, -matmul 4x48x48xf64,66309,,9765,, +matmul 4x48x48xf64,66309,,9739,, matmul 4x48x4xf64,5539,,864,, matmul 4x48x52xf64,71835,,10574,, -matmul 4x48x56xf64,77355,,11382,, -matmul 4x48x60xf64,82869,,12190,, +matmul 4x48x56xf64,77355,,11339,, +matmul 4x48x60xf64,82869,,12155,, matmul 4x48x64xf64,88389,,12997,, matmul 4x48x8xf64,11043,,1686,, -matmul 4x4x12xf64,1231,,388,, +matmul 4x4x12xf64,1231,,371,, matmul 4x4x16xf64,1631,,492,, -matmul 4x4x20xf64,2031,,596,, -matmul 4x4x24xf64,2431,,700,, -matmul 4x4x28xf64,2831,,804,, +matmul 4x4x20xf64,2031,,580,, +matmul 4x4x24xf64,2431,,675,, +matmul 4x4x28xf64,2831,,777,, matmul 4x4x32xf64,3231,,908,, -matmul 4x4x36xf64,3631,,1012,, -matmul 4x4x40xf64,4031,,1116,, +matmul 4x4x36xf64,3631,,979,, +matmul 4x4x40xf64,4031,,1092,, matmul 4x4x44xf64,4431,,1220,, -matmul 4x4x48xf64,4831,,1324,, +matmul 4x4x48xf64,4831,,1283,, matmul 4x4x4xf64,419,,162,, matmul 4x4x52xf64,5231,,1428,, -matmul 4x4x56xf64,5631,,1532,, -matmul 4x4x60xf64,6031,,1636,, +matmul 4x4x56xf64,5631,,1481,, +matmul 4x4x60xf64,6031,,1587,, matmul 4x4x64xf64,6431,,1740,, matmul 4x4x8xf64,831,,284,, -matmul 4x52x12xf64,17831,,2686,, +matmul 4x52x12xf64,17831,,2677,, matmul 4x52x16xf64,23846,,3558,, -matmul 4x52x20xf64,29915,,4430,, -matmul 4x52x24xf64,35883,,5302,, -matmul 4x52x28xf64,41851,,6174,, +matmul 4x52x20xf64,29915,,4421,, +matmul 4x52x24xf64,35883,,5285,, +matmul 4x52x28xf64,41851,,6148,, matmul 4x52x32xf64,47819,,7046,, -matmul 4x52x36xf64,53787,,7918,, -matmul 4x52x40xf64,59755,,8790,, +matmul 4x52x36xf64,53787,,7893,, +matmul 4x52x40xf64,59755,,8773,, matmul 4x52x44xf64,65723,,9662,, -matmul 4x52x48xf64,71691,,10534,, +matmul 4x52x48xf64,71691,,10501,, matmul 4x52x4xf64,5987,,928,, matmul 4x52x52xf64,77659,,11406,, -matmul 4x52x56xf64,83627,,12278,, -matmul 4x52x60xf64,89595,,13150,, +matmul 4x52x56xf64,83627,,12228,, +matmul 4x52x60xf64,89595,,13109,, matmul 4x52x64xf64,95563,,14022,, matmul 4x52x8xf64,11939,,1814,, -matmul 4x56x12xf64,19175,,2878,, +matmul 4x56x12xf64,19175,,2869,, matmul 4x56x16xf64,25638,,3814,, -matmul 4x56x20xf64,32155,,4750,, -matmul 4x56x24xf64,38571,,5686,, -matmul 4x56x28xf64,44987,,6622,, +matmul 4x56x20xf64,32155,,4747,, +matmul 4x56x24xf64,38571,,5669,, +matmul 4x56x28xf64,44987,,6603,, matmul 4x56x32xf64,51403,,7558,, -matmul 4x56x36xf64,57819,,8494,, -matmul 4x56x40xf64,64235,,9430,, +matmul 4x56x36xf64,57819,,8469,, +matmul 4x56x40xf64,64235,,9419,, matmul 4x56x44xf64,70651,,10366,, -matmul 4x56x48xf64,77067,,11302,, +matmul 4x56x48xf64,77067,,11269,, matmul 4x56x4xf64,6435,,992,, matmul 4x56x52xf64,83483,,12238,, -matmul 4x56x56xf64,89899,,13174,, -matmul 4x56x60xf64,96309,,14110,, +matmul 4x56x56xf64,89899,,13124,, +matmul 4x56x60xf64,96309,,14075,, matmul 4x56x64xf64,102725,,15045,, matmul 4x56x8xf64,12835,,1942,, -matmul 4x60x12xf64,20519,,3070,, +matmul 4x60x12xf64,20519,,3061,, matmul 4x60x16xf64,27430,,4070,, -matmul 4x60x20xf64,34395,,5070,, -matmul 4x60x24xf64,41259,,6070,, -matmul 4x60x28xf64,48123,,7070,, +matmul 4x60x20xf64,34395,,5067,, +matmul 4x60x24xf64,41259,,6053,, +matmul 4x60x28xf64,48123,,7051,, matmul 4x60x32xf64,54987,,8070,, -matmul 4x60x36xf64,61851,,9070,, -matmul 4x60x40xf64,68715,,10070,, +matmul 4x60x36xf64,61851,,9045,, +matmul 4x60x40xf64,68715,,10053,, matmul 4x60x44xf64,75579,,11070,, -matmul 4x60x48xf64,82443,,12070,, +matmul 4x60x48xf64,82443,,12037,, matmul 4x60x4xf64,6883,,1056,, matmul 4x60x52xf64,89307,,13070,, -matmul 4x60x56xf64,96171,,14070,, -matmul 4x60x60xf64,103035,,15070,, +matmul 4x60x56xf64,96171,,14020,, +matmul 4x60x60xf64,103035,,15029,, matmul 4x60x64xf64,109899,,16070,, matmul 4x60x8xf64,13731,,2070,, -matmul 4x64x12xf64,21863,,3262,, +matmul 4x64x12xf64,21863,,3253,, matmul 4x64x16xf64,29230,,4331,, -matmul 4x64x20xf64,36635,,5390,, -matmul 4x64x24xf64,43941,,6459,, -matmul 4x64x28xf64,51259,,7518,, +matmul 4x64x20xf64,36635,,5387,, +matmul 4x64x24xf64,43941,,6437,, +matmul 4x64x28xf64,51259,,7499,, matmul 4x64x32xf64,58565,,8587,, -matmul 4x64x36xf64,65883,,9646,, -matmul 4x64x40xf64,73189,,10715,, +matmul 4x64x36xf64,65883,,9621,, +matmul 4x64x40xf64,73189,,10699,, matmul 4x64x44xf64,80507,,11774,, -matmul 4x64x48xf64,87813,,12843,, +matmul 4x64x48xf64,87813,,12805,, matmul 4x64x4xf64,7328,,1125,, matmul 4x64x52xf64,95131,,13902,, -matmul 4x64x56xf64,102437,,14971,, -matmul 4x64x60xf64,109755,,16030,, +matmul 4x64x56xf64,102437,,14923,, +matmul 4x64x60xf64,109755,,15989,, matmul 4x64x64xf64,117067,,17099,, matmul 4x64x8xf64,14627,,2203,, -matmul 4x8x12xf64,2239,,580,, +matmul 4x8x12xf64,2239,,563,, matmul 4x8x16xf64,2975,,748,, -matmul 4x8x20xf64,3711,,918,, -matmul 4x8x24xf64,4447,,1084,, -matmul 4x8x28xf64,5183,,1252,, +matmul 4x8x20xf64,3711,,900,, +matmul 4x8x24xf64,4447,,1059,, +matmul 4x8x28xf64,5183,,1219,, matmul 4x8x32xf64,5911,,1412,, -matmul 4x8x36xf64,6647,,1581,, -matmul 4x8x40xf64,7383,,1750,, +matmul 4x8x36xf64,6647,,1562,, +matmul 4x8x40xf64,7383,,1733,, matmul 4x8x44xf64,8119,,1918,, -matmul 4x8x48xf64,8855,,2086,, +matmul 4x8x48xf64,8855,,2053,, matmul 4x8x4xf64,752,,226,, matmul 4x8x52xf64,9589,,2260,, -matmul 4x8x56xf64,10325,,2422,, -matmul 4x8x60xf64,11061,,2590,, +matmul 4x8x56xf64,10325,,2372,, +matmul 4x8x60xf64,11061,,2555,, matmul 4x8x64xf64,11805,,2757,, matmul 4x8x8xf64,1504,,412,, -matmul 8x12x12xf64,6505,,1468,, +matmul 8x12x12xf64,6505,,1443,, matmul 8x12x16xf64,8651,,1932,, -matmul 8x12x20xf64,10795,,2396,, -matmul 8x12x24xf64,12939,,2854,, -matmul 8x12x28xf64,15083,,3318,, +matmul 8x12x20xf64,10795,,2372,, +matmul 8x12x24xf64,12939,,2821,, +matmul 8x12x28xf64,15083,,3268,, matmul 8x12x32xf64,17245,,3782,, -matmul 8x12x36xf64,19387,,4245,, -matmul 8x12x40xf64,21518,,4709,, +matmul 8x12x36xf64,19387,,4203,, +matmul 8x12x40xf64,21518,,4677,, matmul 8x12x44xf64,23656,,5173,, -matmul 8x12x48xf64,25800,,5637,, +matmul 8x12x48xf64,25800,,5579,, matmul 8x12x4xf64,2164,,520,, matmul 8x12x52xf64,27944,,6101,, -matmul 8x12x56xf64,30088,,6566,, -matmul 8x12x60xf64,32232,,7030,, +matmul 8x12x56xf64,30088,,6468,, +matmul 8x12x60xf64,32232,,6949,, matmul 8x12x64xf64,34376,,7493,, matmul 8x12x8xf64,4356,,1004,, -matmul 8x16x12xf64,8528,,1852,, +matmul 8x16x12xf64,8528,,1827,, matmul 8x16x16xf64,11344,,2444,, -matmul 8x16x20xf64,14160,,3030,, -matmul 8x16x24xf64,16992,,3622,, -matmul 8x16x28xf64,19808,,4214,, +matmul 8x16x20xf64,14160,,3013,, +matmul 8x16x24xf64,16992,,3595,, +matmul 8x16x28xf64,19808,,4164,, matmul 8x16x32xf64,22609,,4805,, -matmul 8x16x36xf64,25425,,5397,, -matmul 8x16x40xf64,28255,,5990,, +matmul 8x16x36xf64,25425,,5355,, +matmul 8x16x40xf64,28255,,5957,, matmul 8x16x44xf64,31072,,6582,, -matmul 8x16x48xf64,33888,,7174,, +matmul 8x16x48xf64,33888,,7109,, matmul 8x16x4xf64,2836,,648,, matmul 8x16x52xf64,36699,,7766,, -matmul 8x16x56xf64,39515,,8358,, -matmul 8x16x60xf64,42331,,8950,, +matmul 8x16x56xf64,39515,,8260,, +matmul 8x16x60xf64,42331,,8869,, matmul 8x16x64xf64,45149,,9541,, matmul 8x16x8xf64,5718,,1260,, -matmul 8x20x12xf64,10622,,2236,, +matmul 8x20x12xf64,10622,,2211,, matmul 8x20x16xf64,14138,,2950,, -matmul 8x20x20xf64,17589,,3669,, -matmul 8x20x24xf64,21086,,4390,, -matmul 8x20x28xf64,24591,,5110,, +matmul 8x20x20xf64,17589,,3653,, +matmul 8x20x24xf64,21086,,4357,, +matmul 8x20x28xf64,24591,,5060,, matmul 8x20x32xf64,28128,,5830,, -matmul 8x20x36xf64,31617,,6550,, -matmul 8x20x40xf64,35102,,7270,, +matmul 8x20x36xf64,31617,,6501,, +matmul 8x20x40xf64,35102,,7237,, matmul 8x20x44xf64,38598,,7990,, -matmul 8x20x48xf64,42086,,8710,, +matmul 8x20x48xf64,42086,,8645,, matmul 8x20x4xf64,3646,,776,, matmul 8x20x52xf64,45699,,9430,, -matmul 8x20x56xf64,49187,,10150,, -matmul 8x20x60xf64,52675,,10870,, +matmul 8x20x56xf64,49187,,10059,, +matmul 8x20x60xf64,52675,,10789,, matmul 8x20x64xf64,56211,,11589,, matmul 8x20x8xf64,7134,,1516,, -matmul 8x24x12xf64,12749,,2614,, +matmul 8x24x12xf64,12749,,2597,, matmul 8x24x16xf64,16926,,3462,, -matmul 8x24x20xf64,21086,,4310,, -matmul 8x24x24xf64,25380,,5158,, -matmul 8x24x28xf64,29540,,6006,, +matmul 8x24x20xf64,21086,,4293,, +matmul 8x24x24xf64,25380,,5125,, +matmul 8x24x28xf64,29540,,5963,, matmul 8x24x32xf64,33537,,6854,, -matmul 8x24x36xf64,38065,,7702,, -matmul 8x24x40xf64,44149,,8550,, +matmul 8x24x36xf64,38065,,7653,, +matmul 8x24x40xf64,44149,,8517,, matmul 8x24x44xf64,46945,,9398,, -matmul 8x24x48xf64,51176,,10246,, +matmul 8x24x48xf64,51176,,10181,, matmul 8x24x4xf64,4429,,909,, matmul 8x24x52xf64,57524,,11094,, -matmul 8x24x56xf64,61903,,11942,, -matmul 8x24x60xf64,66287,,12790,, +matmul 8x24x56xf64,61903,,11844,, +matmul 8x24x60xf64,66287,,12709,, matmul 8x24x64xf64,73744,,13637,, matmul 8x24x8xf64,8589,,1772,, -matmul 8x28x12xf64,14942,,2998,, +matmul 8x28x12xf64,14942,,2981,, matmul 8x28x16xf64,19774,,3974,, -matmul 8x28x20xf64,25625,,4950,, -matmul 8x28x24xf64,30649,,5926,, -matmul 8x28x28xf64,35682,,6901,, +matmul 8x28x20xf64,25625,,4939,, +matmul 8x28x24xf64,30649,,5893,, +matmul 8x28x28xf64,35682,,6852,, matmul 8x28x32xf64,43406,,7878,, -matmul 8x28x36xf64,48791,,8854,, -matmul 8x28x40xf64,53031,,9830,, +matmul 8x28x36xf64,48791,,8805,, +matmul 8x28x40xf64,53031,,9803,, matmul 8x28x44xf64,60062,,10806,, -matmul 8x28x48xf64,65476,,11782,, +matmul 8x28x48xf64,65476,,11717,, matmul 8x28x4xf64,5278,,1037,, matmul 8x28x52xf64,75068,,12758,, -matmul 8x28x56xf64,80796,,13734,, -matmul 8x28x60xf64,87460,,14710,, +matmul 8x28x56xf64,80796,,13643,, +matmul 8x28x60xf64,87460,,14629,, matmul 8x28x64xf64,92303,,15685,, matmul 8x28x8xf64,10116,,2028,, -matmul 8x32x12xf64,21518,,3387,, +matmul 8x32x12xf64,21518,,3365,, matmul 8x32x16xf64,29033,,4491,, -matmul 8x32x20xf64,36169,,5595,, -matmul 8x32x24xf64,43384,,6694,, -matmul 8x32x28xf64,50605,,7803,, +matmul 8x32x20xf64,36169,,5579,, +matmul 8x32x24xf64,43384,,6661,, +matmul 8x32x28xf64,50605,,7755,, matmul 8x32x32xf64,57815,,8907,, -matmul 8x32x36xf64,65034,,10011,, -matmul 8x32x40xf64,72284,,11110,, +matmul 8x32x36xf64,65034,,9957,, +matmul 8x32x40xf64,72284,,11077,, matmul 8x32x44xf64,79552,,12219,, -matmul 8x32x48xf64,86772,,13323,, +matmul 8x32x48xf64,86772,,13253,, matmul 8x32x4xf64,6550,,1159,, matmul 8x32x52xf64,94050,,14427,, -matmul 8x32x56xf64,101274,,15526,, -matmul 8x32x60xf64,108504,,16635,, +matmul 8x32x56xf64,101274,,15428,, +matmul 8x32x60xf64,108504,,16549,, matmul 8x32x64xf64,115808,,17739,, matmul 8x32x8xf64,14221,,2282,, -matmul 8x36x12xf64,24815,,3771,, +matmul 8x36x12xf64,24815,,3749,, matmul 8x36x16xf64,33234,,5003,, -matmul 8x36x20xf64,41881,,6235,, -matmul 8x36x24xf64,50233,,7467,, -matmul 8x36x28xf64,58585,,8699,, +matmul 8x36x20xf64,41881,,6219,, +matmul 8x36x24xf64,50233,,7429,, +matmul 8x36x28xf64,58585,,8651,, matmul 8x36x32xf64,66937,,9931,, -matmul 8x36x36xf64,75297,,11164,, -matmul 8x36x40xf64,83681,,12395,, +matmul 8x36x36xf64,75297,,11110,, +matmul 8x36x40xf64,83681,,12363,, matmul 8x36x44xf64,92083,,13627,, -matmul 8x36x48xf64,100443,,14859,, +matmul 8x36x48xf64,100443,,14789,, matmul 8x36x4xf64,8316,,1287,, matmul 8x36x52xf64,108857,,16091,, -matmul 8x36x56xf64,117221,,17323,, -matmul 8x36x60xf64,125585,,18555,, +matmul 8x36x56xf64,117221,,17227,, +matmul 8x36x60xf64,125585,,18469,, matmul 8x36x64xf64,134014,,19787,, matmul 8x36x8xf64,16627,,2539,, -matmul 8x40x12xf64,27503,,4155,, +matmul 8x40x12xf64,27503,,4133,, matmul 8x40x16xf64,36818,,5515,, -matmul 8x40x20xf64,46363,,6879,, -matmul 8x40x24xf64,55611,,8235,, -matmul 8x40x28xf64,64859,,9595,, +matmul 8x40x20xf64,46363,,6859,, +matmul 8x40x24xf64,55611,,8197,, +matmul 8x40x28xf64,64859,,9547,, matmul 8x40x32xf64,74107,,10955,, -matmul 8x40x36xf64,83355,,12315,, -matmul 8x40x40xf64,92643,,13675,, +matmul 8x40x36xf64,83355,,12261,, +matmul 8x40x40xf64,92643,,13643,, matmul 8x40x44xf64,101941,,15035,, -matmul 8x40x48xf64,111197,,16395,, +matmul 8x40x48xf64,111197,,16325,, matmul 8x40x4xf64,9212,,1415,, matmul 8x40x52xf64,120511,,17767,, -matmul 8x40x56xf64,129766,,19110,, -matmul 8x40x60xf64,139031,,20475,, +matmul 8x40x56xf64,129766,,19019,, +matmul 8x40x60xf64,139031,,20389,, matmul 8x40x64xf64,148343,,21835,, matmul 8x40x8xf64,18419,,2795,, -matmul 8x44x12xf64,30191,,4539,, +matmul 8x44x12xf64,30191,,4517,, matmul 8x44x16xf64,40402,,6027,, -matmul 8x44x20xf64,50843,,7515,, -matmul 8x44x24xf64,60987,,9003,, -matmul 8x44x28xf64,71131,,10491,, +matmul 8x44x20xf64,50843,,7499,, +matmul 8x44x24xf64,60987,,8965,, +matmul 8x44x28xf64,71131,,10443,, matmul 8x44x32xf64,81275,,11979,, -matmul 8x44x36xf64,91419,,13467,, -matmul 8x44x40xf64,101603,,14955,, +matmul 8x44x36xf64,91419,,13413,, +matmul 8x44x40xf64,101603,,14923,, matmul 8x44x44xf64,111796,,16443,, -matmul 8x44x48xf64,121949,,17931,, +matmul 8x44x48xf64,121949,,17861,, matmul 8x44x4xf64,10108,,1543,, matmul 8x44x52xf64,132159,,19419,, -matmul 8x44x56xf64,142315,,20907,, -matmul 8x44x60xf64,152471,,22395,, +matmul 8x44x56xf64,142315,,20811,, +matmul 8x44x60xf64,152471,,22309,, matmul 8x44x64xf64,162679,,23883,, matmul 8x44x8xf64,20211,,3051,, -matmul 8x48x12xf64,32879,,4923,, +matmul 8x48x12xf64,32879,,4901,, matmul 8x48x16xf64,43986,,6539,, -matmul 8x48x20xf64,55323,,8155,, -matmul 8x48x24xf64,66363,,9766,, -matmul 8x48x28xf64,77403,,11387,, +matmul 8x48x20xf64,55323,,8133,, +matmul 8x48x24xf64,66363,,9733,, +matmul 8x48x28xf64,77403,,11339,, matmul 8x48x32xf64,88443,,13003,, -matmul 8x48x36xf64,99483,,14619,, -matmul 8x48x40xf64,110563,,16235,, +matmul 8x48x36xf64,99483,,14565,, +matmul 8x48x40xf64,110563,,16203,, matmul 8x48x44xf64,121653,,17851,, -matmul 8x48x48xf64,132700,,19467,, +matmul 8x48x48xf64,132700,,19397,, matmul 8x48x4xf64,11004,,1671,, matmul 8x48x52xf64,143807,,21083,, -matmul 8x48x56xf64,154854,,22694,, -matmul 8x48x60xf64,165911,,24315,, +matmul 8x48x56xf64,154854,,22603,, +matmul 8x48x60xf64,165911,,24229,, matmul 8x48x64xf64,177015,,25931,, matmul 8x48x8xf64,22003,,3307,, -matmul 8x4x12xf64,2435,,700,, +matmul 8x4x12xf64,2435,,675,, matmul 8x4x16xf64,3235,,908,, -matmul 8x4x20xf64,4035,,1116,, -matmul 8x4x24xf64,4835,,1324,, -matmul 8x4x28xf64,5635,,1532,, +matmul 8x4x20xf64,4035,,1092,, +matmul 8x4x24xf64,4835,,1283,, +matmul 8x4x28xf64,5635,,1481,, matmul 8x4x32xf64,6435,,1732,, -matmul 8x4x36xf64,7235,,1948,, -matmul 8x4x40xf64,8035,,2156,, +matmul 8x4x36xf64,7235,,1891,, +matmul 8x4x40xf64,8035,,2116,, matmul 8x4x44xf64,8835,,2364,, -matmul 8x4x48xf64,9635,,2572,, +matmul 8x4x48xf64,9635,,2499,, matmul 8x4x4xf64,822,,263,, matmul 8x4x52xf64,10435,,2780,, -matmul 8x4x56xf64,11238,,2988,, -matmul 8x4x60xf64,12038,,3196,, +matmul 8x4x56xf64,11238,,2883,, +matmul 8x4x60xf64,12038,,3107,, matmul 8x4x64xf64,12838,,3404,, matmul 8x4x8xf64,1631,,492,, -matmul 8x52x12xf64,35567,,5307,, +matmul 8x52x12xf64,35567,,5285,, matmul 8x52x16xf64,47570,,7051,, -matmul 8x52x20xf64,59807,,8795,, -matmul 8x52x24xf64,71743,,10539,, -matmul 8x52x28xf64,83679,,12283,, +matmul 8x52x20xf64,59807,,8773,, +matmul 8x52x24xf64,71743,,10501,, +matmul 8x52x28xf64,83679,,12235,, matmul 8x52x32xf64,95615,,14027,, -matmul 8x52x36xf64,107551,,15771,, -matmul 8x52x40xf64,119527,,17515,, +matmul 8x52x36xf64,107551,,15717,, +matmul 8x52x40xf64,119527,,17483,, matmul 8x52x44xf64,131516,,19259,, -matmul 8x52x48xf64,143460,,21003,, +matmul 8x52x48xf64,143460,,20933,, matmul 8x52x4xf64,11900,,1799,, matmul 8x52x52xf64,155444,,22747,, -matmul 8x52x56xf64,167392,,24491,, -matmul 8x52x60xf64,179340,,26235,, +matmul 8x52x56xf64,167392,,24395,, +matmul 8x52x60xf64,179340,,26149,, matmul 8x52x64xf64,191354,,27979,, matmul 8x52x8xf64,23795,,3563,, -matmul 8x56x12xf64,38255,,5691,, +matmul 8x56x12xf64,38255,,5669,, matmul 8x56x16xf64,51146,,7563,, -matmul 8x56x20xf64,64287,,9435,, -matmul 8x56x24xf64,77119,,11307,, -matmul 8x56x28xf64,89951,,13179,, +matmul 8x56x20xf64,64287,,9413,, +matmul 8x56x24xf64,77119,,11269,, +matmul 8x56x28xf64,89951,,13131,, matmul 8x56x32xf64,102783,,15051,, -matmul 8x56x36xf64,115615,,16923,, -matmul 8x56x40xf64,128487,,18795,, +matmul 8x56x36xf64,115615,,16869,, +matmul 8x56x40xf64,128487,,18763,, matmul 8x56x44xf64,141372,,20667,, -matmul 8x56x48xf64,154212,,22539,, +matmul 8x56x48xf64,154212,,22469,, matmul 8x56x4xf64,12796,,1927,, matmul 8x56x52xf64,167092,,24411,, -matmul 8x56x56xf64,179942,,26278,, -matmul 8x56x60xf64,192780,,28155,, +matmul 8x56x56xf64,179942,,26180,, +matmul 8x56x60xf64,192780,,28069,, matmul 8x56x64xf64,205690,,30027,, matmul 8x56x8xf64,25587,,3819,, -matmul 8x60x12xf64,40943,,6075,, +matmul 8x60x12xf64,40943,,6053,, matmul 8x60x16xf64,54730,,8075,, -matmul 8x60x20xf64,68767,,10075,, -matmul 8x60x24xf64,82495,,12075,, -matmul 8x60x28xf64,96223,,14075,, +matmul 8x60x20xf64,68767,,10053,, +matmul 8x60x24xf64,82495,,12037,, +matmul 8x60x28xf64,96223,,14027,, matmul 8x60x32xf64,109951,,16075,, -matmul 8x60x36xf64,123679,,18075,, -matmul 8x60x40xf64,137447,,20075,, +matmul 8x60x36xf64,123679,,18021,, +matmul 8x60x40xf64,137447,,20043,, matmul 8x60x44xf64,151228,,22075,, -matmul 8x60x48xf64,164964,,24075,, +matmul 8x60x48xf64,164964,,24005,, matmul 8x60x4xf64,13692,,2055,, matmul 8x60x52xf64,178740,,26075,, -matmul 8x60x56xf64,192480,,28075,, -matmul 8x60x60xf64,206220,,30075,, +matmul 8x60x56xf64,192480,,27979,, +matmul 8x60x60xf64,206220,,29989,, matmul 8x60x64xf64,220026,,32075,, matmul 8x60x8xf64,27379,,4075,, -matmul 8x64x12xf64,43631,,6459,, +matmul 8x64x12xf64,43631,,6437,, matmul 8x64x16xf64,58314,,8581,, -matmul 8x64x20xf64,73247,,10715,, -matmul 8x64x24xf64,87877,,12837,, -matmul 8x64x28xf64,102495,,14971,, +matmul 8x64x20xf64,73247,,10699,, +matmul 8x64x24xf64,87877,,12811,, +matmul 8x64x28xf64,102495,,14923,, matmul 8x64x32xf64,117125,,17093,, -matmul 8x64x36xf64,131743,,19227,, -matmul 8x64x40xf64,146413,,21349,, +matmul 8x64x36xf64,131743,,19173,, +matmul 8x64x40xf64,146413,,21317,, matmul 8x64x44xf64,161084,,23483,, -matmul 8x64x48xf64,175710,,25605,, +matmul 8x64x48xf64,175710,,25547,, matmul 8x64x4xf64,14594,,2183,, matmul 8x64x52xf64,190388,,27739,, -matmul 8x64x56xf64,205040,,29861,, -matmul 8x64x60xf64,219660,,31995,, +matmul 8x64x56xf64,205040,,29764,, +matmul 8x64x60xf64,219660,,31909,, matmul 8x64x64xf64,234370,,34124,, matmul 8x64x8xf64,29163,,4325,, -matmul 8x8x12xf64,4458,,1084,, +matmul 8x8x12xf64,4458,,1059,, matmul 8x8x16xf64,5930,,1420,, -matmul 8x8x20xf64,7402,,1760,, -matmul 8x8x24xf64,8868,,2092,, -matmul 8x8x28xf64,10340,,2428,, +matmul 8x8x20xf64,7402,,1732,, +matmul 8x8x24xf64,8868,,2051,, +matmul 8x8x28xf64,10340,,2377,, matmul 8x8x32xf64,11812,,2764,, -matmul 8x8x36xf64,13284,,3099,, -matmul 8x8x40xf64,14756,,3430,, +matmul 8x8x36xf64,13284,,3044,, +matmul 8x8x40xf64,14756,,3397,, matmul 8x8x44xf64,16228,,3766,, -matmul 8x8x48xf64,17700,,4102,, +matmul 8x8x48xf64,17700,,4043,, matmul 8x8x4xf64,1492,,391,, matmul 8x8x52xf64,19172,,4450,, -matmul 8x8x56xf64,20650,,4780,, -matmul 8x8x60xf64,22115,,5109,, +matmul 8x8x56xf64,20650,,4676,, +matmul 8x8x60xf64,22115,,5035,, matmul 8x8x64xf64,23596,,5452,, matmul 8x8x8xf64,2976,,748,, matmul_transb 1x12x40xf32,,,,416, @@ -858,54 +861,54 @@ matmul_transb 1x20x40xf32,,,,577, matmul_transb 1x20x8xf32,,,,160, matmul_transb 1x4x40xf32,,,,295, matmul_transb 1x8x40xf32,,,,336, -pooling_nchw_max_d1_s2_3x3 12x12xf64,4761,4532,2211,, +pooling_nchw_max_d1_s2_3x3 12x12xf64,4761,4532,2223,, pooling_nchw_max_d1_s2_3x3 12x16xf64,6221,6026,2739,, -pooling_nchw_max_d1_s2_3x3 12x20xf64,7677,7515,3267,, +pooling_nchw_max_d1_s2_3x3 12x20xf64,7677,7515,3271,, pooling_nchw_max_d1_s2_3x3 12x4xf64,1790,1155,582,, pooling_nchw_max_d1_s2_3x3 12x8xf64,3305,2739,1683,, -pooling_nchw_max_d1_s2_3x3 16x12xf64,6221,6039,2939,, +pooling_nchw_max_d1_s2_3x3 16x12xf64,6221,6039,2944,, pooling_nchw_max_d1_s2_3x3 16x16xf64,8121,8024,3643,, -pooling_nchw_max_d1_s2_3x3 16x20xf64,10025,9999,4347,, +pooling_nchw_max_d1_s2_3x3 16x20xf64,10025,9999,4351,, pooling_nchw_max_d1_s2_3x3 16x4xf64,2334,1527,758,, pooling_nchw_max_d1_s2_3x3 16x8xf64,4313,3639,2235,, -pooling_nchw_max_d1_s2_3x3 20x12xf64,7677,7539,3667,, +pooling_nchw_max_d1_s2_3x3 20x12xf64,7677,7539,3672,, pooling_nchw_max_d1_s2_3x3 20x16xf64,10025,10017,4547,, -pooling_nchw_max_d1_s2_3x3 20x20xf64,12377,12491,5426,, +pooling_nchw_max_d1_s2_3x3 20x20xf64,12377,12491,5429,, pooling_nchw_max_d1_s2_3x3 20x4xf64,2878,1899,934,, pooling_nchw_max_d1_s2_3x3 20x8xf64,5321,4539,2787,, -pooling_nchw_max_d1_s2_3x3 4x12xf64,1851,1482,755,, +pooling_nchw_max_d1_s2_3x3 4x12xf64,1851,1482,767,, pooling_nchw_max_d1_s2_3x3 4x16xf64,2411,2000,931,, -pooling_nchw_max_d1_s2_3x3 4x20xf64,2971,2494,1107,, +pooling_nchw_max_d1_s2_3x3 4x20xf64,2971,2494,1106,, pooling_nchw_max_d1_s2_3x3 4x4xf64,711,396,224,, pooling_nchw_max_d1_s2_3x3 4x8xf64,1291,752,579,, -pooling_nchw_max_d1_s2_3x3 8x12xf64,3305,3015,1483,, +pooling_nchw_max_d1_s2_3x3 8x12xf64,3305,3015,1495,, pooling_nchw_max_d1_s2_3x3 8x16xf64,4313,4022,1835,, -pooling_nchw_max_d1_s2_3x3 8x20xf64,5321,4999,2187,, +pooling_nchw_max_d1_s2_3x3 8x20xf64,5321,4999,2186,, pooling_nchw_max_d1_s2_3x3 8x4xf64,1246,783,406,, pooling_nchw_max_d1_s2_3x3 8x8xf64,2297,1799,1131,, -pooling_nchw_sum_d1_s2_3x3 12x12xf64,6622,6706,2281,, +pooling_nchw_sum_d1_s2_3x3 12x12xf64,6622,6706,2258,, pooling_nchw_sum_d1_s2_3x3 12x16xf64,8645,8914,2833,, -pooling_nchw_sum_d1_s2_3x3 12x20xf64,10673,11122,3385,, +pooling_nchw_sum_d1_s2_3x3 12x20xf64,10673,11122,3360,, pooling_nchw_sum_d1_s2_3x3 12x4xf64,2532,2068,612,, pooling_nchw_sum_d1_s2_3x3 12x8xf64,4594,4169,1729,, -pooling_nchw_sum_d1_s2_3x3 16x12xf64,8645,8914,3033,, +pooling_nchw_sum_d1_s2_3x3 16x12xf64,8645,8914,3001,, pooling_nchw_sum_d1_s2_3x3 16x16xf64,11305,11871,3777,, -pooling_nchw_sum_d1_s2_3x3 16x20xf64,13957,14815,4513,, +pooling_nchw_sum_d1_s2_3x3 16x20xf64,13957,14815,4472,, pooling_nchw_sum_d1_s2_3x3 16x4xf64,3304,2732,796,, pooling_nchw_sum_d1_s2_3x3 16x8xf64,5998,5533,2297,, -pooling_nchw_sum_d1_s2_3x3 20x12xf64,10673,11122,3785,, +pooling_nchw_sum_d1_s2_3x3 20x12xf64,10673,11122,3745,, pooling_nchw_sum_d1_s2_3x3 20x16xf64,13957,14815,4713,, -pooling_nchw_sum_d1_s2_3x3 20x20xf64,17233,18495,5633,, +pooling_nchw_sum_d1_s2_3x3 20x20xf64,17233,18495,5584,, pooling_nchw_sum_d1_s2_3x3 20x4xf64,4076,3396,980,, pooling_nchw_sum_d1_s2_3x3 20x8xf64,7402,6897,2865,, -pooling_nchw_sum_d1_s2_3x3 4x12xf64,2558,2281,777,, +pooling_nchw_sum_d1_s2_3x3 4x12xf64,2558,2281,770,, pooling_nchw_sum_d1_s2_3x3 4x16xf64,3338,3013,961,, -pooling_nchw_sum_d1_s2_3x3 4x20xf64,4118,3745,1145,, +pooling_nchw_sum_d1_s2_3x3 4x20xf64,4118,3745,1137,, pooling_nchw_sum_d1_s2_3x3 4x4xf64,982,728,230,, pooling_nchw_sum_d1_s2_3x3 4x8xf64,1774,1349,593,, -pooling_nchw_sum_d1_s2_3x3 8x12xf64,4594,4498,1529,, +pooling_nchw_sum_d1_s2_3x3 8x12xf64,4594,4498,1514,, pooling_nchw_sum_d1_s2_3x3 8x16xf64,5998,5970,1897,, -pooling_nchw_sum_d1_s2_3x3 8x20xf64,7402,7442,2265,, +pooling_nchw_sum_d1_s2_3x3 8x20xf64,7402,7442,2249,, pooling_nchw_sum_d1_s2_3x3 8x4xf64,1760,1404,428,, pooling_nchw_sum_d1_s2_3x3 8x8xf64,3190,2805,1161,, relu 12x12xf64,890,602,178,, diff --git a/results/pivoted_fpu.all.csv b/results/pivoted_fpu.all.csv index f88f5dec..d674970d 100644 --- a/results/pivoted_fpu.all.csv +++ b/results/pivoted_fpu.all.csv @@ -1,27 +1,27 @@ kernels,baseline,linalg,linalg_xdsl,snitch_stream,snrt -conv2d_d1_s1_3x3 12x12xf64,0.18,0.19,0.64,, +conv2d_d1_s1_3x3 12x12xf64,0.18,0.19,0.65,, conv2d_d1_s1_3x3 12x16xf64,0.18,0.19,0.70,, conv2d_d1_s1_3x3 12x20xf64,0.18,0.19,0.74,, conv2d_d1_s1_3x3 12x4xf64,0.18,0.21,0.84,, conv2d_d1_s1_3x3 12x8xf64,0.18,0.19,0.55,, -conv2d_d1_s1_3x3 16x12xf64,0.18,0.19,0.64,, +conv2d_d1_s1_3x3 16x12xf64,0.18,0.19,0.65,, conv2d_d1_s1_3x3 16x16xf64,0.18,0.19,0.70,, conv2d_d1_s1_3x3 16x20xf64,0.18,0.19,0.74,, conv2d_d1_s1_3x3 16x4xf64,0.18,0.21,0.87,, conv2d_d1_s1_3x3 16x8xf64,0.18,0.19,0.55,, -conv2d_d1_s1_3x3 20x12xf64,0.18,0.19,0.64,, +conv2d_d1_s1_3x3 20x12xf64,0.18,0.19,0.65,, conv2d_d1_s1_3x3 20x16xf64,0.18,0.19,0.70,, -conv2d_d1_s1_3x3 20x20xf64,0.18,0.19,0.74,, +conv2d_d1_s1_3x3 20x20xf64,0.18,0.19,0.75,, conv2d_d1_s1_3x3 20x4xf64,0.18,0.21,0.89,, conv2d_d1_s1_3x3 20x8xf64,0.18,0.19,0.55,, -conv2d_d1_s1_3x3 4x12xf64,0.17,0.19,0.62,, +conv2d_d1_s1_3x3 4x12xf64,0.17,0.19,0.64,, conv2d_d1_s1_3x3 4x16xf64,0.18,0.19,0.68,, -conv2d_d1_s1_3x3 4x20xf64,0.18,0.19,0.72,, +conv2d_d1_s1_3x3 4x20xf64,0.18,0.19,0.73,, conv2d_d1_s1_3x3 4x4xf64,0.18,0.19,0.72,, conv2d_d1_s1_3x3 4x8xf64,0.17,0.20,0.53,, conv2d_d1_s1_3x3 8x12xf64,0.18,0.19,0.64,, conv2d_d1_s1_3x3 8x16xf64,0.18,0.19,0.69,, -conv2d_d1_s1_3x3 8x20xf64,0.18,0.19,0.73,, +conv2d_d1_s1_3x3 8x20xf64,0.18,0.19,0.74,, conv2d_d1_s1_3x3 8x4xf64,0.18,0.20,0.80,, conv2d_d1_s1_3x3 8x8xf64,0.18,0.19,0.54,, ddot 128xf64,0.14,0.14,,0.77,0.24 @@ -34,27 +34,30 @@ exp_macro 384xf64,,,,,0.59 exp_macro 448xf64,,,,,0.60 exp_macro 512xf64,,,,,0.61 exp_macro 64xf64,,,,,0.34 -exp_micro 106xf16,0.14,,,, -exp_micro 106xf32,0.13,,,, -exp_micro 106xf64,0.12,,,, -exp_micro 122xf16,0.14,,,, -exp_micro 122xf32,0.13,,,, -exp_micro 122xf64,0.12,,,, -exp_micro 26xf16,0.14,,,, -exp_micro 26xf32,0.13,,,, -exp_micro 26xf64,0.12,,,, -exp_micro 42xf16,0.14,,,, -exp_micro 42xf32,0.13,,,, -exp_micro 42xf64,0.12,,,, -exp_micro 58xf16,0.14,,,, -exp_micro 58xf32,0.13,,,, -exp_micro 58xf64,0.12,,,, -exp_micro 74xf16,0.14,,,, -exp_micro 74xf32,0.13,,,, -exp_micro 74xf64,0.12,,,, -exp_micro 90xf16,0.14,,,, -exp_micro 90xf32,0.13,,,, -exp_micro 90xf64,0.12,,,, +exp_micro 112xf16,0.14,,,, +exp_micro 112xf32,0.13,,,, +exp_micro 112xf64,0.12,,,, +exp_micro 128xf16,0.14,,,, +exp_micro 128xf32,0.13,,,, +exp_micro 128xf64,0.12,,,, +exp_micro 16xf16,0.14,,,, +exp_micro 16xf32,0.13,,,, +exp_micro 16xf64,0.12,,,, +exp_micro 32xf16,0.14,,,, +exp_micro 32xf32,0.13,,,, +exp_micro 32xf64,0.12,,,, +exp_micro 48xf16,0.14,,,, +exp_micro 48xf32,0.13,,,, +exp_micro 48xf64,0.12,,,, +exp_micro 64xf16,0.14,,,, +exp_micro 64xf32,0.13,,,, +exp_micro 64xf64,0.12,,,, +exp_micro 80xf16,0.14,,,, +exp_micro 80xf32,0.13,,,, +exp_micro 80xf64,0.12,,,, +exp_micro 96xf16,0.14,,,, +exp_micro 96xf32,0.13,,,, +exp_micro 96xf64,0.12,,,, fill 12x12xf64,0.00,0.00,0.83,, fill 12x16xf64,0.00,0.00,0.87,, fill 12x20xf64,0.00,0.00,0.89,, @@ -80,44 +83,44 @@ fill 8x16xf64,0.01,0.01,0.82,, fill 8x20xf64,0.01,0.01,0.85,, fill 8x4xf64,0.02,0.02,0.54,, fill 8x8xf64,0.01,0.01,0.69,, -matmul 1x12x12xf64,0.18,,0.75,, +matmul 1x12x12xf64,0.18,,0.76,, matmul 1x12x16xf64,0.18,,0.79,, matmul 1x12x20xf64,0.18,,0.82,, matmul 1x12x24xf64,0.18,,0.82,, -matmul 1x12x28xf64,0.18,,0.81,, +matmul 1x12x28xf64,0.18,,0.83,, matmul 1x12x32xf64,0.18,,0.86,, -matmul 1x12x36xf64,0.18,,0.87,, +matmul 1x12x36xf64,0.18,,0.86,, matmul 1x12x40xf64,0.18,,0.88,, matmul 1x12x44xf64,0.18,,0.89,, matmul 1x12x48xf64,0.18,,0.89,, matmul 1x12x4xf64,0.17,,0.59,, matmul 1x12x52xf64,0.18,,0.90,, -matmul 1x12x56xf64,0.18,,0.90,, +matmul 1x12x56xf64,0.18,,0.91,, matmul 1x12x60xf64,0.18,,0.91,, matmul 1x12x64xf64,0.18,,0.91,, matmul 1x12x8xf64,0.18,,0.67,, -matmul 1x16x12xf64,0.18,,0.79,, +matmul 1x16x12xf64,0.18,,0.80,, matmul 1x16x16xf64,0.18,,0.82,, -matmul 1x16x20xf64,0.18,,0.84,, +matmul 1x16x20xf64,0.18,,0.83,, matmul 1x16x24xf64,0.18,,0.85,, -matmul 1x16x28xf64,0.18,,0.85,, +matmul 1x16x28xf64,0.18,,0.86,, matmul 1x16x32xf64,0.18,,0.89,, -matmul 1x16x36xf64,0.18,,0.90,, +matmul 1x16x36xf64,0.18,,0.89,, matmul 1x16x40xf64,0.18,,0.90,, matmul 1x16x44xf64,0.18,,0.91,, matmul 1x16x48xf64,0.18,,0.91,, matmul 1x16x4xf64,0.18,,0.65,, matmul 1x16x52xf64,0.18,,0.92,, -matmul 1x16x56xf64,0.18,,0.92,, -matmul 1x16x60xf64,0.18,,0.92,, +matmul 1x16x56xf64,0.18,,0.93,, +matmul 1x16x60xf64,0.18,,0.93,, matmul 1x16x64xf64,0.18,,0.93,, matmul 1x16x8xf64,0.18,,0.72,, matmul 1x200x5xf64,,,0.96,, -matmul 1x20x12xf64,0.18,,0.77,, +matmul 1x20x12xf64,0.18,,0.79,, matmul 1x20x16xf64,0.18,,0.81,, -matmul 1x20x20xf64,0.18,,0.86,, -matmul 1x20x24xf64,0.18,,0.88,, -matmul 1x20x28xf64,0.18,,0.89,, +matmul 1x20x20xf64,0.18,,0.85,, +matmul 1x20x24xf64,0.18,,0.89,, +matmul 1x20x28xf64,0.18,,0.88,, matmul 1x20x32xf64,0.18,,0.91,, matmul 1x20x36xf64,0.18,,0.91,, matmul 1x20x40xf64,0.18,,0.92,, @@ -125,31 +128,31 @@ matmul 1x20x44xf64,0.18,,0.92,, matmul 1x20x48xf64,0.18,,0.93,, matmul 1x20x4xf64,0.18,,0.69,, matmul 1x20x52xf64,0.18,,0.93,, -matmul 1x20x56xf64,0.18,,0.93,, +matmul 1x20x56xf64,0.18,,0.94,, matmul 1x20x60xf64,0.18,,0.94,, matmul 1x20x64xf64,0.18,,0.94,, matmul 1x20x8xf64,0.18,,0.76,, matmul 1x24x12xf64,0.18,,0.81,, matmul 1x24x16xf64,0.18,,0.84,, -matmul 1x24x20xf64,0.18,,0.88,, -matmul 1x24x24xf64,0.18,,0.88,, +matmul 1x24x20xf64,0.18,,0.87,, +matmul 1x24x24xf64,0.18,,0.89,, matmul 1x24x28xf64,0.18,,0.90,, matmul 1x24x32xf64,0.18,,0.92,, -matmul 1x24x36xf64,0.18,,0.93,, +matmul 1x24x36xf64,0.18,,0.92,, matmul 1x24x40xf64,0.18,,0.93,, matmul 1x24x44xf64,0.18,,0.93,, matmul 1x24x48xf64,0.18,,0.94,, matmul 1x24x4xf64,0.18,,0.72,, matmul 1x24x52xf64,0.18,,0.94,, -matmul 1x24x56xf64,0.18,,0.94,, +matmul 1x24x56xf64,0.18,,0.95,, matmul 1x24x60xf64,0.18,,0.95,, matmul 1x24x64xf64,0.18,,0.95,, matmul 1x24x8xf64,0.18,,0.79,, matmul 1x28x12xf64,0.18,,0.83,, matmul 1x28x16xf64,0.18,,0.86,, -matmul 1x28x20xf64,0.18,,0.88,, -matmul 1x28x24xf64,0.18,,0.89,, -matmul 1x28x28xf64,0.18,,0.89,, +matmul 1x28x20xf64,0.18,,0.89,, +matmul 1x28x24xf64,0.18,,0.90,, +matmul 1x28x28xf64,0.18,,0.91,, matmul 1x28x32xf64,0.18,,0.93,, matmul 1x28x36xf64,0.18,,0.93,, matmul 1x28x40xf64,0.18,,0.94,, @@ -157,18 +160,18 @@ matmul 1x28x44xf64,0.18,,0.94,, matmul 1x28x48xf64,0.18,,0.95,, matmul 1x28x4xf64,0.18,,0.75,, matmul 1x28x52xf64,0.18,,0.95,, -matmul 1x28x56xf64,0.18,,0.95,, +matmul 1x28x56xf64,0.18,,0.96,, matmul 1x28x60xf64,0.18,,0.95,, matmul 1x28x64xf64,0.18,,0.96,, matmul 1x28x8xf64,0.18,,0.81,, matmul 1x32x12xf64,0.18,,0.85,, matmul 1x32x16xf64,0.18,,0.89,, -matmul 1x32x20xf64,0.18,,0.89,, -matmul 1x32x24xf64,0.18,,0.90,, +matmul 1x32x20xf64,0.18,,0.90,, +matmul 1x32x24xf64,0.18,,0.91,, matmul 1x32x28xf64,0.18,,0.92,, matmul 1x32x32xf64,0.19,,0.93,, matmul 1x32x36xf64,0.19,,0.94,, -matmul 1x32x40xf64,0.19,,0.95,, +matmul 1x32x40xf64,0.19,,0.94,, matmul 1x32x44xf64,0.18,,0.95,, matmul 1x32x48xf64,0.18,,0.95,, matmul 1x32x4xf64,0.18,,0.77,, @@ -179,8 +182,8 @@ matmul 1x32x64xf64,0.19,,0.96,, matmul 1x32x8xf64,0.18,,0.82,, matmul 1x36x12xf64,0.14,,0.86,, matmul 1x36x16xf64,0.14,,0.88,, -matmul 1x36x20xf64,0.14,,0.90,, -matmul 1x36x24xf64,0.14,,0.91,, +matmul 1x36x20xf64,0.14,,0.92,, +matmul 1x36x24xf64,0.14,,0.92,, matmul 1x36x28xf64,0.14,,0.93,, matmul 1x36x32xf64,0.14,,0.94,, matmul 1x36x36xf64,0.14,,0.95,, @@ -189,15 +192,15 @@ matmul 1x36x44xf64,0.14,,0.95,, matmul 1x36x48xf64,0.14,,0.96,, matmul 1x36x4xf64,0.15,,0.79,, matmul 1x36x52xf64,0.14,,0.96,, -matmul 1x36x56xf64,0.14,,0.96,, +matmul 1x36x56xf64,0.14,,0.97,, matmul 1x36x60xf64,0.14,,0.96,, matmul 1x36x64xf64,0.14,,0.96,, matmul 1x36x8xf64,0.15,,0.83,, -matmul 1x40x12xf64,0.14,,0.86,, +matmul 1x40x12xf64,0.14,,0.88,, matmul 1x40x16xf64,0.14,,0.89,, -matmul 1x40x20xf64,0.14,,0.91,, -matmul 1x40x24xf64,0.14,,0.92,, -matmul 1x40x28xf64,0.14,,0.94,, +matmul 1x40x20xf64,0.14,,0.92,, +matmul 1x40x24xf64,0.14,,0.93,, +matmul 1x40x28xf64,0.14,,0.93,, matmul 1x40x32xf64,0.14,,0.95,, matmul 1x40x36xf64,0.14,,0.95,, matmul 1x40x40xf64,0.14,,0.96,, @@ -205,17 +208,17 @@ matmul 1x40x44xf64,0.14,,0.96,, matmul 1x40x48xf64,0.14,,0.96,, matmul 1x40x4xf64,0.14,,0.81,, matmul 1x40x52xf64,0.14,,0.96,, -matmul 1x40x56xf64,0.14,,0.96,, +matmul 1x40x56xf64,0.14,,0.97,, matmul 1x40x60xf64,0.14,,0.97,, matmul 1x40x64xf64,0.14,,0.97,, matmul 1x40x8xf64,0.14,,0.84,, -matmul 1x44x12xf64,0.14,,0.88,, +matmul 1x44x12xf64,0.14,,0.89,, matmul 1x44x16xf64,0.14,,0.90,, matmul 1x44x20xf64,0.14,,0.92,, matmul 1x44x24xf64,0.14,,0.93,, matmul 1x44x28xf64,0.14,,0.94,, matmul 1x44x32xf64,0.14,,0.95,, -matmul 1x44x36xf64,0.14,,0.96,, +matmul 1x44x36xf64,0.14,,0.95,, matmul 1x44x40xf64,0.14,,0.96,, matmul 1x44x44xf64,0.14,,0.96,, matmul 1x44x48xf64,0.14,,0.96,, @@ -225,11 +228,11 @@ matmul 1x44x56xf64,0.14,,0.97,, matmul 1x44x60xf64,0.14,,0.97,, matmul 1x44x64xf64,0.14,,0.97,, matmul 1x44x8xf64,0.14,,0.86,, -matmul 1x48x12xf64,0.14,,0.88,, +matmul 1x48x12xf64,0.14,,0.90,, matmul 1x48x16xf64,0.14,,0.91,, -matmul 1x48x20xf64,0.14,,0.94,, -matmul 1x48x24xf64,0.14,,0.93,, -matmul 1x48x28xf64,0.14,,0.95,, +matmul 1x48x20xf64,0.14,,0.93,, +matmul 1x48x24xf64,0.14,,0.94,, +matmul 1x48x28xf64,0.14,,0.94,, matmul 1x48x32xf64,0.14,,0.96,, matmul 1x48x36xf64,0.14,,0.96,, matmul 1x48x40xf64,0.14,,0.96,, @@ -241,42 +244,42 @@ matmul 1x48x56xf64,0.14,,0.97,, matmul 1x48x60xf64,0.14,,0.97,, matmul 1x48x64xf64,0.14,,0.97,, matmul 1x48x8xf64,0.14,,0.87,, -matmul 1x4x12xf64,0.15,,0.56,, +matmul 1x4x12xf64,0.15,,0.58,, matmul 1x4x16xf64,0.15,,0.62,, -matmul 1x4x20xf64,0.16,,0.66,, +matmul 1x4x20xf64,0.16,,0.67,, matmul 1x4x24xf64,0.16,,0.68,, -matmul 1x4x28xf64,0.16,,0.71,, +matmul 1x4x28xf64,0.16,,0.68,, matmul 1x4x32xf64,0.16,,0.71,, -matmul 1x4x36xf64,0.16,,0.73,, -matmul 1x4x40xf64,0.16,,0.74,, +matmul 1x4x36xf64,0.16,,0.74,, +matmul 1x4x40xf64,0.16,,0.77,, matmul 1x4x44xf64,0.16,,0.76,, -matmul 1x4x48xf64,0.16,,0.77,, +matmul 1x4x48xf64,0.16,,0.79,, matmul 1x4x4xf64,0.14,,0.38,, matmul 1x4x52xf64,0.16,,0.78,, -matmul 1x4x56xf64,0.16,,0.79,, -matmul 1x4x60xf64,0.16,,0.80,, +matmul 1x4x56xf64,0.16,,0.80,, +matmul 1x4x60xf64,0.16,,0.81,, matmul 1x4x64xf64,0.16,,0.81,, matmul 1x4x8xf64,0.15,,0.47,, -matmul 1x52x12xf64,0.14,,0.89,, +matmul 1x52x12xf64,0.14,,0.91,, matmul 1x52x16xf64,0.14,,0.91,, matmul 1x52x20xf64,0.14,,0.93,, matmul 1x52x24xf64,0.14,,0.94,, matmul 1x52x28xf64,0.14,,0.95,, matmul 1x52x32xf64,0.14,,0.96,, matmul 1x52x36xf64,0.14,,0.96,, -matmul 1x52x40xf64,0.14,,0.97,, +matmul 1x52x40xf64,0.14,,0.96,, matmul 1x52x44xf64,0.14,,0.97,, matmul 1x52x48xf64,0.14,,0.97,, matmul 1x52x4xf64,0.14,,0.83,, matmul 1x52x52xf64,0.14,,0.97,, -matmul 1x52x56xf64,0.14,,0.97,, +matmul 1x52x56xf64,0.14,,0.98,, matmul 1x52x60xf64,0.14,,0.97,, matmul 1x52x64xf64,0.14,,0.97,, matmul 1x52x8xf64,0.14,,0.88,, -matmul 1x56x12xf64,0.14,,0.90,, +matmul 1x56x12xf64,0.14,,0.91,, matmul 1x56x16xf64,0.14,,0.92,, -matmul 1x56x20xf64,0.14,,0.93,, -matmul 1x56x24xf64,0.14,,0.94,, +matmul 1x56x20xf64,0.14,,0.94,, +matmul 1x56x24xf64,0.14,,0.95,, matmul 1x56x28xf64,0.14,,0.95,, matmul 1x56x32xf64,0.14,,0.96,, matmul 1x56x36xf64,0.14,,0.96,, @@ -285,15 +288,15 @@ matmul 1x56x44xf64,0.14,,0.97,, matmul 1x56x48xf64,0.14,,0.97,, matmul 1x56x4xf64,0.14,,0.84,, matmul 1x56x52xf64,0.14,,0.97,, -matmul 1x56x56xf64,0.14,,0.97,, +matmul 1x56x56xf64,0.14,,0.98,, matmul 1x56x60xf64,0.14,,0.98,, matmul 1x56x64xf64,0.14,,0.98,, matmul 1x56x8xf64,0.14,,0.88,, -matmul 1x60x12xf64,0.14,,0.90,, +matmul 1x60x12xf64,0.14,,0.92,, matmul 1x60x16xf64,0.14,,0.94,, matmul 1x60x20xf64,0.14,,0.94,, -matmul 1x60x24xf64,0.14,,0.94,, -matmul 1x60x28xf64,0.14,,0.96,, +matmul 1x60x24xf64,0.14,,0.95,, +matmul 1x60x28xf64,0.14,,0.95,, matmul 1x60x32xf64,0.14,,0.96,, matmul 1x60x36xf64,0.14,,0.97,, matmul 1x60x40xf64,0.14,,0.97,, @@ -305,7 +308,7 @@ matmul 1x60x56xf64,0.14,,0.98,, matmul 1x60x60xf64,0.14,,0.98,, matmul 1x60x64xf64,0.14,,0.98,, matmul 1x60x8xf64,0.14,,0.87,, -matmul 1x64x12xf64,0.14,,0.91,, +matmul 1x64x12xf64,0.14,,0.92,, matmul 1x64x16xf64,0.14,,0.94,, matmul 1x64x20xf64,0.14,,0.94,, matmul 1x64x24xf64,0.14,,0.95,, @@ -321,100 +324,100 @@ matmul 1x64x56xf64,0.14,,0.98,, matmul 1x64x60xf64,0.14,,0.98,, matmul 1x64x64xf64,0.14,,0.98,, matmul 1x64x8xf64,0.14,,0.90,, -matmul 1x8x12xf64,0.17,,0.68,, +matmul 1x8x12xf64,0.17,,0.69,, matmul 1x8x16xf64,0.17,,0.73,, -matmul 1x8x20xf64,0.17,,0.76,, +matmul 1x8x20xf64,0.17,,0.77,, matmul 1x8x24xf64,0.17,,0.78,, -matmul 1x8x28xf64,0.17,,0.77,, +matmul 1x8x28xf64,0.17,,0.80,, matmul 1x8x32xf64,0.17,,0.82,, -matmul 1x8x36xf64,0.17,,0.83,, -matmul 1x8x40xf64,0.17,,0.84,, +matmul 1x8x36xf64,0.17,,0.82,, +matmul 1x8x40xf64,0.17,,0.83,, matmul 1x8x44xf64,0.17,,0.85,, matmul 1x8x48xf64,0.17,,0.85,, matmul 1x8x4xf64,0.16,,0.51,, matmul 1x8x52xf64,0.17,,0.86,, -matmul 1x8x56xf64,0.17,,0.87,, +matmul 1x8x56xf64,0.17,,0.88,, matmul 1x8x60xf64,0.17,,0.87,, matmul 1x8x64xf64,0.17,,0.88,, matmul 1x8x8xf64,0.17,,0.59,, -matmul 4x12x12xf64,0.18,,0.87,, +matmul 4x12x12xf64,0.18,,0.89,, matmul 4x12x16xf64,0.18,,0.89,, -matmul 4x12x20xf64,0.18,,0.91,, -matmul 4x12x24xf64,0.18,,0.92,, -matmul 4x12x28xf64,0.18,,0.93,, +matmul 4x12x20xf64,0.18,,0.92,, +matmul 4x12x24xf64,0.18,,0.93,, +matmul 4x12x28xf64,0.18,,0.94,, matmul 4x12x32xf64,0.18,,0.93,, -matmul 4x12x36xf64,0.18,,0.94,, +matmul 4x12x36xf64,0.18,,0.95,, matmul 4x12x40xf64,0.18,,0.94,, matmul 4x12x44xf64,0.18,,0.94,, -matmul 4x12x48xf64,0.18,,0.94,, +matmul 4x12x48xf64,0.18,,0.95,, matmul 4x12x4xf64,0.18,,0.78,, matmul 4x12x52xf64,0.18,,0.94,, -matmul 4x12x56xf64,0.18,,0.95,, -matmul 4x12x60xf64,0.18,,0.95,, +matmul 4x12x56xf64,0.18,,0.96,, +matmul 4x12x60xf64,0.18,,0.96,, matmul 4x12x64xf64,0.18,,0.95,, matmul 4x12x8xf64,0.17,,0.83,, -matmul 4x16x12xf64,0.18,,0.90,, +matmul 4x16x12xf64,0.18,,0.91,, matmul 4x16x16xf64,0.18,,0.92,, -matmul 4x16x20xf64,0.18,,0.93,, -matmul 4x16x24xf64,0.18,,0.94,, -matmul 4x16x28xf64,0.18,,0.94,, +matmul 4x16x20xf64,0.18,,0.94,, +matmul 4x16x24xf64,0.18,,0.95,, +matmul 4x16x28xf64,0.18,,0.95,, matmul 4x16x32xf64,0.18,,0.95,, -matmul 4x16x36xf64,0.18,,0.95,, -matmul 4x16x40xf64,0.18,,0.95,, +matmul 4x16x36xf64,0.18,,0.96,, +matmul 4x16x40xf64,0.18,,0.96,, matmul 4x16x44xf64,0.18,,0.95,, -matmul 4x16x48xf64,0.18,,0.95,, +matmul 4x16x48xf64,0.18,,0.96,, matmul 4x16x4xf64,0.18,,0.82,, matmul 4x16x52xf64,0.18,,0.96,, -matmul 4x16x56xf64,0.18,,0.96,, -matmul 4x16x60xf64,0.18,,0.96,, +matmul 4x16x56xf64,0.18,,0.97,, +matmul 4x16x60xf64,0.18,,0.97,, matmul 4x16x64xf64,0.18,,0.96,, matmul 4x16x8xf64,0.18,,0.87,, -matmul 4x20x12xf64,0.18,,0.92,, +matmul 4x20x12xf64,0.18,,0.93,, matmul 4x20x16xf64,0.18,,0.93,, -matmul 4x20x20xf64,0.18,,0.94,, -matmul 4x20x24xf64,0.18,,0.95,, -matmul 4x20x28xf64,0.18,,0.95,, +matmul 4x20x20xf64,0.18,,0.95,, +matmul 4x20x24xf64,0.18,,0.96,, +matmul 4x20x28xf64,0.18,,0.96,, matmul 4x20x32xf64,0.18,,0.96,, matmul 4x20x36xf64,0.18,,0.96,, matmul 4x20x40xf64,0.18,,0.96,, matmul 4x20x44xf64,0.18,,0.96,, -matmul 4x20x48xf64,0.18,,0.96,, +matmul 4x20x48xf64,0.18,,0.97,, matmul 4x20x4xf64,0.17,,0.85,, matmul 4x20x52xf64,0.18,,0.96,, -matmul 4x20x56xf64,0.18,,0.96,, +matmul 4x20x56xf64,0.18,,0.97,, matmul 4x20x60xf64,0.18,,0.97,, matmul 4x20x64xf64,0.18,,0.97,, matmul 4x20x8xf64,0.18,,0.89,, -matmul 4x24x12xf64,0.18,,0.93,, +matmul 4x24x12xf64,0.18,,0.94,, matmul 4x24x16xf64,0.18,,0.94,, matmul 4x24x20xf64,0.18,,0.95,, matmul 4x24x24xf64,0.18,,0.96,, -matmul 4x24x28xf64,0.18,,0.96,, +matmul 4x24x28xf64,0.18,,0.97,, matmul 4x24x32xf64,0.18,,0.96,, -matmul 4x24x36xf64,0.18,,0.96,, +matmul 4x24x36xf64,0.18,,0.97,, matmul 4x24x40xf64,0.17,,0.97,, matmul 4x24x44xf64,0.18,,0.97,, matmul 4x24x48xf64,0.18,,0.97,, matmul 4x24x4xf64,0.17,,0.87,, matmul 4x24x52xf64,0.17,,0.97,, -matmul 4x24x56xf64,0.17,,0.97,, -matmul 4x24x60xf64,0.17,,0.97,, +matmul 4x24x56xf64,0.17,,0.98,, +matmul 4x24x60xf64,0.17,,0.98,, matmul 4x24x64xf64,0.17,,0.97,, matmul 4x24x8xf64,0.18,,0.90,, -matmul 4x28x12xf64,0.18,,0.94,, +matmul 4x28x12xf64,0.18,,0.95,, matmul 4x28x16xf64,0.18,,0.95,, matmul 4x28x20xf64,0.17,,0.96,, -matmul 4x28x24xf64,0.18,,0.96,, -matmul 4x28x28xf64,0.18,,0.96,, +matmul 4x28x24xf64,0.18,,0.97,, +matmul 4x28x28xf64,0.18,,0.97,, matmul 4x28x32xf64,0.16,,0.97,, matmul 4x28x36xf64,0.17,,0.97,, matmul 4x28x40xf64,0.17,,0.97,, matmul 4x28x44xf64,0.16,,0.97,, -matmul 4x28x48xf64,0.16,,0.97,, +matmul 4x28x48xf64,0.16,,0.98,, matmul 4x28x4xf64,0.17,,0.88,, matmul 4x28x52xf64,0.16,,0.97,, -matmul 4x28x56xf64,0.16,,0.97,, -matmul 4x28x60xf64,0.15,,0.97,, +matmul 4x28x56xf64,0.16,,0.98,, +matmul 4x28x60xf64,0.15,,0.98,, matmul 4x28x64xf64,0.16,,0.98,, matmul 4x28x8xf64,0.18,,0.91,, matmul 4x32x12xf64,0.15,,0.95,, @@ -423,8 +426,8 @@ matmul 4x32x20xf64,0.15,,0.96,, matmul 4x32x24xf64,0.15,,0.97,, matmul 4x32x28xf64,0.15,,0.97,, matmul 4x32x32xf64,0.15,,0.97,, -matmul 4x32x36xf64,0.15,,0.97,, -matmul 4x32x40xf64,0.15,,0.97,, +matmul 4x32x36xf64,0.15,,0.98,, +matmul 4x32x40xf64,0.15,,0.98,, matmul 4x32x44xf64,0.15,,0.97,, matmul 4x32x48xf64,0.15,,0.98,, matmul 4x32x4xf64,0.16,,0.90,, @@ -433,11 +436,11 @@ matmul 4x32x56xf64,0.15,,0.98,, matmul 4x32x60xf64,0.15,,0.98,, matmul 4x32x64xf64,0.15,,0.98,, matmul 4x32x8xf64,0.15,,0.93,, -matmul 4x36x12xf64,0.14,,0.95,, +matmul 4x36x12xf64,0.14,,0.96,, matmul 4x36x16xf64,0.14,,0.96,, matmul 4x36x20xf64,0.14,,0.97,, matmul 4x36x24xf64,0.14,,0.97,, -matmul 4x36x28xf64,0.14,,0.97,, +matmul 4x36x28xf64,0.14,,0.98,, matmul 4x36x32xf64,0.14,,0.97,, matmul 4x36x36xf64,0.14,,0.98,, matmul 4x36x40xf64,0.14,,0.98,, @@ -452,8 +455,8 @@ matmul 4x36x8xf64,0.14,,0.94,, matmul 4x40x12xf64,0.14,,0.96,, matmul 4x40x16xf64,0.14,,0.96,, matmul 4x40x20xf64,0.14,,0.97,, -matmul 4x40x24xf64,0.14,,0.97,, -matmul 4x40x28xf64,0.14,,0.97,, +matmul 4x40x24xf64,0.14,,0.98,, +matmul 4x40x28xf64,0.14,,0.98,, matmul 4x40x32xf64,0.14,,0.98,, matmul 4x40x36xf64,0.14,,0.98,, matmul 4x40x40xf64,0.14,,0.98,, @@ -461,56 +464,56 @@ matmul 4x40x44xf64,0.14,,0.98,, matmul 4x40x48xf64,0.14,,0.98,, matmul 4x40x4xf64,0.14,,0.92,, matmul 4x40x52xf64,0.14,,0.98,, -matmul 4x40x56xf64,0.14,,0.98,, -matmul 4x40x60xf64,0.14,,0.98,, +matmul 4x40x56xf64,0.14,,0.99,, +matmul 4x40x60xf64,0.14,,0.99,, matmul 4x40x64xf64,0.14,,0.98,, matmul 4x40x8xf64,0.14,,0.94,, matmul 4x44x12xf64,0.14,,0.96,, matmul 4x44x16xf64,0.14,,0.97,, matmul 4x44x20xf64,0.14,,0.97,, -matmul 4x44x24xf64,0.14,,0.97,, +matmul 4x44x24xf64,0.14,,0.98,, matmul 4x44x28xf64,0.14,,0.98,, matmul 4x44x32xf64,0.14,,0.98,, matmul 4x44x36xf64,0.14,,0.98,, matmul 4x44x40xf64,0.14,,0.98,, matmul 4x44x44xf64,0.14,,0.98,, -matmul 4x44x48xf64,0.14,,0.98,, +matmul 4x44x48xf64,0.14,,0.99,, matmul 4x44x4xf64,0.14,,0.92,, matmul 4x44x52xf64,0.14,,0.98,, -matmul 4x44x56xf64,0.14,,0.98,, -matmul 4x44x60xf64,0.14,,0.98,, +matmul 4x44x56xf64,0.14,,0.99,, +matmul 4x44x60xf64,0.14,,0.99,, matmul 4x44x64xf64,0.14,,0.98,, matmul 4x44x8xf64,0.14,,0.95,, -matmul 4x48x12xf64,0.14,,0.96,, +matmul 4x48x12xf64,0.14,,0.97,, matmul 4x48x16xf64,0.14,,0.97,, -matmul 4x48x20xf64,0.14,,0.97,, +matmul 4x48x20xf64,0.14,,0.98,, matmul 4x48x24xf64,0.14,,0.98,, matmul 4x48x28xf64,0.14,,0.98,, matmul 4x48x32xf64,0.14,,0.98,, matmul 4x48x36xf64,0.14,,0.98,, matmul 4x48x40xf64,0.14,,0.98,, matmul 4x48x44xf64,0.14,,0.98,, -matmul 4x48x48xf64,0.14,,0.98,, +matmul 4x48x48xf64,0.14,,0.99,, matmul 4x48x4xf64,0.14,,0.93,, matmul 4x48x52xf64,0.14,,0.98,, -matmul 4x48x56xf64,0.14,,0.98,, -matmul 4x48x60xf64,0.14,,0.98,, +matmul 4x48x56xf64,0.14,,0.99,, +matmul 4x48x60xf64,0.14,,0.99,, matmul 4x48x64xf64,0.14,,0.98,, matmul 4x48x8xf64,0.14,,0.95,, -matmul 4x4x12xf64,0.16,,0.75,, +matmul 4x4x12xf64,0.16,,0.78,, matmul 4x4x16xf64,0.16,,0.78,, -matmul 4x4x20xf64,0.16,,0.81,, -matmul 4x4x24xf64,0.16,,0.83,, -matmul 4x4x28xf64,0.16,,0.84,, +matmul 4x4x20xf64,0.16,,0.83,, +matmul 4x4x24xf64,0.16,,0.86,, +matmul 4x4x28xf64,0.16,,0.87,, matmul 4x4x32xf64,0.16,,0.85,, -matmul 4x4x36xf64,0.16,,0.86,, -matmul 4x4x40xf64,0.16,,0.86,, +matmul 4x4x36xf64,0.16,,0.88,, +matmul 4x4x40xf64,0.16,,0.88,, matmul 4x4x44xf64,0.16,,0.87,, -matmul 4x4x48xf64,0.16,,0.87,, +matmul 4x4x48xf64,0.16,,0.90,, matmul 4x4x4xf64,0.16,,0.60,, matmul 4x4x52xf64,0.16,,0.88,, -matmul 4x4x56xf64,0.16,,0.88,, -matmul 4x4x60xf64,0.16,,0.88,, +matmul 4x4x56xf64,0.16,,0.91,, +matmul 4x4x60xf64,0.16,,0.91,, matmul 4x4x64xf64,0.16,,0.88,, matmul 4x4x8xf64,0.16,,0.68,, matmul 4x52x12xf64,0.14,,0.97,, @@ -519,10 +522,10 @@ matmul 4x52x20xf64,0.14,,0.98,, matmul 4x52x24xf64,0.14,,0.98,, matmul 4x52x28xf64,0.14,,0.98,, matmul 4x52x32xf64,0.14,,0.98,, -matmul 4x52x36xf64,0.14,,0.98,, -matmul 4x52x40xf64,0.14,,0.98,, +matmul 4x52x36xf64,0.14,,0.99,, +matmul 4x52x40xf64,0.14,,0.99,, matmul 4x52x44xf64,0.14,,0.98,, -matmul 4x52x48xf64,0.14,,0.98,, +matmul 4x52x48xf64,0.14,,0.99,, matmul 4x52x4xf64,0.14,,0.93,, matmul 4x52x52xf64,0.14,,0.98,, matmul 4x52x56xf64,0.14,,0.99,, @@ -535,8 +538,8 @@ matmul 4x56x20xf64,0.14,,0.98,, matmul 4x56x24xf64,0.14,,0.98,, matmul 4x56x28xf64,0.14,,0.98,, matmul 4x56x32xf64,0.14,,0.98,, -matmul 4x56x36xf64,0.14,,0.98,, -matmul 4x56x40xf64,0.14,,0.98,, +matmul 4x56x36xf64,0.14,,0.99,, +matmul 4x56x40xf64,0.14,,0.99,, matmul 4x56x44xf64,0.14,,0.98,, matmul 4x56x48xf64,0.14,,0.99,, matmul 4x56x4xf64,0.14,,0.94,, @@ -549,9 +552,9 @@ matmul 4x60x12xf64,0.14,,0.97,, matmul 4x60x16xf64,0.14,,0.98,, matmul 4x60x20xf64,0.14,,0.98,, matmul 4x60x24xf64,0.14,,0.98,, -matmul 4x60x28xf64,0.14,,0.98,, +matmul 4x60x28xf64,0.14,,0.99,, matmul 4x60x32xf64,0.14,,0.98,, -matmul 4x60x36xf64,0.14,,0.98,, +matmul 4x60x36xf64,0.14,,0.99,, matmul 4x60x40xf64,0.14,,0.99,, matmul 4x60x44xf64,0.14,,0.99,, matmul 4x60x48xf64,0.14,,0.99,, @@ -565,7 +568,7 @@ matmul 4x64x12xf64,0.14,,0.97,, matmul 4x64x16xf64,0.14,,0.98,, matmul 4x64x20xf64,0.14,,0.98,, matmul 4x64x24xf64,0.14,,0.98,, -matmul 4x64x28xf64,0.14,,0.98,, +matmul 4x64x28xf64,0.14,,0.99,, matmul 4x64x32xf64,0.14,,0.98,, matmul 4x64x36xf64,0.14,,0.99,, matmul 4x64x40xf64,0.14,,0.99,, @@ -577,91 +580,91 @@ matmul 4x64x56xf64,0.14,,0.99,, matmul 4x64x60xf64,0.14,,0.99,, matmul 4x64x64xf64,0.14,,0.99,, matmul 4x64x8xf64,0.14,,0.96,, -matmul 4x8x12xf64,0.17,,0.83,, +matmul 4x8x12xf64,0.17,,0.86,, matmul 4x8x16xf64,0.17,,0.86,, -matmul 4x8x20xf64,0.17,,0.87,, -matmul 4x8x24xf64,0.17,,0.89,, -matmul 4x8x28xf64,0.17,,0.90,, +matmul 4x8x20xf64,0.17,,0.89,, +matmul 4x8x24xf64,0.17,,0.91,, +matmul 4x8x28xf64,0.17,,0.92,, matmul 4x8x32xf64,0.17,,0.91,, -matmul 4x8x36xf64,0.17,,0.91,, +matmul 4x8x36xf64,0.17,,0.92,, matmul 4x8x40xf64,0.17,,0.92,, matmul 4x8x44xf64,0.17,,0.92,, -matmul 4x8x48xf64,0.17,,0.92,, +matmul 4x8x48xf64,0.17,,0.94,, matmul 4x8x4xf64,0.17,,0.72,, matmul 4x8x52xf64,0.17,,0.92,, -matmul 4x8x56xf64,0.17,,0.93,, -matmul 4x8x60xf64,0.17,,0.93,, +matmul 4x8x56xf64,0.17,,0.95,, +matmul 4x8x60xf64,0.17,,0.94,, matmul 4x8x64xf64,0.17,,0.93,, matmul 4x8x8xf64,0.17,,0.78,, -matmul 8x12x12xf64,0.18,,0.92,, +matmul 8x12x12xf64,0.18,,0.93,, matmul 8x12x16xf64,0.18,,0.93,, -matmul 8x12x20xf64,0.18,,0.94,, -matmul 8x12x24xf64,0.18,,0.94,, -matmul 8x12x28xf64,0.18,,0.95,, +matmul 8x12x20xf64,0.18,,0.95,, +matmul 8x12x24xf64,0.18,,0.95,, +matmul 8x12x28xf64,0.18,,0.96,, matmul 8x12x32xf64,0.18,,0.95,, -matmul 8x12x36xf64,0.18,,0.95,, -matmul 8x12x40xf64,0.18,,0.95,, +matmul 8x12x36xf64,0.18,,0.96,, +matmul 8x12x40xf64,0.18,,0.96,, matmul 8x12x44xf64,0.18,,0.95,, -matmul 8x12x48xf64,0.18,,0.95,, +matmul 8x12x48xf64,0.18,,0.96,, matmul 8x12x4xf64,0.18,,0.87,, matmul 8x12x52xf64,0.18,,0.95,, -matmul 8x12x56xf64,0.18,,0.96,, -matmul 8x12x60xf64,0.18,,0.96,, +matmul 8x12x56xf64,0.18,,0.97,, +matmul 8x12x60xf64,0.18,,0.97,, matmul 8x12x64xf64,0.18,,0.96,, matmul 8x12x8xf64,0.18,,0.89,, -matmul 8x16x12xf64,0.18,,0.93,, +matmul 8x16x12xf64,0.18,,0.95,, matmul 8x16x16xf64,0.18,,0.94,, -matmul 8x16x20xf64,0.18,,0.95,, -matmul 8x16x24xf64,0.18,,0.95,, -matmul 8x16x28xf64,0.18,,0.96,, +matmul 8x16x20xf64,0.18,,0.96,, +matmul 8x16x24xf64,0.18,,0.96,, +matmul 8x16x28xf64,0.18,,0.97,, matmul 8x16x32xf64,0.18,,0.96,, -matmul 8x16x36xf64,0.18,,0.96,, -matmul 8x16x40xf64,0.18,,0.96,, +matmul 8x16x36xf64,0.18,,0.97,, +matmul 8x16x40xf64,0.18,,0.97,, matmul 8x16x44xf64,0.18,,0.96,, -matmul 8x16x48xf64,0.18,,0.96,, +matmul 8x16x48xf64,0.18,,0.97,, matmul 8x16x4xf64,0.18,,0.89,, matmul 8x16x52xf64,0.18,,0.96,, -matmul 8x16x56xf64,0.18,,0.97,, +matmul 8x16x56xf64,0.18,,0.98,, matmul 8x16x60xf64,0.18,,0.97,, matmul 8x16x64xf64,0.18,,0.97,, matmul 8x16x8xf64,0.18,,0.92,, -matmul 8x20x12xf64,0.18,,0.95,, +matmul 8x20x12xf64,0.18,,0.96,, matmul 8x20x16xf64,0.18,,0.96,, matmul 8x20x20xf64,0.18,,0.96,, -matmul 8x20x24xf64,0.18,,0.96,, -matmul 8x20x28xf64,0.18,,0.96,, +matmul 8x20x24xf64,0.18,,0.97,, +matmul 8x20x28xf64,0.18,,0.97,, matmul 8x20x32xf64,0.18,,0.97,, matmul 8x20x36xf64,0.18,,0.97,, matmul 8x20x40xf64,0.18,,0.97,, matmul 8x20x44xf64,0.18,,0.97,, -matmul 8x20x48xf64,0.18,,0.97,, +matmul 8x20x48xf64,0.18,,0.98,, matmul 8x20x4xf64,0.18,,0.91,, matmul 8x20x52xf64,0.18,,0.97,, -matmul 8x20x56xf64,0.18,,0.97,, -matmul 8x20x60xf64,0.18,,0.97,, +matmul 8x20x56xf64,0.18,,0.98,, +matmul 8x20x60xf64,0.18,,0.98,, matmul 8x20x64xf64,0.18,,0.97,, matmul 8x20x8xf64,0.18,,0.93,, matmul 8x24x12xf64,0.18,,0.96,, matmul 8x24x16xf64,0.18,,0.96,, matmul 8x24x20xf64,0.18,,0.97,, matmul 8x24x24xf64,0.18,,0.97,, -matmul 8x24x28xf64,0.18,,0.97,, +matmul 8x24x28xf64,0.18,,0.98,, matmul 8x24x32xf64,0.18,,0.97,, -matmul 8x24x36xf64,0.18,,0.97,, -matmul 8x24x40xf64,0.17,,0.97,, +matmul 8x24x36xf64,0.18,,0.98,, +matmul 8x24x40xf64,0.17,,0.98,, matmul 8x24x44xf64,0.18,,0.97,, -matmul 8x24x48xf64,0.18,,0.97,, +matmul 8x24x48xf64,0.18,,0.98,, matmul 8x24x4xf64,0.17,,0.92,, matmul 8x24x52xf64,0.17,,0.98,, matmul 8x24x56xf64,0.17,,0.98,, matmul 8x24x60xf64,0.17,,0.98,, matmul 8x24x64xf64,0.17,,0.98,, matmul 8x24x8xf64,0.18,,0.94,, -matmul 8x28x12xf64,0.18,,0.96,, +matmul 8x28x12xf64,0.18,,0.97,, matmul 8x28x16xf64,0.18,,0.97,, matmul 8x28x20xf64,0.17,,0.97,, -matmul 8x28x24xf64,0.18,,0.97,, -matmul 8x28x28xf64,0.18,,0.97,, +matmul 8x28x24xf64,0.18,,0.98,, +matmul 8x28x28xf64,0.18,,0.98,, matmul 8x28x32xf64,0.17,,0.98,, matmul 8x28x36xf64,0.17,,0.98,, matmul 8x28x40xf64,0.17,,0.98,, @@ -669,24 +672,24 @@ matmul 8x28x44xf64,0.16,,0.98,, matmul 8x28x48xf64,0.16,,0.98,, matmul 8x28x4xf64,0.17,,0.93,, matmul 8x28x52xf64,0.16,,0.98,, -matmul 8x28x56xf64,0.16,,0.98,, +matmul 8x28x56xf64,0.16,,0.99,, matmul 8x28x60xf64,0.15,,0.98,, matmul 8x28x64xf64,0.16,,0.98,, matmul 8x28x8xf64,0.18,,0.95,, -matmul 8x32x12xf64,0.15,,0.96,, +matmul 8x32x12xf64,0.15,,0.97,, matmul 8x32x16xf64,0.15,,0.97,, -matmul 8x32x20xf64,0.15,,0.97,, +matmul 8x32x20xf64,0.15,,0.98,, matmul 8x32x24xf64,0.15,,0.98,, matmul 8x32x28xf64,0.15,,0.98,, matmul 8x32x32xf64,0.15,,0.98,, matmul 8x32x36xf64,0.15,,0.98,, matmul 8x32x40xf64,0.15,,0.98,, matmul 8x32x44xf64,0.15,,0.98,, -matmul 8x32x48xf64,0.15,,0.98,, +matmul 8x32x48xf64,0.15,,0.99,, matmul 8x32x4xf64,0.16,,0.94,, matmul 8x32x52xf64,0.15,,0.98,, -matmul 8x32x56xf64,0.15,,0.98,, -matmul 8x32x60xf64,0.15,,0.98,, +matmul 8x32x56xf64,0.15,,0.99,, +matmul 8x32x60xf64,0.15,,0.99,, matmul 8x32x64xf64,0.15,,0.98,, matmul 8x32x8xf64,0.15,,0.95,, matmul 8x36x12xf64,0.14,,0.97,, @@ -695,40 +698,40 @@ matmul 8x36x20xf64,0.14,,0.98,, matmul 8x36x24xf64,0.14,,0.98,, matmul 8x36x28xf64,0.14,,0.98,, matmul 8x36x32xf64,0.14,,0.98,, -matmul 8x36x36xf64,0.14,,0.98,, +matmul 8x36x36xf64,0.14,,0.99,, matmul 8x36x40xf64,0.14,,0.98,, matmul 8x36x44xf64,0.14,,0.98,, -matmul 8x36x48xf64,0.14,,0.98,, +matmul 8x36x48xf64,0.14,,0.99,, matmul 8x36x4xf64,0.14,,0.95,, matmul 8x36x52xf64,0.14,,0.98,, -matmul 8x36x56xf64,0.14,,0.98,, -matmul 8x36x60xf64,0.14,,0.98,, +matmul 8x36x56xf64,0.14,,0.99,, +matmul 8x36x60xf64,0.14,,0.99,, matmul 8x36x64xf64,0.14,,0.98,, matmul 8x36x8xf64,0.14,,0.96,, -matmul 8x40x12xf64,0.14,,0.97,, +matmul 8x40x12xf64,0.14,,0.98,, matmul 8x40x16xf64,0.14,,0.98,, matmul 8x40x20xf64,0.14,,0.98,, matmul 8x40x24xf64,0.14,,0.98,, -matmul 8x40x28xf64,0.14,,0.98,, +matmul 8x40x28xf64,0.14,,0.99,, matmul 8x40x32xf64,0.14,,0.98,, -matmul 8x40x36xf64,0.14,,0.98,, -matmul 8x40x40xf64,0.14,,0.98,, +matmul 8x40x36xf64,0.14,,0.99,, +matmul 8x40x40xf64,0.14,,0.99,, matmul 8x40x44xf64,0.14,,0.98,, -matmul 8x40x48xf64,0.14,,0.98,, +matmul 8x40x48xf64,0.14,,0.99,, matmul 8x40x4xf64,0.14,,0.95,, matmul 8x40x52xf64,0.14,,0.98,, -matmul 8x40x56xf64,0.14,,0.98,, -matmul 8x40x60xf64,0.14,,0.98,, +matmul 8x40x56xf64,0.14,,0.99,, +matmul 8x40x60xf64,0.14,,0.99,, matmul 8x40x64xf64,0.14,,0.98,, matmul 8x40x8xf64,0.14,,0.96,, -matmul 8x44x12xf64,0.14,,0.97,, +matmul 8x44x12xf64,0.14,,0.98,, matmul 8x44x16xf64,0.14,,0.98,, matmul 8x44x20xf64,0.14,,0.98,, -matmul 8x44x24xf64,0.14,,0.98,, -matmul 8x44x28xf64,0.14,,0.98,, +matmul 8x44x24xf64,0.14,,0.99,, +matmul 8x44x28xf64,0.14,,0.99,, matmul 8x44x32xf64,0.14,,0.98,, -matmul 8x44x36xf64,0.14,,0.98,, -matmul 8x44x40xf64,0.14,,0.98,, +matmul 8x44x36xf64,0.14,,0.99,, +matmul 8x44x40xf64,0.14,,0.99,, matmul 8x44x44xf64,0.14,,0.98,, matmul 8x44x48xf64,0.14,,0.99,, matmul 8x44x4xf64,0.14,,0.96,, @@ -740,8 +743,8 @@ matmul 8x44x8xf64,0.14,,0.97,, matmul 8x48x12xf64,0.14,,0.98,, matmul 8x48x16xf64,0.14,,0.98,, matmul 8x48x20xf64,0.14,,0.98,, -matmul 8x48x24xf64,0.14,,0.98,, -matmul 8x48x28xf64,0.14,,0.98,, +matmul 8x48x24xf64,0.14,,0.99,, +matmul 8x48x28xf64,0.14,,0.99,, matmul 8x48x32xf64,0.14,,0.98,, matmul 8x48x36xf64,0.14,,0.99,, matmul 8x48x40xf64,0.14,,0.99,, @@ -753,27 +756,27 @@ matmul 8x48x56xf64,0.14,,0.99,, matmul 8x48x60xf64,0.14,,0.99,, matmul 8x48x64xf64,0.14,,0.99,, matmul 8x48x8xf64,0.14,,0.97,, -matmul 8x4x12xf64,0.16,,0.83,, +matmul 8x4x12xf64,0.16,,0.86,, matmul 8x4x16xf64,0.16,,0.85,, -matmul 8x4x20xf64,0.16,,0.86,, -matmul 8x4x24xf64,0.16,,0.87,, -matmul 8x4x28xf64,0.16,,0.88,, +matmul 8x4x20xf64,0.16,,0.88,, +matmul 8x4x24xf64,0.16,,0.90,, +matmul 8x4x28xf64,0.16,,0.91,, matmul 8x4x32xf64,0.16,,0.89,, -matmul 8x4x36xf64,0.16,,0.89,, -matmul 8x4x40xf64,0.16,,0.89,, +matmul 8x4x36xf64,0.16,,0.91,, +matmul 8x4x40xf64,0.16,,0.91,, matmul 8x4x44xf64,0.16,,0.89,, -matmul 8x4x48xf64,0.16,,0.90,, +matmul 8x4x48xf64,0.16,,0.92,, matmul 8x4x4xf64,0.16,,0.74,, matmul 8x4x52xf64,0.16,,0.90,, -matmul 8x4x56xf64,0.16,,0.90,, -matmul 8x4x60xf64,0.16,,0.90,, +matmul 8x4x56xf64,0.16,,0.93,, +matmul 8x4x60xf64,0.16,,0.93,, matmul 8x4x64xf64,0.16,,0.90,, matmul 8x4x8xf64,0.16,,0.78,, matmul 8x52x12xf64,0.14,,0.98,, matmul 8x52x16xf64,0.14,,0.98,, -matmul 8x52x20xf64,0.14,,0.98,, -matmul 8x52x24xf64,0.14,,0.98,, -matmul 8x52x28xf64,0.14,,0.98,, +matmul 8x52x20xf64,0.14,,0.99,, +matmul 8x52x24xf64,0.14,,0.99,, +matmul 8x52x28xf64,0.14,,0.99,, matmul 8x52x32xf64,0.14,,0.99,, matmul 8x52x36xf64,0.14,,0.99,, matmul 8x52x40xf64,0.14,,0.99,, @@ -787,7 +790,7 @@ matmul 8x52x64xf64,0.14,,0.99,, matmul 8x52x8xf64,0.14,,0.97,, matmul 8x56x12xf64,0.14,,0.98,, matmul 8x56x16xf64,0.14,,0.98,, -matmul 8x56x20xf64,0.14,,0.98,, +matmul 8x56x20xf64,0.14,,0.99,, matmul 8x56x24xf64,0.14,,0.99,, matmul 8x56x28xf64,0.14,,0.99,, matmul 8x56x32xf64,0.14,,0.99,, @@ -803,7 +806,7 @@ matmul 8x56x64xf64,0.14,,0.99,, matmul 8x56x8xf64,0.14,,0.97,, matmul 8x60x12xf64,0.14,,0.98,, matmul 8x60x16xf64,0.14,,0.98,, -matmul 8x60x20xf64,0.14,,0.98,, +matmul 8x60x20xf64,0.14,,0.99,, matmul 8x60x24xf64,0.14,,0.99,, matmul 8x60x28xf64,0.14,,0.99,, matmul 8x60x32xf64,0.14,,0.99,, @@ -833,20 +836,20 @@ matmul 8x64x56xf64,0.14,,0.99,, matmul 8x64x60xf64,0.14,,0.99,, matmul 8x64x64xf64,0.14,,0.99,, matmul 8x64x8xf64,0.14,,0.98,, -matmul 8x8x12xf64,0.17,,0.89,, +matmul 8x8x12xf64,0.17,,0.91,, matmul 8x8x16xf64,0.17,,0.90,, -matmul 8x8x20xf64,0.17,,0.91,, -matmul 8x8x24xf64,0.17,,0.92,, -matmul 8x8x28xf64,0.17,,0.92,, +matmul 8x8x20xf64,0.17,,0.92,, +matmul 8x8x24xf64,0.17,,0.94,, +matmul 8x8x28xf64,0.17,,0.94,, matmul 8x8x32xf64,0.17,,0.93,, -matmul 8x8x36xf64,0.17,,0.93,, -matmul 8x8x40xf64,0.17,,0.93,, +matmul 8x8x36xf64,0.17,,0.95,, +matmul 8x8x40xf64,0.17,,0.94,, matmul 8x8x44xf64,0.17,,0.94,, -matmul 8x8x48xf64,0.17,,0.94,, +matmul 8x8x48xf64,0.17,,0.95,, matmul 8x8x4xf64,0.17,,0.82,, matmul 8x8x52xf64,0.17,,0.94,, -matmul 8x8x56xf64,0.17,,0.94,, -matmul 8x8x60xf64,0.17,,0.94,, +matmul 8x8x56xf64,0.17,,0.96,, +matmul 8x8x60xf64,0.17,,0.95,, matmul 8x8x64xf64,0.17,,0.94,, matmul 8x8x8xf64,0.17,,0.86,, matmul_transb 1x12x40xf32,,,,0.77, @@ -858,7 +861,7 @@ matmul_transb 1x20x40xf32,,,,0.84, matmul_transb 1x20x8xf32,,,,0.61, matmul_transb 1x4x40xf32,,,,0.55, matmul_transb 1x8x40xf32,,,,0.72, -pooling_nchw_max_d1_s2_3x3 12x12xf64,0.32,0.29,0.72,, +pooling_nchw_max_d1_s2_3x3 12x12xf64,0.32,0.29,0.71,, pooling_nchw_max_d1_s2_3x3 12x16xf64,0.32,0.29,0.77,, pooling_nchw_max_d1_s2_3x3 12x20xf64,0.32,0.29,0.81,, pooling_nchw_max_d1_s2_3x3 12x4xf64,0.33,0.37,0.91,, @@ -873,7 +876,7 @@ pooling_nchw_max_d1_s2_3x3 20x16xf64,0.32,0.29,0.77,, pooling_nchw_max_d1_s2_3x3 20x20xf64,0.32,0.29,0.81,, pooling_nchw_max_d1_s2_3x3 20x4xf64,0.33,0.38,0.94,, pooling_nchw_max_d1_s2_3x3 20x8xf64,0.32,0.32,0.63,, -pooling_nchw_max_d1_s2_3x3 4x12xf64,0.32,0.29,0.70,, +pooling_nchw_max_d1_s2_3x3 4x12xf64,0.32,0.29,0.69,, pooling_nchw_max_d1_s2_3x3 4x16xf64,0.32,0.29,0.76,, pooling_nchw_max_d1_s2_3x3 4x20xf64,0.32,0.29,0.80,, pooling_nchw_max_d1_s2_3x3 4x4xf64,0.32,0.37,0.79,, @@ -885,25 +888,25 @@ pooling_nchw_max_d1_s2_3x3 8x4xf64,0.33,0.37,0.87,, pooling_nchw_max_d1_s2_3x3 8x8xf64,0.32,0.32,0.62,, pooling_nchw_sum_d1_s2_3x3 12x12xf64,0.20,0.19,0.70,, pooling_nchw_sum_d1_s2_3x3 12x16xf64,0.20,0.19,0.75,, -pooling_nchw_sum_d1_s2_3x3 12x20xf64,0.20,0.19,0.78,, +pooling_nchw_sum_d1_s2_3x3 12x20xf64,0.20,0.19,0.79,, pooling_nchw_sum_d1_s2_3x3 12x4xf64,0.21,0.21,0.87,, pooling_nchw_sum_d1_s2_3x3 12x8xf64,0.20,0.21,0.61,, pooling_nchw_sum_d1_s2_3x3 16x12xf64,0.20,0.19,0.70,, pooling_nchw_sum_d1_s2_3x3 16x16xf64,0.20,0.19,0.75,, -pooling_nchw_sum_d1_s2_3x3 16x20xf64,0.20,0.19,0.78,, +pooling_nchw_sum_d1_s2_3x3 16x20xf64,0.20,0.19,0.79,, pooling_nchw_sum_d1_s2_3x3 16x4xf64,0.21,0.21,0.89,, pooling_nchw_sum_d1_s2_3x3 16x8xf64,0.20,0.21,0.61,, -pooling_nchw_sum_d1_s2_3x3 20x12xf64,0.20,0.19,0.70,, +pooling_nchw_sum_d1_s2_3x3 20x12xf64,0.20,0.19,0.71,, pooling_nchw_sum_d1_s2_3x3 20x16xf64,0.20,0.19,0.75,, -pooling_nchw_sum_d1_s2_3x3 20x20xf64,0.20,0.19,0.78,, +pooling_nchw_sum_d1_s2_3x3 20x20xf64,0.20,0.19,0.79,, pooling_nchw_sum_d1_s2_3x3 20x4xf64,0.21,0.21,0.90,, pooling_nchw_sum_d1_s2_3x3 20x8xf64,0.20,0.21,0.62,, -pooling_nchw_sum_d1_s2_3x3 4x12xf64,0.20,0.19,0.68,, +pooling_nchw_sum_d1_s2_3x3 4x12xf64,0.20,0.19,0.69,, pooling_nchw_sum_d1_s2_3x3 4x16xf64,0.20,0.19,0.73,, -pooling_nchw_sum_d1_s2_3x3 4x20xf64,0.20,0.19,0.77,, +pooling_nchw_sum_d1_s2_3x3 4x20xf64,0.20,0.19,0.78,, pooling_nchw_sum_d1_s2_3x3 4x4xf64,0.20,0.20,0.77,, pooling_nchw_sum_d1_s2_3x3 4x8xf64,0.20,0.21,0.60,, -pooling_nchw_sum_d1_s2_3x3 8x12xf64,0.20,0.19,0.69,, +pooling_nchw_sum_d1_s2_3x3 8x12xf64,0.20,0.19,0.70,, pooling_nchw_sum_d1_s2_3x3 8x16xf64,0.20,0.19,0.74,, pooling_nchw_sum_d1_s2_3x3 8x20xf64,0.20,0.19,0.78,, pooling_nchw_sum_d1_s2_3x3 8x4xf64,0.21,0.21,0.83,, diff --git a/results/pivoted_ipc.all.csv b/results/pivoted_ipc.all.csv index f2f6dc09..b1141c76 100644 --- a/results/pivoted_ipc.all.csv +++ b/results/pivoted_ipc.all.csv @@ -9,7 +9,7 @@ conv2d_d1_s1_3x3 16x16xf64,0.63,0.60,0.98,, conv2d_d1_s1_3x3 16x20xf64,0.63,0.59,0.98,, conv2d_d1_s1_3x3 16x4xf64,0.57,0.48,0.99,, conv2d_d1_s1_3x3 16x8xf64,0.64,0.61,0.95,, -conv2d_d1_s1_3x3 20x12xf64,0.64,0.60,0.97,, +conv2d_d1_s1_3x3 20x12xf64,0.64,0.60,0.96,, conv2d_d1_s1_3x3 20x16xf64,0.63,0.60,0.98,, conv2d_d1_s1_3x3 20x20xf64,0.63,0.59,0.98,, conv2d_d1_s1_3x3 20x4xf64,0.57,0.48,1.00,, @@ -34,27 +34,30 @@ exp_macro 384xf64,,,,,1.34 exp_macro 448xf64,,,,,1.37 exp_macro 512xf64,,,,,1.38 exp_macro 64xf64,,,,,0.89 -exp_micro 106xf16,0.50,,,, -exp_micro 106xf32,0.51,,,, -exp_micro 106xf64,0.51,,,, -exp_micro 122xf16,0.50,,,, -exp_micro 122xf32,0.51,,,, -exp_micro 122xf64,0.51,,,, -exp_micro 26xf16,0.46,,,, -exp_micro 26xf32,0.47,,,, -exp_micro 26xf64,0.48,,,, -exp_micro 42xf16,0.50,,,, -exp_micro 42xf32,0.47,,,, -exp_micro 42xf64,0.48,,,, -exp_micro 58xf16,0.50,,,, -exp_micro 58xf32,0.51,,,, -exp_micro 58xf64,0.51,,,, -exp_micro 74xf16,0.50,,,, -exp_micro 74xf32,0.51,,,, -exp_micro 74xf64,0.51,,,, -exp_micro 90xf16,0.50,,,, -exp_micro 90xf32,0.51,,,, -exp_micro 90xf64,0.51,,,, +exp_micro 112xf16,0.50,,,, +exp_micro 112xf32,0.51,,,, +exp_micro 112xf64,0.51,,,, +exp_micro 128xf16,0.50,,,, +exp_micro 128xf32,0.51,,,, +exp_micro 128xf64,0.51,,,, +exp_micro 16xf16,0.46,,,, +exp_micro 16xf32,0.47,,,, +exp_micro 16xf64,0.48,,,, +exp_micro 32xf16,0.46,,,, +exp_micro 32xf32,0.47,,,, +exp_micro 32xf64,0.48,,,, +exp_micro 48xf16,0.50,,,, +exp_micro 48xf32,0.47,,,, +exp_micro 48xf64,0.48,,,, +exp_micro 64xf16,0.50,,,, +exp_micro 64xf32,0.51,,,, +exp_micro 64xf64,0.52,,,, +exp_micro 80xf16,0.50,,,, +exp_micro 80xf32,0.51,,,, +exp_micro 80xf64,0.51,,,, +exp_micro 96xf16,0.50,,,, +exp_micro 96xf32,0.51,,,, +exp_micro 96xf64,0.51,,,, fill 12x12xf64,0.94,0.94,0.93,, fill 12x16xf64,0.98,0.98,0.94,, fill 12x20xf64,0.99,0.99,0.95,, @@ -80,190 +83,190 @@ fill 8x16xf64,0.96,0.96,0.92,, fill 8x20xf64,0.97,0.97,0.93,, fill 8x4xf64,0.91,0.91,0.79,, fill 8x8xf64,0.95,0.95,0.86,, -matmul 1x12x12xf64,0.61,,0.98,, +matmul 1x12x12xf64,0.61,,0.99,, matmul 1x12x16xf64,0.61,,0.99,, matmul 1x12x20xf64,0.61,,0.99,, -matmul 1x12x24xf64,0.61,,0.97,, +matmul 1x12x24xf64,0.61,,0.96,, matmul 1x12x28xf64,0.61,,0.95,, matmul 1x12x32xf64,0.61,,0.99,, -matmul 1x12x36xf64,0.61,,0.99,, -matmul 1x12x40xf64,0.61,,1.00,, +matmul 1x12x36xf64,0.61,,0.97,, +matmul 1x12x40xf64,0.61,,0.98,, matmul 1x12x44xf64,0.62,,1.00,, -matmul 1x12x48xf64,0.62,,1.00,, +matmul 1x12x48xf64,0.62,,0.98,, matmul 1x12x4xf64,0.54,,0.92,, matmul 1x12x52xf64,0.62,,1.00,, -matmul 1x12x56xf64,0.62,,1.00,, -matmul 1x12x60xf64,0.62,,1.00,, +matmul 1x12x56xf64,0.62,,0.99,, +matmul 1x12x60xf64,0.62,,0.99,, matmul 1x12x64xf64,0.62,,1.00,, matmul 1x12x8xf64,0.61,,0.97,, matmul 1x16x12xf64,0.60,,0.99,, matmul 1x16x16xf64,0.60,,0.98,, -matmul 1x16x20xf64,0.60,,0.99,, -matmul 1x16x24xf64,0.60,,0.98,, +matmul 1x16x20xf64,0.60,,0.96,, +matmul 1x16x24xf64,0.60,,0.97,, matmul 1x16x28xf64,0.60,,0.96,, matmul 1x16x32xf64,0.61,,0.99,, -matmul 1x16x36xf64,0.61,,1.00,, -matmul 1x16x40xf64,0.62,,1.00,, +matmul 1x16x36xf64,0.61,,0.98,, +matmul 1x16x40xf64,0.62,,0.99,, matmul 1x16x44xf64,0.62,,1.00,, -matmul 1x16x48xf64,0.62,,1.00,, +matmul 1x16x48xf64,0.62,,0.99,, matmul 1x16x4xf64,0.55,,0.93,, matmul 1x16x52xf64,0.64,,1.00,, matmul 1x16x56xf64,0.64,,1.00,, -matmul 1x16x60xf64,0.64,,1.00,, +matmul 1x16x60xf64,0.64,,0.99,, matmul 1x16x64xf64,0.65,,1.00,, matmul 1x16x8xf64,0.60,,0.98,, matmul 1x200x5xf64,,,0.99,, -matmul 1x20x12xf64,0.60,,0.93,, +matmul 1x20x12xf64,0.60,,0.94,, matmul 1x20x16xf64,0.59,,0.95,, -matmul 1x20x20xf64,0.60,,0.98,, -matmul 1x20x24xf64,0.59,,0.99,, -matmul 1x20x28xf64,0.60,,0.99,, +matmul 1x20x20xf64,0.60,,0.97,, +matmul 1x20x24xf64,0.59,,0.98,, +matmul 1x20x28xf64,0.60,,0.97,, matmul 1x20x32xf64,0.61,,0.99,, -matmul 1x20x36xf64,0.61,,1.00,, -matmul 1x20x40xf64,0.60,,1.00,, +matmul 1x20x36xf64,0.61,,0.98,, +matmul 1x20x40xf64,0.60,,0.99,, matmul 1x20x44xf64,0.62,,1.00,, -matmul 1x20x48xf64,0.62,,1.00,, +matmul 1x20x48xf64,0.62,,0.99,, matmul 1x20x4xf64,0.59,,0.94,, matmul 1x20x52xf64,0.64,,1.00,, matmul 1x20x56xf64,0.64,,1.00,, -matmul 1x20x60xf64,0.64,,1.00,, +matmul 1x20x60xf64,0.64,,0.99,, matmul 1x20x64xf64,0.66,,1.00,, matmul 1x20x8xf64,0.59,,0.98,, -matmul 1x24x12xf64,0.59,,0.96,, +matmul 1x24x12xf64,0.59,,0.94,, matmul 1x24x16xf64,0.59,,0.96,, -matmul 1x24x20xf64,0.59,,0.99,, -matmul 1x24x24xf64,0.61,,0.97,, -matmul 1x24x28xf64,0.60,,0.99,, +matmul 1x24x20xf64,0.59,,0.97,, +matmul 1x24x24xf64,0.61,,0.98,, +matmul 1x24x28xf64,0.60,,0.97,, matmul 1x24x32xf64,0.60,,1.00,, -matmul 1x24x36xf64,0.61,,1.00,, -matmul 1x24x40xf64,0.62,,1.00,, +matmul 1x24x36xf64,0.61,,0.99,, +matmul 1x24x40xf64,0.62,,0.99,, matmul 1x24x44xf64,0.63,,1.00,, -matmul 1x24x48xf64,0.63,,1.00,, +matmul 1x24x48xf64,0.63,,0.99,, matmul 1x24x4xf64,0.59,,0.94,, matmul 1x24x52xf64,0.65,,1.00,, matmul 1x24x56xf64,0.65,,1.00,, -matmul 1x24x60xf64,0.65,,1.00,, +matmul 1x24x60xf64,0.65,,0.99,, matmul 1x24x64xf64,0.66,,1.00,, matmul 1x24x8xf64,0.59,,0.98,, -matmul 1x28x12xf64,0.59,,0.96,, +matmul 1x28x12xf64,0.59,,0.95,, matmul 1x28x16xf64,0.59,,0.96,, matmul 1x28x20xf64,0.60,,0.97,, -matmul 1x28x24xf64,0.60,,0.97,, -matmul 1x28x28xf64,0.60,,0.97,, +matmul 1x28x24xf64,0.60,,0.98,, +matmul 1x28x28xf64,0.60,,0.98,, matmul 1x28x32xf64,0.62,,1.00,, -matmul 1x28x36xf64,0.62,,1.00,, -matmul 1x28x40xf64,0.62,,1.00,, +matmul 1x28x36xf64,0.62,,0.99,, +matmul 1x28x40xf64,0.62,,0.99,, matmul 1x28x44xf64,0.64,,1.00,, -matmul 1x28x48xf64,0.64,,1.00,, +matmul 1x28x48xf64,0.64,,0.99,, matmul 1x28x4xf64,0.59,,0.95,, matmul 1x28x52xf64,0.66,,1.00,, matmul 1x28x56xf64,0.66,,1.00,, -matmul 1x28x60xf64,0.66,,1.00,, +matmul 1x28x60xf64,0.66,,0.99,, matmul 1x28x64xf64,0.67,,1.00,, matmul 1x28x8xf64,0.59,,0.98,, -matmul 1x32x12xf64,0.58,,0.97,, +matmul 1x32x12xf64,0.58,,0.95,, matmul 1x32x16xf64,0.59,,0.99,, -matmul 1x32x20xf64,0.60,,0.97,, -matmul 1x32x24xf64,0.60,,0.97,, -matmul 1x32x28xf64,0.60,,0.99,, +matmul 1x32x20xf64,0.60,,0.98,, +matmul 1x32x24xf64,0.60,,0.98,, +matmul 1x32x28xf64,0.60,,0.98,, matmul 1x32x32xf64,0.61,,0.99,, -matmul 1x32x36xf64,0.62,,1.00,, -matmul 1x32x40xf64,0.63,,1.00,, +matmul 1x32x36xf64,0.62,,0.99,, +matmul 1x32x40xf64,0.63,,0.99,, matmul 1x32x44xf64,0.65,,1.00,, -matmul 1x32x48xf64,0.65,,1.00,, +matmul 1x32x48xf64,0.65,,0.99,, matmul 1x32x4xf64,0.59,,0.95,, matmul 1x32x52xf64,0.66,,1.00,, matmul 1x32x56xf64,0.66,,1.00,, -matmul 1x32x60xf64,0.66,,1.00,, +matmul 1x32x60xf64,0.66,,0.99,, matmul 1x32x64xf64,0.68,,1.00,, matmul 1x32x8xf64,0.59,,0.97,, -matmul 1x36x12xf64,0.95,,0.97,, +matmul 1x36x12xf64,0.95,,0.96,, matmul 1x36x16xf64,0.97,,0.97,, -matmul 1x36x20xf64,1.00,,0.98,, +matmul 1x36x20xf64,1.00,,0.99,, matmul 1x36x24xf64,1.00,,0.98,, -matmul 1x36x28xf64,1.00,,0.99,, +matmul 1x36x28xf64,1.00,,0.98,, matmul 1x36x32xf64,1.00,,1.00,, -matmul 1x36x36xf64,1.00,,1.00,, -matmul 1x36x40xf64,1.00,,1.00,, +matmul 1x36x36xf64,1.00,,0.99,, +matmul 1x36x40xf64,1.00,,0.99,, matmul 1x36x44xf64,1.00,,1.00,, -matmul 1x36x48xf64,1.00,,1.00,, +matmul 1x36x48xf64,1.00,,0.99,, matmul 1x36x4xf64,0.89,,0.96,, matmul 1x36x52xf64,1.00,,1.00,, matmul 1x36x56xf64,1.00,,1.00,, matmul 1x36x60xf64,1.00,,1.00,, matmul 1x36x64xf64,1.00,,1.00,, matmul 1x36x8xf64,0.94,,0.98,, -matmul 1x40x12xf64,0.98,,0.96,, +matmul 1x40x12xf64,0.98,,0.98,, matmul 1x40x16xf64,0.98,,0.97,, matmul 1x40x20xf64,1.00,,0.98,, matmul 1x40x24xf64,1.00,,0.98,, -matmul 1x40x28xf64,1.00,,0.99,, +matmul 1x40x28xf64,1.00,,0.98,, matmul 1x40x32xf64,1.00,,1.00,, -matmul 1x40x36xf64,1.00,,1.00,, +matmul 1x40x36xf64,1.00,,0.99,, matmul 1x40x40xf64,1.00,,1.00,, matmul 1x40x44xf64,1.00,,1.00,, -matmul 1x40x48xf64,1.00,,1.00,, +matmul 1x40x48xf64,1.00,,0.99,, matmul 1x40x4xf64,0.98,,0.96,, matmul 1x40x52xf64,1.00,,1.00,, matmul 1x40x56xf64,1.00,,1.00,, matmul 1x40x60xf64,1.00,,1.00,, matmul 1x40x64xf64,1.00,,1.00,, matmul 1x40x8xf64,0.98,,0.98,, -matmul 1x44x12xf64,0.98,,0.96,, +matmul 1x44x12xf64,0.98,,0.98,, matmul 1x44x16xf64,0.98,,0.97,, matmul 1x44x20xf64,1.00,,0.98,, matmul 1x44x24xf64,1.00,,0.98,, -matmul 1x44x28xf64,1.00,,0.99,, +matmul 1x44x28xf64,1.00,,0.98,, matmul 1x44x32xf64,1.00,,1.00,, -matmul 1x44x36xf64,1.00,,1.00,, -matmul 1x44x40xf64,1.00,,1.00,, +matmul 1x44x36xf64,1.00,,0.99,, +matmul 1x44x40xf64,1.00,,0.99,, matmul 1x44x44xf64,1.00,,1.00,, -matmul 1x44x48xf64,1.00,,1.00,, +matmul 1x44x48xf64,1.00,,0.99,, matmul 1x44x4xf64,0.98,,0.96,, matmul 1x44x52xf64,1.00,,1.00,, matmul 1x44x56xf64,1.00,,1.00,, matmul 1x44x60xf64,1.00,,1.00,, matmul 1x44x64xf64,1.00,,1.00,, matmul 1x44x8xf64,0.98,,0.98,, -matmul 1x48x12xf64,0.98,,0.97,, +matmul 1x48x12xf64,0.98,,0.98,, matmul 1x48x16xf64,0.98,,0.98,, -matmul 1x48x20xf64,1.00,,0.99,, -matmul 1x48x24xf64,1.00,,0.98,, -matmul 1x48x28xf64,1.00,,0.99,, +matmul 1x48x20xf64,1.00,,0.98,, +matmul 1x48x24xf64,1.00,,0.99,, +matmul 1x48x28xf64,1.00,,0.98,, matmul 1x48x32xf64,1.00,,1.00,, -matmul 1x48x36xf64,1.00,,1.00,, +matmul 1x48x36xf64,1.00,,0.99,, matmul 1x48x40xf64,1.00,,1.00,, matmul 1x48x44xf64,1.00,,1.00,, -matmul 1x48x48xf64,1.00,,1.00,, +matmul 1x48x48xf64,1.00,,0.99,, matmul 1x48x4xf64,0.98,,0.97,, matmul 1x48x52xf64,1.00,,1.00,, matmul 1x48x56xf64,1.00,,1.00,, matmul 1x48x60xf64,1.00,,1.00,, matmul 1x48x64xf64,1.00,,1.00,, matmul 1x48x8xf64,0.98,,0.98,, -matmul 1x4x12xf64,0.66,,0.97,, +matmul 1x4x12xf64,0.66,,0.98,, matmul 1x4x16xf64,0.67,,0.98,, -matmul 1x4x20xf64,0.67,,0.99,, -matmul 1x4x24xf64,0.67,,0.97,, -matmul 1x4x28xf64,0.68,,0.98,, +matmul 1x4x20xf64,0.67,,0.98,, +matmul 1x4x24xf64,0.67,,0.95,, +matmul 1x4x28xf64,0.68,,0.91,, matmul 1x4x32xf64,0.67,,0.96,, -matmul 1x4x36xf64,0.67,,0.97,, -matmul 1x4x40xf64,0.67,,0.98,, +matmul 1x4x36xf64,0.67,,0.96,, +matmul 1x4x40xf64,0.67,,0.99,, matmul 1x4x44xf64,0.67,,0.98,, -matmul 1x4x48xf64,0.68,,0.98,, +matmul 1x4x48xf64,0.68,,0.97,, matmul 1x4x4xf64,0.49,,0.88,, matmul 1x4x52xf64,0.68,,0.99,, -matmul 1x4x56xf64,0.68,,0.99,, -matmul 1x4x60xf64,0.68,,0.99,, +matmul 1x4x56xf64,0.68,,0.97,, +matmul 1x4x60xf64,0.68,,0.98,, matmul 1x4x64xf64,0.68,,1.01,, matmul 1x4x8xf64,0.52,,0.95,, -matmul 1x52x12xf64,0.98,,0.97,, +matmul 1x52x12xf64,0.98,,0.98,, matmul 1x52x16xf64,0.98,,0.98,, matmul 1x52x20xf64,1.00,,0.98,, -matmul 1x52x24xf64,1.00,,0.98,, +matmul 1x52x24xf64,1.00,,0.99,, matmul 1x52x28xf64,1.00,,0.99,, matmul 1x52x32xf64,1.00,,1.00,, -matmul 1x52x36xf64,1.00,,1.00,, +matmul 1x52x36xf64,1.00,,0.99,, matmul 1x52x40xf64,1.00,,1.00,, matmul 1x52x44xf64,1.00,,1.00,, matmul 1x52x48xf64,1.00,,1.00,, @@ -273,13 +276,13 @@ matmul 1x52x56xf64,1.00,,1.00,, matmul 1x52x60xf64,1.00,,1.00,, matmul 1x52x64xf64,1.00,,1.00,, matmul 1x52x8xf64,0.98,,0.98,, -matmul 1x56x12xf64,0.98,,0.97,, +matmul 1x56x12xf64,0.98,,0.98,, matmul 1x56x16xf64,0.98,,0.98,, -matmul 1x56x20xf64,1.00,,0.98,, -matmul 1x56x24xf64,1.00,,0.98,, +matmul 1x56x20xf64,1.00,,0.99,, +matmul 1x56x24xf64,1.00,,0.99,, matmul 1x56x28xf64,1.00,,0.99,, matmul 1x56x32xf64,1.00,,1.00,, -matmul 1x56x36xf64,1.00,,1.00,, +matmul 1x56x36xf64,1.00,,0.99,, matmul 1x56x40xf64,1.00,,1.00,, matmul 1x56x44xf64,1.00,,1.00,, matmul 1x56x48xf64,1.00,,1.00,, @@ -289,13 +292,13 @@ matmul 1x56x56xf64,1.00,,1.00,, matmul 1x56x60xf64,1.00,,1.00,, matmul 1x56x64xf64,1.00,,1.00,, matmul 1x56x8xf64,0.98,,0.98,, -matmul 1x60x12xf64,0.99,,0.97,, +matmul 1x60x12xf64,0.99,,0.98,, matmul 1x60x16xf64,0.99,,0.99,, -matmul 1x60x20xf64,1.00,,0.98,, +matmul 1x60x20xf64,1.00,,0.99,, matmul 1x60x24xf64,1.00,,0.99,, matmul 1x60x28xf64,1.00,,0.99,, matmul 1x60x32xf64,1.00,,1.00,, -matmul 1x60x36xf64,1.00,,1.00,, +matmul 1x60x36xf64,1.00,,0.99,, matmul 1x60x40xf64,1.00,,1.00,, matmul 1x60x44xf64,1.00,,1.00,, matmul 1x60x48xf64,1.00,,1.00,, @@ -305,13 +308,13 @@ matmul 1x60x56xf64,1.00,,1.00,, matmul 1x60x60xf64,1.00,,1.00,, matmul 1x60x64xf64,1.00,,1.00,, matmul 1x60x8xf64,0.98,,0.96,, -matmul 1x64x12xf64,0.99,,0.97,, +matmul 1x64x12xf64,0.99,,0.98,, matmul 1x64x16xf64,0.99,,0.99,, matmul 1x64x20xf64,1.00,,0.99,, matmul 1x64x24xf64,1.00,,0.99,, matmul 1x64x28xf64,1.00,,0.99,, matmul 1x64x32xf64,1.00,,1.00,, -matmul 1x64x36xf64,1.00,,1.00,, +matmul 1x64x36xf64,1.00,,0.99,, matmul 1x64x40xf64,1.00,,1.00,, matmul 1x64x44xf64,1.00,,1.00,, matmul 1x64x48xf64,1.00,,1.00,, @@ -324,24 +327,24 @@ matmul 1x64x8xf64,0.99,,0.98,, matmul 1x8x12xf64,0.63,,0.98,, matmul 1x8x16xf64,0.63,,0.99,, matmul 1x8x20xf64,0.63,,0.99,, -matmul 1x8x24xf64,0.62,,0.98,, -matmul 1x8x28xf64,0.63,,0.95,, +matmul 1x8x24xf64,0.62,,0.96,, +matmul 1x8x28xf64,0.63,,0.96,, matmul 1x8x32xf64,0.63,,0.99,, -matmul 1x8x36xf64,0.63,,0.99,, -matmul 1x8x40xf64,0.63,,1.00,, +matmul 1x8x36xf64,0.63,,0.97,, +matmul 1x8x40xf64,0.63,,0.98,, matmul 1x8x44xf64,0.63,,1.00,, -matmul 1x8x48xf64,0.63,,1.00,, +matmul 1x8x48xf64,0.63,,0.98,, matmul 1x8x4xf64,0.53,,0.90,, matmul 1x8x52xf64,0.63,,1.00,, -matmul 1x8x56xf64,0.63,,1.00,, -matmul 1x8x60xf64,0.63,,1.00,, +matmul 1x8x56xf64,0.63,,0.99,, +matmul 1x8x60xf64,0.63,,0.98,, matmul 1x8x64xf64,0.63,,1.01,, matmul 1x8x8xf64,0.54,,0.96,, matmul 4x12x12xf64,0.63,,0.99,, matmul 4x12x16xf64,0.63,,1.00,, matmul 4x12x20xf64,0.62,,1.00,, -matmul 4x12x24xf64,0.62,,1.01,, -matmul 4x12x28xf64,0.62,,1.01,, +matmul 4x12x24xf64,0.62,,1.00,, +matmul 4x12x28xf64,0.62,,1.00,, matmul 4x12x32xf64,0.62,,1.01,, matmul 4x12x36xf64,0.62,,1.01,, matmul 4x12x40xf64,0.62,,1.01,, @@ -353,35 +356,35 @@ matmul 4x12x56xf64,0.63,,1.01,, matmul 4x12x60xf64,0.63,,1.01,, matmul 4x12x64xf64,0.63,,1.01,, matmul 4x12x8xf64,0.64,,0.98,, -matmul 4x16x12xf64,0.62,,0.99,, +matmul 4x16x12xf64,0.62,,1.00,, matmul 4x16x16xf64,0.62,,1.00,, matmul 4x16x20xf64,0.61,,1.00,, -matmul 4x16x24xf64,0.61,,1.01,, -matmul 4x16x28xf64,0.61,,1.01,, +matmul 4x16x24xf64,0.61,,1.00,, +matmul 4x16x28xf64,0.61,,1.00,, matmul 4x16x32xf64,0.62,,1.01,, -matmul 4x16x36xf64,0.62,,1.01,, +matmul 4x16x36xf64,0.62,,1.00,, matmul 4x16x40xf64,0.63,,1.01,, matmul 4x16x44xf64,0.63,,1.01,, matmul 4x16x48xf64,0.63,,1.01,, matmul 4x16x4xf64,0.57,,0.97,, matmul 4x16x52xf64,0.64,,1.01,, matmul 4x16x56xf64,0.64,,1.01,, -matmul 4x16x60xf64,0.64,,1.01,, +matmul 4x16x60xf64,0.64,,1.00,, matmul 4x16x64xf64,0.65,,1.01,, matmul 4x16x8xf64,0.63,,0.98,, -matmul 4x20x12xf64,0.61,,0.99,, +matmul 4x20x12xf64,0.61,,1.00,, matmul 4x20x16xf64,0.61,,1.00,, matmul 4x20x20xf64,0.60,,1.00,, matmul 4x20x24xf64,0.60,,1.00,, -matmul 4x20x28xf64,0.61,,1.01,, +matmul 4x20x28xf64,0.61,,1.00,, matmul 4x20x32xf64,0.62,,1.01,, -matmul 4x20x36xf64,0.62,,1.01,, +matmul 4x20x36xf64,0.62,,1.00,, matmul 4x20x40xf64,0.61,,1.01,, matmul 4x20x44xf64,0.63,,1.01,, -matmul 4x20x48xf64,0.63,,1.01,, +matmul 4x20x48xf64,0.63,,1.00,, matmul 4x20x4xf64,0.64,,0.97,, matmul 4x20x52xf64,0.67,,1.01,, -matmul 4x20x56xf64,0.67,,1.01,, +matmul 4x20x56xf64,0.67,,1.00,, matmul 4x20x60xf64,0.67,,1.01,, matmul 4x20x64xf64,0.71,,1.01,, matmul 4x20x8xf64,0.62,,0.98,, @@ -391,14 +394,14 @@ matmul 4x24x20xf64,0.61,,1.00,, matmul 4x24x24xf64,0.66,,1.00,, matmul 4x24x28xf64,0.66,,1.00,, matmul 4x24x32xf64,0.61,,1.01,, -matmul 4x24x36xf64,0.62,,1.01,, -matmul 4x24x40xf64,0.61,,1.01,, +matmul 4x24x36xf64,0.62,,1.00,, +matmul 4x24x40xf64,0.61,,1.00,, matmul 4x24x44xf64,0.68,,1.01,, -matmul 4x24x48xf64,0.68,,1.01,, +matmul 4x24x48xf64,0.68,,1.00,, matmul 4x24x4xf64,0.64,,0.98,, matmul 4x24x52xf64,0.69,,1.01,, -matmul 4x24x56xf64,0.69,,1.01,, -matmul 4x24x60xf64,0.69,,1.01,, +matmul 4x24x56xf64,0.69,,1.00,, +matmul 4x24x60xf64,0.69,,1.00,, matmul 4x24x64xf64,0.68,,1.01,, matmul 4x24x8xf64,0.62,,0.99,, matmul 4x28x12xf64,0.64,,1.00,, @@ -407,17 +410,17 @@ matmul 4x28x20xf64,0.63,,1.00,, matmul 4x28x24xf64,0.63,,1.00,, matmul 4x28x28xf64,0.63,,1.00,, matmul 4x28x32xf64,0.61,,1.00,, -matmul 4x28x36xf64,0.61,,1.01,, -matmul 4x28x40xf64,0.64,,1.01,, +matmul 4x28x36xf64,0.61,,1.00,, +matmul 4x28x40xf64,0.64,,1.00,, matmul 4x28x44xf64,0.66,,1.01,, -matmul 4x28x48xf64,0.66,,1.01,, +matmul 4x28x48xf64,0.66,,1.00,, matmul 4x28x4xf64,0.65,,0.98,, matmul 4x28x52xf64,0.64,,1.01,, -matmul 4x28x56xf64,0.64,,1.01,, -matmul 4x28x60xf64,0.64,,1.01,, +matmul 4x28x56xf64,0.64,,1.00,, +matmul 4x28x60xf64,0.64,,1.00,, matmul 4x28x64xf64,0.67,,1.01,, matmul 4x28x8xf64,0.64,,0.99,, -matmul 4x32x12xf64,0.97,,1.00,, +matmul 4x32x12xf64,0.97,,0.99,, matmul 4x32x16xf64,0.98,,1.00,, matmul 4x32x20xf64,0.92,,1.00,, matmul 4x32x24xf64,0.92,,1.00,, @@ -426,11 +429,11 @@ matmul 4x32x32xf64,0.92,,1.00,, matmul 4x32x36xf64,0.92,,1.00,, matmul 4x32x40xf64,0.93,,1.00,, matmul 4x32x44xf64,0.93,,1.01,, -matmul 4x32x48xf64,0.93,,1.01,, +matmul 4x32x48xf64,0.93,,1.00,, matmul 4x32x4xf64,0.97,,0.99,, matmul 4x32x52xf64,0.93,,1.01,, -matmul 4x32x56xf64,0.93,,1.01,, -matmul 4x32x60xf64,0.93,,1.01,, +matmul 4x32x56xf64,0.93,,1.00,, +matmul 4x32x60xf64,0.93,,1.00,, matmul 4x32x64xf64,0.94,,1.01,, matmul 4x32x8xf64,0.96,,1.00,, matmul 4x36x12xf64,0.99,,1.00,, @@ -446,7 +449,7 @@ matmul 4x36x48xf64,1.00,,1.00,, matmul 4x36x4xf64,0.96,,0.99,, matmul 4x36x52xf64,1.00,,1.00,, matmul 4x36x56xf64,1.00,,1.00,, -matmul 4x36x60xf64,1.00,,1.01,, +matmul 4x36x60xf64,1.00,,1.00,, matmul 4x36x64xf64,1.00,,1.01,, matmul 4x36x8xf64,0.99,,1.00,, matmul 4x40x12xf64,0.99,,1.00,, @@ -497,11 +500,11 @@ matmul 4x48x56xf64,1.00,,1.00,, matmul 4x48x60xf64,1.00,,1.00,, matmul 4x48x64xf64,1.00,,1.00,, matmul 4x48x8xf64,0.99,,1.00,, -matmul 4x4x12xf64,0.68,,0.98,, +matmul 4x4x12xf64,0.68,,0.99,, matmul 4x4x16xf64,0.68,,0.99,, -matmul 4x4x20xf64,0.68,,1.00,, -matmul 4x4x24xf64,0.68,,1.00,, -matmul 4x4x28xf64,0.68,,1.01,, +matmul 4x4x20xf64,0.68,,1.01,, +matmul 4x4x24xf64,0.68,,1.01,, +matmul 4x4x28xf64,0.68,,1.00,, matmul 4x4x32xf64,0.68,,1.01,, matmul 4x4x36xf64,0.68,,1.01,, matmul 4x4x40xf64,0.68,,1.02,, @@ -509,7 +512,7 @@ matmul 4x4x44xf64,0.68,,1.02,, matmul 4x4x48xf64,0.68,,1.02,, matmul 4x4x4xf64,0.51,,0.93,, matmul 4x4x52xf64,0.68,,1.02,, -matmul 4x4x56xf64,0.68,,1.02,, +matmul 4x4x56xf64,0.68,,1.01,, matmul 4x4x60xf64,0.68,,1.02,, matmul 4x4x64xf64,0.68,,1.02,, matmul 4x4x8xf64,0.53,,0.95,, @@ -577,20 +580,20 @@ matmul 4x64x56xf64,1.00,,1.00,, matmul 4x64x60xf64,1.00,,1.00,, matmul 4x64x64xf64,1.00,,1.00,, matmul 4x64x8xf64,1.00,,1.00,, -matmul 4x8x12xf64,0.63,,0.98,, +matmul 4x8x12xf64,0.63,,0.99,, matmul 4x8x16xf64,0.63,,0.99,, matmul 4x8x20xf64,0.63,,1.00,, matmul 4x8x24xf64,0.63,,1.00,, -matmul 4x8x28xf64,0.63,,1.01,, +matmul 4x8x28xf64,0.63,,1.00,, matmul 4x8x32xf64,0.63,,1.01,, -matmul 4x8x36xf64,0.63,,1.01,, -matmul 4x8x40xf64,0.63,,1.02,, +matmul 4x8x36xf64,0.63,,1.00,, +matmul 4x8x40xf64,0.63,,1.01,, matmul 4x8x44xf64,0.63,,1.02,, -matmul 4x8x48xf64,0.63,,1.02,, +matmul 4x8x48xf64,0.63,,1.01,, matmul 4x8x4xf64,0.57,,0.95,, matmul 4x8x52xf64,0.68,,1.01,, -matmul 4x8x56xf64,0.68,,1.02,, -matmul 4x8x60xf64,0.68,,1.02,, +matmul 4x8x56xf64,0.68,,1.01,, +matmul 4x8x60xf64,0.68,,1.01,, matmul 4x8x64xf64,0.63,,1.02,, matmul 4x8x8xf64,0.55,,0.97,, matmul 8x12x12xf64,0.63,,1.00,, @@ -605,14 +608,14 @@ matmul 8x12x44xf64,0.63,,1.01,, matmul 8x12x48xf64,0.63,,1.01,, matmul 8x12x4xf64,0.57,,0.99,, matmul 8x12x52xf64,0.63,,1.02,, -matmul 8x12x56xf64,0.63,,1.02,, -matmul 8x12x60xf64,0.63,,1.02,, +matmul 8x12x56xf64,0.63,,1.01,, +matmul 8x12x60xf64,0.63,,1.01,, matmul 8x12x64xf64,0.63,,1.02,, matmul 8x12x8xf64,0.64,,1.00,, matmul 8x16x12xf64,0.62,,1.00,, matmul 8x16x16xf64,0.62,,1.00,, matmul 8x16x20xf64,0.61,,1.01,, -matmul 8x16x24xf64,0.61,,1.01,, +matmul 8x16x24xf64,0.61,,1.00,, matmul 8x16x28xf64,0.61,,1.01,, matmul 8x16x32xf64,0.62,,1.01,, matmul 8x16x36xf64,0.62,,1.01,, @@ -628,8 +631,8 @@ matmul 8x16x8xf64,0.63,,1.00,, matmul 8x20x12xf64,0.61,,1.00,, matmul 8x20x16xf64,0.61,,1.01,, matmul 8x20x20xf64,0.60,,1.01,, -matmul 8x20x24xf64,0.60,,1.01,, -matmul 8x20x28xf64,0.61,,1.01,, +matmul 8x20x24xf64,0.60,,1.00,, +matmul 8x20x28xf64,0.61,,1.00,, matmul 8x20x32xf64,0.62,,1.01,, matmul 8x20x36xf64,0.62,,1.01,, matmul 8x20x40xf64,0.61,,1.01,, @@ -637,56 +640,56 @@ matmul 8x20x44xf64,0.63,,1.01,, matmul 8x20x48xf64,0.63,,1.01,, matmul 8x20x4xf64,0.64,,0.99,, matmul 8x20x52xf64,0.67,,1.01,, -matmul 8x20x56xf64,0.67,,1.01,, +matmul 8x20x56xf64,0.67,,1.00,, matmul 8x20x60xf64,0.67,,1.01,, matmul 8x20x64xf64,0.71,,1.01,, matmul 8x20x8xf64,0.62,,1.00,, matmul 8x24x12xf64,0.61,,1.00,, matmul 8x24x16xf64,0.61,,1.01,, -matmul 8x24x20xf64,0.61,,1.01,, -matmul 8x24x24xf64,0.66,,1.01,, -matmul 8x24x28xf64,0.66,,1.01,, +matmul 8x24x20xf64,0.61,,1.00,, +matmul 8x24x24xf64,0.66,,1.00,, +matmul 8x24x28xf64,0.66,,1.00,, matmul 8x24x32xf64,0.61,,1.01,, -matmul 8x24x36xf64,0.62,,1.01,, +matmul 8x24x36xf64,0.62,,1.00,, matmul 8x24x40xf64,0.61,,1.01,, matmul 8x24x44xf64,0.68,,1.01,, matmul 8x24x48xf64,0.68,,1.01,, matmul 8x24x4xf64,0.63,,0.99,, matmul 8x24x52xf64,0.69,,1.01,, -matmul 8x24x56xf64,0.69,,1.01,, +matmul 8x24x56xf64,0.69,,1.00,, matmul 8x24x60xf64,0.69,,1.01,, matmul 8x24x64xf64,0.68,,1.01,, matmul 8x24x8xf64,0.62,,1.00,, matmul 8x28x12xf64,0.64,,1.00,, matmul 8x28x16xf64,0.63,,1.00,, -matmul 8x28x20xf64,0.63,,1.01,, -matmul 8x28x24xf64,0.63,,1.01,, -matmul 8x28x28xf64,0.63,,1.01,, +matmul 8x28x20xf64,0.63,,1.00,, +matmul 8x28x24xf64,0.63,,1.00,, +matmul 8x28x28xf64,0.63,,1.00,, matmul 8x28x32xf64,0.61,,1.01,, -matmul 8x28x36xf64,0.61,,1.01,, -matmul 8x28x40xf64,0.64,,1.01,, +matmul 8x28x36xf64,0.61,,1.00,, +matmul 8x28x40xf64,0.64,,1.00,, matmul 8x28x44xf64,0.66,,1.01,, -matmul 8x28x48xf64,0.66,,1.01,, +matmul 8x28x48xf64,0.66,,1.00,, matmul 8x28x4xf64,0.65,,0.99,, matmul 8x28x52xf64,0.64,,1.01,, -matmul 8x28x56xf64,0.64,,1.01,, -matmul 8x28x60xf64,0.64,,1.01,, +matmul 8x28x56xf64,0.64,,1.00,, +matmul 8x28x60xf64,0.64,,1.00,, matmul 8x28x64xf64,0.67,,1.01,, matmul 8x28x8xf64,0.64,,1.00,, matmul 8x32x12xf64,0.98,,1.00,, matmul 8x32x16xf64,0.98,,1.00,, matmul 8x32x20xf64,0.96,,1.00,, -matmul 8x32x24xf64,0.96,,1.01,, +matmul 8x32x24xf64,0.96,,1.00,, matmul 8x32x28xf64,0.96,,1.00,, matmul 8x32x32xf64,0.96,,1.01,, -matmul 8x32x36xf64,0.96,,1.01,, -matmul 8x32x40xf64,0.96,,1.01,, +matmul 8x32x36xf64,0.96,,1.00,, +matmul 8x32x40xf64,0.96,,1.00,, matmul 8x32x44xf64,0.97,,1.01,, -matmul 8x32x48xf64,0.97,,1.01,, +matmul 8x32x48xf64,0.97,,1.00,, matmul 8x32x4xf64,0.97,,1.00,, matmul 8x32x52xf64,0.97,,1.01,, -matmul 8x32x56xf64,0.97,,1.01,, -matmul 8x32x60xf64,0.97,,1.01,, +matmul 8x32x56xf64,0.97,,1.00,, +matmul 8x32x60xf64,0.97,,1.00,, matmul 8x32x64xf64,0.97,,1.01,, matmul 8x32x8xf64,0.97,,1.00,, matmul 8x36x12xf64,1.00,,1.00,, @@ -696,13 +699,13 @@ matmul 8x36x24xf64,1.00,,1.00,, matmul 8x36x28xf64,1.00,,1.00,, matmul 8x36x32xf64,1.00,,1.00,, matmul 8x36x36xf64,1.00,,1.00,, -matmul 8x36x40xf64,1.00,,1.01,, +matmul 8x36x40xf64,1.00,,1.00,, matmul 8x36x44xf64,1.00,,1.01,, -matmul 8x36x48xf64,1.00,,1.01,, +matmul 8x36x48xf64,1.00,,1.00,, matmul 8x36x4xf64,1.00,,1.00,, matmul 8x36x52xf64,1.00,,1.01,, -matmul 8x36x56xf64,1.00,,1.01,, -matmul 8x36x60xf64,1.00,,1.01,, +matmul 8x36x56xf64,1.00,,1.00,, +matmul 8x36x60xf64,1.00,,1.00,, matmul 8x36x64xf64,1.00,,1.01,, matmul 8x36x8xf64,1.00,,1.00,, matmul 8x40x12xf64,1.00,,1.00,, @@ -717,7 +720,7 @@ matmul 8x40x44xf64,1.00,,1.00,, matmul 8x40x48xf64,1.00,,1.00,, matmul 8x40x4xf64,1.00,,1.00,, matmul 8x40x52xf64,1.00,,1.00,, -matmul 8x40x56xf64,1.00,,1.01,, +matmul 8x40x56xf64,1.00,,1.00,, matmul 8x40x60xf64,1.00,,1.00,, matmul 8x40x64xf64,1.00,,1.01,, matmul 8x40x8xf64,1.00,,1.00,, @@ -753,20 +756,20 @@ matmul 8x48x56xf64,1.00,,1.00,, matmul 8x48x60xf64,1.00,,1.00,, matmul 8x48x64xf64,1.00,,1.00,, matmul 8x48x8xf64,1.00,,1.00,, -matmul 8x4x12xf64,0.70,,1.00,, +matmul 8x4x12xf64,0.70,,1.01,, matmul 8x4x16xf64,0.70,,1.01,, matmul 8x4x20xf64,0.69,,1.02,, matmul 8x4x24xf64,0.69,,1.02,, -matmul 8x4x28xf64,0.69,,1.02,, +matmul 8x4x28xf64,0.69,,1.01,, matmul 8x4x32xf64,0.69,,1.03,, -matmul 8x4x36xf64,0.69,,1.03,, -matmul 8x4x40xf64,0.69,,1.03,, +matmul 8x4x36xf64,0.69,,1.02,, +matmul 8x4x40xf64,0.69,,1.02,, matmul 8x4x44xf64,0.69,,1.03,, -matmul 8x4x48xf64,0.69,,1.03,, +matmul 8x4x48xf64,0.69,,1.02,, matmul 8x4x4xf64,0.56,,0.98,, matmul 8x4x52xf64,0.69,,1.03,, -matmul 8x4x56xf64,0.69,,1.03,, -matmul 8x4x60xf64,0.68,,1.03,, +matmul 8x4x56xf64,0.69,,1.02,, +matmul 8x4x60xf64,0.68,,1.02,, matmul 8x4x64xf64,0.68,,1.03,, matmul 8x4x8xf64,0.54,,0.99,, matmul 8x52x12xf64,1.00,,1.00,, @@ -839,14 +842,14 @@ matmul 8x8x20xf64,0.64,,1.01,, matmul 8x8x24xf64,0.64,,1.01,, matmul 8x8x28xf64,0.64,,1.01,, matmul 8x8x32xf64,0.64,,1.02,, -matmul 8x8x36xf64,0.64,,1.02,, +matmul 8x8x36xf64,0.64,,1.01,, matmul 8x8x40xf64,0.64,,1.02,, matmul 8x8x44xf64,0.64,,1.02,, -matmul 8x8x48xf64,0.64,,1.02,, +matmul 8x8x48xf64,0.64,,1.01,, matmul 8x8x4xf64,0.56,,0.99,, matmul 8x8x52xf64,0.64,,1.02,, -matmul 8x8x56xf64,0.63,,1.02,, -matmul 8x8x60xf64,0.63,,1.02,, +matmul 8x8x56xf64,0.63,,1.01,, +matmul 8x8x60xf64,0.63,,1.01,, matmul 8x8x64xf64,0.63,,1.02,, matmul 8x8x8xf64,0.55,,0.99,, matmul_transb 1x12x40xf32,,,,1.09, @@ -858,29 +861,29 @@ matmul_transb 1x20x40xf32,,,,1.06, matmul_transb 1x20x8xf32,,,,1.03, matmul_transb 1x4x40xf32,,,,0.96, matmul_transb 1x8x40xf32,,,,1.11, -pooling_nchw_max_d1_s2_3x3 12x12xf64,0.83,0.85,0.99,, +pooling_nchw_max_d1_s2_3x3 12x12xf64,0.83,0.85,0.97,, pooling_nchw_max_d1_s2_3x3 12x16xf64,0.83,0.85,1.01,, -pooling_nchw_max_d1_s2_3x3 12x20xf64,0.83,0.85,1.02,, +pooling_nchw_max_d1_s2_3x3 12x20xf64,0.83,0.85,1.01,, pooling_nchw_max_d1_s2_3x3 12x4xf64,0.73,0.78,1.04,, pooling_nchw_max_d1_s2_3x3 12x8xf64,0.84,0.81,0.97,, -pooling_nchw_max_d1_s2_3x3 16x12xf64,0.83,0.85,1.00,, +pooling_nchw_max_d1_s2_3x3 16x12xf64,0.83,0.85,0.98,, pooling_nchw_max_d1_s2_3x3 16x16xf64,0.83,0.85,1.01,, -pooling_nchw_max_d1_s2_3x3 16x20xf64,0.83,0.85,1.02,, +pooling_nchw_max_d1_s2_3x3 16x20xf64,0.83,0.85,1.01,, pooling_nchw_max_d1_s2_3x3 16x4xf64,0.73,0.78,1.05,, pooling_nchw_max_d1_s2_3x3 16x8xf64,0.84,0.81,0.97,, -pooling_nchw_max_d1_s2_3x3 20x12xf64,0.83,0.85,1.00,, +pooling_nchw_max_d1_s2_3x3 20x12xf64,0.83,0.85,0.98,, pooling_nchw_max_d1_s2_3x3 20x16xf64,0.83,0.85,1.01,, -pooling_nchw_max_d1_s2_3x3 20x20xf64,0.83,0.85,1.02,, +pooling_nchw_max_d1_s2_3x3 20x20xf64,0.83,0.85,1.01,, pooling_nchw_max_d1_s2_3x3 20x4xf64,0.73,0.79,1.05,, pooling_nchw_max_d1_s2_3x3 20x8xf64,0.84,0.81,0.97,, -pooling_nchw_max_d1_s2_3x3 4x12xf64,0.82,0.86,0.98,, +pooling_nchw_max_d1_s2_3x3 4x12xf64,0.82,0.86,0.95,, pooling_nchw_max_d1_s2_3x3 4x16xf64,0.82,0.84,1.00,, -pooling_nchw_max_d1_s2_3x3 4x20xf64,0.82,0.84,1.01,, +pooling_nchw_max_d1_s2_3x3 4x20xf64,0.82,0.84,1.00,, pooling_nchw_max_d1_s2_3x3 4x4xf64,0.72,0.74,1.02,, pooling_nchw_max_d1_s2_3x3 4x8xf64,0.82,0.72,0.96,, -pooling_nchw_max_d1_s2_3x3 8x12xf64,0.83,0.85,0.99,, +pooling_nchw_max_d1_s2_3x3 8x12xf64,0.83,0.85,0.97,, pooling_nchw_max_d1_s2_3x3 8x16xf64,0.83,0.84,1.01,, -pooling_nchw_max_d1_s2_3x3 8x20xf64,0.83,0.84,1.02,, +pooling_nchw_max_d1_s2_3x3 8x20xf64,0.83,0.84,1.01,, pooling_nchw_max_d1_s2_3x3 8x4xf64,0.73,0.77,1.03,, pooling_nchw_max_d1_s2_3x3 8x8xf64,0.84,0.81,0.97,, pooling_nchw_sum_d1_s2_3x3 12x12xf64,0.57,0.60,0.96,, @@ -893,17 +896,17 @@ pooling_nchw_sum_d1_s2_3x3 16x16xf64,0.57,0.60,0.97,, pooling_nchw_sum_d1_s2_3x3 16x20xf64,0.57,0.59,0.98,, pooling_nchw_sum_d1_s2_3x3 16x4xf64,0.49,0.48,0.99,, pooling_nchw_sum_d1_s2_3x3 16x8xf64,0.58,0.56,0.95,, -pooling_nchw_sum_d1_s2_3x3 20x12xf64,0.57,0.60,0.97,, +pooling_nchw_sum_d1_s2_3x3 20x12xf64,0.57,0.60,0.96,, pooling_nchw_sum_d1_s2_3x3 20x16xf64,0.57,0.60,0.97,, pooling_nchw_sum_d1_s2_3x3 20x20xf64,0.57,0.59,0.98,, pooling_nchw_sum_d1_s2_3x3 20x4xf64,0.49,0.48,1.00,, pooling_nchw_sum_d1_s2_3x3 20x8xf64,0.58,0.55,0.95,, pooling_nchw_sum_d1_s2_3x3 4x12xf64,0.57,0.60,0.95,, pooling_nchw_sum_d1_s2_3x3 4x16xf64,0.57,0.60,0.97,, -pooling_nchw_sum_d1_s2_3x3 4x20xf64,0.57,0.60,0.98,, +pooling_nchw_sum_d1_s2_3x3 4x20xf64,0.57,0.60,0.97,, pooling_nchw_sum_d1_s2_3x3 4x4xf64,0.49,0.49,0.99,, pooling_nchw_sum_d1_s2_3x3 4x8xf64,0.46,0.44,0.93,, -pooling_nchw_sum_d1_s2_3x3 8x12xf64,0.57,0.60,0.96,, +pooling_nchw_sum_d1_s2_3x3 8x12xf64,0.57,0.60,0.95,, pooling_nchw_sum_d1_s2_3x3 8x16xf64,0.57,0.60,0.97,, pooling_nchw_sum_d1_s2_3x3 8x20xf64,0.57,0.60,0.98,, pooling_nchw_sum_d1_s2_3x3 8x4xf64,0.49,0.49,0.97,, From bb6a117b75c981effbe997543b9c8af298a89dc6 Mon Sep 17 00:00:00 2001 From: szerdick Date: Sun, 10 May 2026 22:48:50 +0200 Subject: [PATCH 10/33] new kernel to test polynomial evaluation via degree --- Makefile | 8 +- Snakefile | 101 +++++++++++++++++++- kernels/exp_polynomial/data.h.template | 31 ++++++ kernels/exp_polynomial/gendata.py | 39 ++++++++ kernels/exp_polynomial/linalg.mlir.template | 17 ++++ kernels/exp_polynomial/main.c | 56 +++++++++++ 6 files changed, 249 insertions(+), 3 deletions(-) create mode 100644 kernels/exp_polynomial/data.h.template create mode 100644 kernels/exp_polynomial/gendata.py create mode 100644 kernels/exp_polynomial/linalg.mlir.template create mode 100644 kernels/exp_polynomial/main.c diff --git a/Makefile b/Makefile index acc679ad..c930c016 100644 --- a/Makefile +++ b/Makefile @@ -30,17 +30,21 @@ pipeline: exp_micro: snakemake --cores $(JOBS) --rerun-incomplete exp_micro +.PHONY: exp_polynomial +exp_polynomial: + snakemake --cores $(JOBS) --rerun-incomplete exp_polynomial + .PHONY: exp_macro exp_macro: snakemake --cores $(JOBS) --rerun-incomplete exp_macro .PHONY: exp exp: - snakemake --cores $(JOBS) --rerun-incomplete exp_micro exp_macro + snakemake --cores $(JOBS) --rerun-incomplete exp_micro exp_macro exp_polynomial .PHONY: clean clean: - snakemake --delete-all-output --rerun-incomplete fast all pipeline low_level_representation exp_micro exp_macro + snakemake --delete-all-output --rerun-incomplete fast all pipeline low_level_representation exp_micro exp_macro exp_polynomial .PHONY: docker-build docker-build: diff --git a/Snakefile b/Snakefile index 5c5702d9..ed4b303e 100644 --- a/Snakefile +++ b/Snakefile @@ -50,10 +50,25 @@ XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 = [ if int(v.rsplit("_b", 1)[1]) < 11 ] +XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS = [ + "linalg_xdsl_d2", + "linalg_xdsl_d3", + "linalg_xdsl_d4", + "linalg_xdsl_d5", + "linalg_xdsl_d6", + "linalg_xdsl_d7", + "linalg_xdsl_d8", + "linalg_xdsl_d9", + "linalg_xdsl_d10", + "linalg_xdsl_d11", + "linalg_xdsl_d12", +] + XDSL_LINALG_VARIANTS = [ "linalg_xdsl", # xDSL lowering from linalg on tensors *XDSL_LINALG_OPT_VARIANTS, *XDSL_LINALG_MAX_BITS_LOST_VARIANTS, + *XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS, ] XDSL_VARIANTS = [ @@ -85,6 +100,7 @@ SHAPE_3D = r"(?P\d+)x(?P\d+)x(?P\d+)xf(?P\d+)" KERNEL_SHAPE = { "exp_micro": SHAPE_1D, "exp_macro": SHAPE_1D, + "exp_polynomial": SHAPE_1D, "sum": SHAPE_2D, "relu": SHAPE_2D, "fill": SHAPE_2D, @@ -261,6 +277,14 @@ TESTSET_EXP_MICRO = [ variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS, ), ] +TESTSET_EXP_POLYNOMIAL = [ + *expand( + "exp_polynomial/{N}xf{precision}/{variant}", + N=range(64, 129, 16), + precision=[616, 32, 4], + variant=XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS, + ), +] TESTSET_EXP_MACRO = [ *expand( @@ -278,6 +302,7 @@ TESTSET_ALL = [ *TESTSET_PIPELINE, *TESTSET_EXP_MICRO, *TESTSET_EXP_MACRO, + *TESTSET_EXP_POLYNOMIAL, # 3d templated kernels: baseline + linalg_xdsl *expand( "matmul/{M}x{K}x{N}xf64/{variant}", @@ -787,7 +812,12 @@ rule xdsl_kernel_generate_source: "kernels/{kernel}/{shape}/{variant}.xdsl.mlir", wildcard_constraints: kernel="|".join(KERNEL_TEMPLATES), - variant="|".join(v for v in XDSL_LINALG_VARIANTS if v not in XDSL_LINALG_MAX_BITS_LOST_VARIANTS), + variant="|".join( + v + for v in XDSL_LINALG_VARIANTS + if v not in XDSL_LINALG_MAX_BITS_LOST_VARIANTS + and v not in XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS + ), params: format_template="scripts/format.py", xdsl_opt=config["xdsl-opt"], @@ -840,3 +870,72 @@ rule xdsl_kernel_generate_source_exp_attrs: | {params.xdsl_opt} -p arith-add-fastmath \ | sed 's/arith.maximumf/arith.maxf/g' > {output} """ + + +# Chebyshev approximation domain for exp_polynomial. Must match the +# DOMAIN_LOWER/DOMAIN_UPPER in kernels/exp_polynomial/gendata.py. +CHEBYSHEV_DOMAIN_LOWER = -2.0 +CHEBYSHEV_DOMAIN_UPPER = 0.0 + + +def get_chebyshev_coeffs_from_variant(wildcards): + """Compute the Chebyshev coefficient list for the variant. + + Uses Chebyshev-Lobatto nodes via DCT-I. + (Can not use numpy's Chebyshev.interpolate here because it returns standard + (single-prime) coefficients. + """ + import math + import re + + m = re.search(r"_d(\d+)$", wildcards.variant) + if not m: + raise ValueError( + f"Cannot extract Chebyshev degree from variant: {wildcards.variant}" + ) + degree = int(m.group(1)) + n = degree + lower = CHEBYSHEV_DOMAIN_LOWER + upper = CHEBYSHEV_DOMAIN_UPPER + nodes = [math.cos(math.pi * j / n) for j in range(n + 1)] + mid = (upper + lower) / 2.0 + half = (upper - lower) / 2.0 + values = [math.exp(half * t + mid) for t in nodes] + coeffs: list[float] = [] + for k in range(n + 1): + s = 0.0 + for j in range(n + 1): + w = 0.5 if (j == 0 or j == n) else 1.0 + s += w * values[j] * math.cos(math.pi * k * j / n) + coeffs.append(2.0 * s / n) + return ", ".join(f"{c:.16e} : f64" for c in coeffs) + + +def get_chebyshev_bounds_string(wildcards): + return ( + f"domain_lower = {CHEBYSHEV_DOMAIN_LOWER:.6e} : f64, " + f"domain_upper = {CHEBYSHEV_DOMAIN_UPPER:.6e} : f64" + ) + + +rule xdsl_kernel_generate_source_chebyshev: + input: + json="kernels/{kernel}/{shape}/params.json", + template="kernels/{kernel}/linalg.mlir.template", + output: + "kernels/{kernel}/{shape}/{variant}.xdsl.mlir", + wildcard_constraints: + kernel="|".join(KERNEL_TEMPLATES), + variant="|".join(XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS), + params: + format_template="scripts/format.py", + xdsl_opt=config["xdsl-opt"], + coeffs=get_chebyshev_coeffs_from_variant, + bounds=get_chebyshev_bounds_string, + shell: + """ + python3 {params.format_template} {input.template} {input.json} \ + | sed 's/__COEFFS__/{params.coeffs}/g' \ + | sed 's/scheme = "clenshaw"/scheme = "clenshaw", {params.bounds}/g' \ + | {params.xdsl_opt} -p arith-add-fastmath > {output} + """ diff --git a/kernels/exp_polynomial/data.h.template b/kernels/exp_polynomial/data.h.template new file mode 100644 index 00000000..2df3762d --- /dev/null +++ b/kernels/exp_polynomial/data.h.template @@ -0,0 +1,31 @@ +#pragma once + +#define PRECISION {{precision}} +#if PRECISION == 16 +#define DTYPE __fp16 +#define EXPF expf +#define FABSF fabsf +#elif PRECISION == 32 +#define DTYPE float +#define EXPF expf +#define FABSF fabsf +#elif PRECISION == 64 +#define DTYPE double +#define EXPF exp +#define FABSF fabs +#else +#error Unsupported precision +#endif + +#define N {{N}} + +#ifdef __cplusplus +extern "C" { +#endif + +extern const DTYPE X[N]; +extern const DTYPE G[N]; + +#ifdef __cplusplus +} +#endif diff --git a/kernels/exp_polynomial/gendata.py b/kernels/exp_polynomial/gendata.py new file mode 100644 index 00000000..ef24aaae --- /dev/null +++ b/kernels/exp_polynomial/gendata.py @@ -0,0 +1,39 @@ +#!/usr/bin/env python3 + +import numpy as np +from typing import Iterator + +from gendatautils import main, Define, Array + + +# Chebyshev approximation domain for the exp kernel. Must match the +# `domain_lower`/`domain_upper` attributes injected into polynomial.eval +# by the Snakefile rule for the `linalg_xdsl_d*` variants. +DOMAIN_LOWER: float = -2.0 +DOMAIN_UPPER: float = 0.0 + + +def exp_polynomial_data( + N: int, rmin: float, rmax: float, precision: int +) -> Iterator[Define | Array]: + yield Define("N", N) + + t = {16: np.float16, 32: np.float32, 64: np.float64}[precision] + + # Clamp the random range to the approximation domain so inputs stay + # inside [DOMAIN_LOWER, DOMAIN_UPPER] where the Chebyshev fit is valid. + rmin = max(rmin, DOMAIN_LOWER) + rmax = min(rmax, DOMAIN_UPPER) + + np.random.seed(0) + x = np.random.uniform(rmin, rmax, N).astype(t) + + # Compute golden reference in float64 then cast down. + g = np.exp(x.astype(np.float64)).astype(t) + + yield Array("X", ("N",), x) + yield Array("G", ("N",), g) + + +if __name__ == "__main__": + main(exp_polynomial_data) diff --git a/kernels/exp_polynomial/linalg.mlir.template b/kernels/exp_polynomial/linalg.mlir.template new file mode 100644 index 00000000..07cc18b6 --- /dev/null +++ b/kernels/exp_polynomial/linalg.mlir.template @@ -0,0 +1,17 @@ +module { + func.func public @exp_kernel( + %arg0: memref<{{N}}xf{{precision}}> {llvm.noalias}, + %arg1: memref<{{N}}xf{{precision}}> {llvm.noalias}) -> memref<{{N}}xf{{precision}}> { + linalg.generic { + indexing_maps = [ + affine_map<(d0) -> (d0)>, + affine_map<(d0) -> (d0)>], + iterator_types = ["parallel"] + } ins(%arg0 : memref<{{N}}xf{{precision}}>) outs(%arg1 : memref<{{N}}xf{{precision}}>) { + ^bb0(%in: f{{precision}}, %out: f{{precision}}): + %0 = polynomial.eval #polynomial.typed_chebyshev_polynomial<[__COEFFS__]> : !polynomial.polynomial>, %in {scheme = "clenshaw"} : f{{precision}} + linalg.yield %0 : f{{precision}} + } + return %arg1 : memref<{{N}}xf{{precision}}> + } +} diff --git a/kernels/exp_polynomial/main.c b/kernels/exp_polynomial/main.c new file mode 100644 index 00000000..975ffbbd --- /dev/null +++ b/kernels/exp_polynomial/main.c @@ -0,0 +1,56 @@ +#include "data.h" + +#include + +#include + +#include + +extern "C" { + void *_sbrk(ptrdiff_t incr) { (void)incr; return (void *)-1; } + int _read(int fd, void *buf, size_t count) { (void)fd; (void)buf; (void)count; return -1; } + int _write(int fd, const void *buf, size_t count) { (void)fd; (void)buf; (void)count; return -1; } + int _lseek(int fd, long offset, int whence) { (void)fd; (void)offset; (void)whence; return -1; } + int _close(int fd) { (void)fd; return -1; } +} + +// Kernel provided via external definition +extern "C" void exp_kernel(const DTYPE *x, DTYPE *z); + +int main() { + // Allocate shared local memory + // By avoiding allocators and bumping by a known offset a base pointer + // (snrt_l1_next()) that is the same for all the cores in the cluster, we are + // essentially providing the same memory regions to all the cores in this cluster. + DTYPE *local_x = (DTYPE *)snrt_l1_next(); + DTYPE *local_z = local_x + N; + + // Copy data in shared local memory + if (snrt_is_dm_core()) { + snrt_dma_start_1d((uint64_t)local_x, (uint64_t)X, N * sizeof(DTYPE)); + snrt_dma_wait_all(); + } + + snrt_cluster_hw_barrier(); + + // Launch kernel: from this point on only core 0 is required to be alive. + int thiscore = snrt_cluster_core_idx(); + if (thiscore != 0) return 0; + + snrt_fpu_fence(); + (void)snrt_mcycle(); + exp_kernel(local_x, local_z); + snrt_fpu_fence(); + (void)snrt_mcycle(); + + // Correctness check. + int nerr = 0; + for (int i = 0; i < N; i++) { + printf("x[%d] = %f, G[%d] = %f, z[%d] = %f\n", i, local_x[i], i, G[i], i, local_z[i]); + DTYPE d = FABSF(local_z[i] - G[i]); + DTYPE ref = FABSF(G[i]); + DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)2E-1 : (DTYPE)2E-1; + nerr += !(d <= tol); + } + return nerr; +} From 2744e54739b994442fe7adb8a029af14b1784eac Mon Sep 17 00:00:00 2001 From: szerdick Date: Mon, 11 May 2026 00:17:47 +0200 Subject: [PATCH 11/33] add exp_polynomial csv file --- Snakefile | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/Snakefile b/Snakefile index ed4b303e..2bdddf89 100644 --- a/Snakefile +++ b/Snakefile @@ -426,6 +426,14 @@ rule exp_macro: input: "results/kernels.exp_macro.csv" +rule exp_polynomial: + input: + "results/kernels.exp_polynomial.csv" + +rule softmax_polynomial: + input: + "results/kernels.softmax_polynomial.csv" + rule all: input: "results/kernels.all.csv", From 23cac104e5b165e21500cb3918e637132e861f8c Mon Sep 17 00:00:00 2001 From: szerdick Date: Wed, 13 May 2026 17:07:49 +0200 Subject: [PATCH 12/33] remove softmax rule from the next pr --- Snakefile | 4 ---- 1 file changed, 4 deletions(-) diff --git a/Snakefile b/Snakefile index 2bdddf89..bb71f80e 100644 --- a/Snakefile +++ b/Snakefile @@ -430,10 +430,6 @@ rule exp_polynomial: input: "results/kernels.exp_polynomial.csv" -rule softmax_polynomial: - input: - "results/kernels.softmax_polynomial.csv" - rule all: input: "results/kernels.all.csv", From 34ce014f48c795855406e575da0904a645d2589d Mon Sep 17 00:00:00 2001 From: szerdick Date: Sun, 10 May 2026 23:41:20 +0200 Subject: [PATCH 13/33] import softmax-mia kernel from szerdick/softmax-to-exp-to-polynomial-to-arith --- kernels/softmax-mia/data.h.template | 30 +++++++++++ kernels/softmax-mia/gendata.py | 34 +++++++++++++ kernels/softmax-mia/linalg.mlir.template | 17 +++++++ kernels/softmax-mia/main.c | 60 ++++++++++++++++++++++ kernels/softmax-mia/softmax.c | 65 ++++++++++++++++++++++++ 5 files changed, 206 insertions(+) create mode 100644 kernels/softmax-mia/data.h.template create mode 100644 kernels/softmax-mia/gendata.py create mode 100644 kernels/softmax-mia/linalg.mlir.template create mode 100644 kernels/softmax-mia/main.c create mode 100644 kernels/softmax-mia/softmax.c diff --git a/kernels/softmax-mia/data.h.template b/kernels/softmax-mia/data.h.template new file mode 100644 index 00000000..c36eedaf --- /dev/null +++ b/kernels/softmax-mia/data.h.template @@ -0,0 +1,30 @@ +#pragma once + +#define PRECISION {{precision}} +#if PRECISION == 16 +#define DTYPE _Float16 +#define FABSF fabsf +#elif PRECISION == 32 +#define DTYPE float +#define FABSF fabsf +#elif PRECISION == 64 +#define DTYPE double +#define FABSF fabs +#else +#error Unsupported precision +#endif + +#define N {{N}} +#define ACC_EXP {{acc_exp}} +#define ACC_BOUND 1e-{{acc_exp}} + +#ifdef __cplusplus +extern "C" { +#endif + +extern const DTYPE X[N]; +extern const DTYPE G[N]; + +#ifdef __cplusplus +} +#endif diff --git a/kernels/softmax-mia/gendata.py b/kernels/softmax-mia/gendata.py new file mode 100644 index 00000000..3ea9586f --- /dev/null +++ b/kernels/softmax-mia/gendata.py @@ -0,0 +1,34 @@ +#!/usr/bin/env python3 + +import numpy as np +from typing import Iterator + +from gendatautils import main, Define, Array + + +def softmax_data( + N: int, acc_exp: int, rmin: float, rmax: float, precision: int +) -> Iterator[Define | Array]: + yield Define("N", N) + yield Define("ACC_EXP", acc_exp) + + t = {16: np.float16, 32: np.float32, 64: np.float64}[precision] + + # Clamp to a range that yields a numerically reasonable softmax + # (also keeps the polynomial exp approximation in its accurate region). + rmin = max(rmin, -1.0) + rmax = min(rmax, 1.0) + + np.random.seed(0) + x = np.random.uniform(rmin, rmax, N).astype(t) + + x64 = x.astype(np.float64) + e = np.exp(x64 - np.max(x64)) + g = (e / e.sum()).astype(t) + + yield Array("X", ("N",), x) + yield Array("G", ("N",), g) + + +if __name__ == "__main__": + main(softmax_data) diff --git a/kernels/softmax-mia/linalg.mlir.template b/kernels/softmax-mia/linalg.mlir.template new file mode 100644 index 00000000..b0e99dca --- /dev/null +++ b/kernels/softmax-mia/linalg.mlir.template @@ -0,0 +1,17 @@ +module { + func.func public @exp_kernel( + %arg0: memref<{{N}}xf{{precision}}> {llvm.noalias}, + %arg1: memref<{{N}}xf{{precision}}> {llvm.noalias}) -> memref<{{N}}xf{{precision}}> { + linalg.generic { + indexing_maps = [ + affine_map<(d0) -> (d0)>, + affine_map<(d0) -> (d0)>], + iterator_types = ["parallel"] + } ins(%arg0 : memref<{{N}}xf{{precision}}>) outs(%arg1 : memref<{{N}}xf{{precision}}>) { + ^bb0(%in: f{{precision}}, %out: f{{precision}}): + %0 = math.exp %in {acc_bound = {{f"{10**(-acc_exp):.6e}"}} : f{{precision}}} : f{{precision}} + linalg.yield %0 : f{{precision}} + } + return %arg1 : memref<{{N}}xf{{precision}}> + } +} diff --git a/kernels/softmax-mia/main.c b/kernels/softmax-mia/main.c new file mode 100644 index 00000000..624dcae5 --- /dev/null +++ b/kernels/softmax-mia/main.c @@ -0,0 +1,60 @@ +#include "data.h" + +#include + +#include + +#include + +extern "C" { + void *_sbrk(ptrdiff_t incr) { (void)incr; return (void *)-1; } + int _read(int fd, void *buf, size_t count) { (void)fd; (void)buf; (void)count; return -1; } + int _write(int fd, const void *buf, size_t count) { (void)fd; (void)buf; (void)count; return -1; } + int _lseek(int fd, long offset, int whence) { (void)fd; (void)offset; (void)whence; return -1; } + int _close(int fd) { (void)fd; return -1; } +} + +// Kernel provided via external definition +extern "C" void softmax_kernel(const DTYPE *x, DTYPE *z); + +int main() { + // Allocate shared local memory + // By avoiding allocators and bumping by a known offset a base pointer + // (snrt_l1_next()) that is the same for all the cores in the cluster, we are + // essentially providing the same memory regions to all the cores in this cluster. + DTYPE *local_x = (DTYPE *)snrt_l1_next(); + DTYPE *local_z = local_x + N; + + // Copy data in shared local memory + if (snrt_is_dm_core()) { + snrt_dma_start_1d((uint64_t)local_x, (uint64_t)X, N * sizeof(DTYPE)); + snrt_dma_wait_all(); + } + + snrt_cluster_hw_barrier(); + + // Launch kernel: from this point on only core 0 is required to be alive. + int thiscore = snrt_cluster_core_idx(); + if (thiscore != 0) return 0; + + snrt_fpu_fence(); + (void)snrt_mcycle(); + softmax_kernel(local_x, local_z); + snrt_fpu_fence(); + (void)snrt_mcycle(); + + // Correctness check. Tolerance is scaled by ACC_BOUND (= 10^-ACC_EXP) + // with a 20x margin to allow for finite-precision accumulation on top + // of the polynomial approximation error. + DTYPE tol_base = (DTYPE)(20.0 * ACC_BOUND); + int nerr = 0; + for (int i = 0; i < N; i++) { + printf("x[%d] = %f, G[%d] = %f, z[%d] = %f\n", i, (double)local_x[i], i, (double)G[i], i, (double)local_z[i]); + DTYPE d = FABSF(local_z[i] - G[i]); + DTYPE ref = FABSF(G[i]); + // Use relative error for large values, absolute for small + DTYPE tol = ref > (DTYPE)1.0 ? ref * tol_base : tol_base; + nerr += !(d <= tol); + } + return nerr; +} \ No newline at end of file diff --git a/kernels/softmax-mia/softmax.c b/kernels/softmax-mia/softmax.c new file mode 100644 index 00000000..f681b0c3 --- /dev/null +++ b/kernels/softmax-mia/softmax.c @@ -0,0 +1,65 @@ +#include "data.h" + +#ifdef __cplusplus +extern "C" { +#endif + +// Element-wise exp; provided by the MLIR/xDSL pipeline (linalg.mlir.template +// produces this symbol after xDSL lowering passes). +extern void exp_kernel(const DTYPE *x, DTYPE *z); + +#if PRECISION == 16 +// snitch-llvm -mno-fdiv only emulates fdiv.s/.d; fdiv.h still traps +// (DIVSQRT disabled on this cluster). -ffast-math also folds +// (_Float16)(1.0f / (float)s) back into a single fdiv.h, so we need an +// opaque call the optimizer can't see through. __divsf3 is provided by +// clang_rt.builtins-riscv32 (linked via ldflags). +extern float __divsf3(float, float); +#endif + +// Step 1: max over x[0..N). +static DTYPE softmax_max(const DTYPE *x) { + DTYPE m = x[0]; + for (int i = 1; i < N; i++) { + if (x[i] > m) m = x[i]; + } + return m; +} + +// Step 2: e[i] = exp(x[i] - m); returns sum(e). +// Subtraction is done in C, the elementwise exp goes through the extern +// kernel so xDSL can lower it. exp_kernel(e, e) is safe because each +// output element only depends on the corresponding input element. +static DTYPE softmax_exp_sum(const DTYPE *x, DTYPE m, DTYPE *e) { + for (int i = 0; i < N; i++) { + e[i] = x[i] - m; + } + exp_kernel(e, e); + DTYPE s = (DTYPE)0; + for (int i = 0; i < N; i++) { + s += e[i]; + } + return s; +} + +// Step 3: e[i] /= sum. +static void softmax_normalize(DTYPE *e, DTYPE inv_sum) { + for (int i = 0; i < N; i++) { + e[i] *= inv_sum; + } +} + +void softmax_kernel(const DTYPE *x, DTYPE *z) { + DTYPE m = softmax_max(x); + DTYPE s = softmax_exp_sum(x, m, z); +#if PRECISION == 16 + DTYPE inv_s = (DTYPE)__divsf3(1.0f, (float)s); +#else + DTYPE inv_s = (DTYPE)1.0 / s; // fdiv is emulated only once +#endif + softmax_normalize(z, inv_s); +} + +#ifdef __cplusplus +} +#endif From 017eb69dbfbe81e12b4d1b6d75ab6b818578513f Mon Sep 17 00:00:00 2001 From: szerdick Date: Sun, 10 May 2026 23:58:38 +0200 Subject: [PATCH 14/33] add softmax to snakefile --- Snakefile | 49 ++++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 46 insertions(+), 3 deletions(-) diff --git a/Snakefile b/Snakefile index bb71f80e..1650e3e9 100644 --- a/Snakefile +++ b/Snakefile @@ -101,6 +101,7 @@ KERNEL_SHAPE = { "exp_micro": SHAPE_1D, "exp_macro": SHAPE_1D, "exp_polynomial": SHAPE_1D, + "softmax-mia": SHAPE_1D, "sum": SHAPE_2D, "relu": SHAPE_2D, "fill": SHAPE_2D, @@ -295,6 +296,15 @@ TESTSET_EXP_MACRO = [ ), ] +TESTSET_SOFTMAX_MIA = [ + *expand( + "softmax-mia/{N}xf{precision}/{variant}", + N=range(16, 129, 16), + precision=[16, 32, 64], + variant=XDSL_LINALG_ACC_BOUND_VARIANTS, + ), +] + # Full set. Contains all tests needed by plots in the paper. Beware: it's huge. TESTSET_ALL = [ *MANUAL_KERNELS, @@ -303,6 +313,7 @@ TESTSET_ALL = [ *TESTSET_EXP_MICRO, *TESTSET_EXP_MACRO, *TESTSET_EXP_POLYNOMIAL, + *TESTSET_SOFTMAX_MIA, # 3d templated kernels: baseline + linalg_xdsl *expand( "matmul/{M}x{K}x{N}xf64/{variant}", @@ -352,6 +363,7 @@ def select_test_set_profiles(wildcards) -> list[str]: "pipeline": sorted(set(TESTSET_PIPELINE)), "exp_micro": sorted(set(TESTSET_EXP_MICRO)), "exp_macro": sorted(set(TESTSET_EXP_MACRO)), + "softmax_mia": sorted(set(TESTSET_SOFTMAX_MIA)), } name = wildcards.testset if name not in sets: @@ -368,6 +380,7 @@ def select_test_set_regalloc_jsons(wildcards) -> list[str]: "pipeline": sorted(set(TESTSET_PIPELINE)), "exp_micro": sorted(set(TESTSET_EXP_MICRO)), "exp_macro": sorted(set(TESTSET_EXP_MACRO)), + "softmax_mia": sorted(set(TESTSET_SOFTMAX_MIA)), } name = wildcards.testset if name not in sets: @@ -430,6 +443,10 @@ rule exp_polynomial: input: "results/kernels.exp_polynomial.csv" +rule softmax_mia: + input: + "results/kernels.softmax_mia.csv" + rule all: input: "results/kernels.all.csv", @@ -601,11 +618,22 @@ rule optimization_pipelines: # Build rules +def cc_link_inputs(wildcards): + base = [ + f"kernels/{wildcards.kernel}/{wildcards.shape}/{wildcards.variant}.o", + f"kernels/{wildcards.kernel}/{wildcards.shape}/data.o", + f"kernels/{wildcards.kernel}/{wildcards.shape}/main.o", + ] + # softmax-mia ships an extra translation unit (softmax.c at the kernel + # root) that drives the xDSL-lowered exp_kernel. + if wildcards.kernel == "softmax-mia": + base.append(f"kernels/{wildcards.kernel}/{wildcards.shape}/softmax.o") + return base + + rule cc_link: input: - "kernels/{kernel}/{shape}/{variant}.o", - "kernels/{kernel}/{shape}/data.o", - "kernels/{kernel}/{shape}/main.o", + cc_link_inputs, output: "kernels/{kernel}/{shape}/{variant}.x", params: @@ -742,6 +770,21 @@ rule cc_compile_shared_main: "{params.cc} -I$(dirname {input.h}) {params.cflags} -S -x c++ -o {output} {input.c}" +rule cc_compile_shared_softmax: + input: + c="kernels/{kernel}/softmax.c", + h="kernels/{kernel}/{shape}/data.h", + output: + "kernels/{kernel}/{shape}/softmax.S", + wildcard_constraints: + kernel="softmax-mia", + params: + cc=config["cc"], + cflags=config["cflags"], + shell: + "{params.cc} -I$(dirname {input.h}) {params.cflags} -S -x c++ -o {output} {input.c}" + + ########################################################### # Sources/data generation rules, restricted to templated # kernels only From 8a97a663d1c0b9ba557056e96eb4014c205262d4 Mon Sep 17 00:00:00 2001 From: szerdick Date: Mon, 11 May 2026 00:15:14 +0200 Subject: [PATCH 15/33] renaming --- Snakefile | 22 +++++++++---------- .../data.h.template | 2 -- .../gendata.py | 3 +-- .../linalg.mlir.template | 2 +- .../main.c | 8 ++----- .../softmax.c | 0 6 files changed, 14 insertions(+), 23 deletions(-) rename kernels/{softmax-mia => softmax_polynomial}/data.h.template (87%) rename kernels/{softmax-mia => softmax_polynomial}/gendata.py (87%) rename kernels/{softmax-mia => softmax_polynomial}/linalg.mlir.template (85%) rename kernels/{softmax-mia => softmax_polynomial}/main.c (82%) rename kernels/{softmax-mia => softmax_polynomial}/softmax.c (100%) diff --git a/Snakefile b/Snakefile index 1650e3e9..bb821aef 100644 --- a/Snakefile +++ b/Snakefile @@ -101,7 +101,7 @@ KERNEL_SHAPE = { "exp_micro": SHAPE_1D, "exp_macro": SHAPE_1D, "exp_polynomial": SHAPE_1D, - "softmax-mia": SHAPE_1D, + "softmax_polynomial": SHAPE_1D, "sum": SHAPE_2D, "relu": SHAPE_2D, "fill": SHAPE_2D, @@ -296,9 +296,9 @@ TESTSET_EXP_MACRO = [ ), ] -TESTSET_SOFTMAX_MIA = [ +TESTSET_SOFTMAX_POLYNOMIAL = [ *expand( - "softmax-mia/{N}xf{precision}/{variant}", + "softmax_polynomial/{N}xf{precision}/{variant}", N=range(16, 129, 16), precision=[16, 32, 64], variant=XDSL_LINALG_ACC_BOUND_VARIANTS, @@ -313,7 +313,7 @@ TESTSET_ALL = [ *TESTSET_EXP_MICRO, *TESTSET_EXP_MACRO, *TESTSET_EXP_POLYNOMIAL, - *TESTSET_SOFTMAX_MIA, + *TESTSET_SOFTMAX_POLYNOMIAL, # 3d templated kernels: baseline + linalg_xdsl *expand( "matmul/{M}x{K}x{N}xf64/{variant}", @@ -363,7 +363,7 @@ def select_test_set_profiles(wildcards) -> list[str]: "pipeline": sorted(set(TESTSET_PIPELINE)), "exp_micro": sorted(set(TESTSET_EXP_MICRO)), "exp_macro": sorted(set(TESTSET_EXP_MACRO)), - "softmax_mia": sorted(set(TESTSET_SOFTMAX_MIA)), + "softmax_polynomial": sorted(set(TESTSET_SOFTMAX_POLYNOMIAL)), } name = wildcards.testset if name not in sets: @@ -380,7 +380,7 @@ def select_test_set_regalloc_jsons(wildcards) -> list[str]: "pipeline": sorted(set(TESTSET_PIPELINE)), "exp_micro": sorted(set(TESTSET_EXP_MICRO)), "exp_macro": sorted(set(TESTSET_EXP_MACRO)), - "softmax_mia": sorted(set(TESTSET_SOFTMAX_MIA)), + "softmax_polynomial": sorted(set(TESTSET_SOFTMAX_POLYNOMIAL)), } name = wildcards.testset if name not in sets: @@ -443,9 +443,9 @@ rule exp_polynomial: input: "results/kernels.exp_polynomial.csv" -rule softmax_mia: +rule softmax_polynomial: input: - "results/kernels.softmax_mia.csv" + "results/kernels.softmax_polynomial.csv" rule all: input: @@ -624,9 +624,7 @@ def cc_link_inputs(wildcards): f"kernels/{wildcards.kernel}/{wildcards.shape}/data.o", f"kernels/{wildcards.kernel}/{wildcards.shape}/main.o", ] - # softmax-mia ships an extra translation unit (softmax.c at the kernel - # root) that drives the xDSL-lowered exp_kernel. - if wildcards.kernel == "softmax-mia": + if wildcards.kernel == "softmax-polynomial": base.append(f"kernels/{wildcards.kernel}/{wildcards.shape}/softmax.o") return base @@ -777,7 +775,7 @@ rule cc_compile_shared_softmax: output: "kernels/{kernel}/{shape}/softmax.S", wildcard_constraints: - kernel="softmax-mia", + kernel="softmax-polynomial", params: cc=config["cc"], cflags=config["cflags"], diff --git a/kernels/softmax-mia/data.h.template b/kernels/softmax_polynomial/data.h.template similarity index 87% rename from kernels/softmax-mia/data.h.template rename to kernels/softmax_polynomial/data.h.template index c36eedaf..a0505e53 100644 --- a/kernels/softmax-mia/data.h.template +++ b/kernels/softmax_polynomial/data.h.template @@ -15,8 +15,6 @@ #endif #define N {{N}} -#define ACC_EXP {{acc_exp}} -#define ACC_BOUND 1e-{{acc_exp}} #ifdef __cplusplus extern "C" { diff --git a/kernels/softmax-mia/gendata.py b/kernels/softmax_polynomial/gendata.py similarity index 87% rename from kernels/softmax-mia/gendata.py rename to kernels/softmax_polynomial/gendata.py index 3ea9586f..f8d96125 100644 --- a/kernels/softmax-mia/gendata.py +++ b/kernels/softmax_polynomial/gendata.py @@ -7,10 +7,9 @@ def softmax_data( - N: int, acc_exp: int, rmin: float, rmax: float, precision: int + N: int, rmin: float, rmax: float, precision: int ) -> Iterator[Define | Array]: yield Define("N", N) - yield Define("ACC_EXP", acc_exp) t = {16: np.float16, 32: np.float32, 64: np.float64}[precision] diff --git a/kernels/softmax-mia/linalg.mlir.template b/kernels/softmax_polynomial/linalg.mlir.template similarity index 85% rename from kernels/softmax-mia/linalg.mlir.template rename to kernels/softmax_polynomial/linalg.mlir.template index b0e99dca..41de3c54 100644 --- a/kernels/softmax-mia/linalg.mlir.template +++ b/kernels/softmax_polynomial/linalg.mlir.template @@ -9,7 +9,7 @@ module { iterator_types = ["parallel"] } ins(%arg0 : memref<{{N}}xf{{precision}}>) outs(%arg1 : memref<{{N}}xf{{precision}}>) { ^bb0(%in: f{{precision}}, %out: f{{precision}}): - %0 = math.exp %in {acc_bound = {{f"{10**(-acc_exp):.6e}"}} : f{{precision}}} : f{{precision}} + %0 = math.exp %in : f{{precision}} linalg.yield %0 : f{{precision}} } return %arg1 : memref<{{N}}xf{{precision}}> diff --git a/kernels/softmax-mia/main.c b/kernels/softmax_polynomial/main.c similarity index 82% rename from kernels/softmax-mia/main.c rename to kernels/softmax_polynomial/main.c index 624dcae5..8476b400 100644 --- a/kernels/softmax-mia/main.c +++ b/kernels/softmax_polynomial/main.c @@ -43,17 +43,13 @@ int main() { snrt_fpu_fence(); (void)snrt_mcycle(); - // Correctness check. Tolerance is scaled by ACC_BOUND (= 10^-ACC_EXP) - // with a 20x margin to allow for finite-precision accumulation on top - // of the polynomial approximation error. - DTYPE tol_base = (DTYPE)(20.0 * ACC_BOUND); + // Correctness check int nerr = 0; for (int i = 0; i < N; i++) { printf("x[%d] = %f, G[%d] = %f, z[%d] = %f\n", i, (double)local_x[i], i, (double)G[i], i, (double)local_z[i]); DTYPE d = FABSF(local_z[i] - G[i]); DTYPE ref = FABSF(G[i]); - // Use relative error for large values, absolute for small - DTYPE tol = ref > (DTYPE)1.0 ? ref * tol_base : tol_base; + DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)2E-1 : (DTYPE)2E-1; nerr += !(d <= tol); } return nerr; diff --git a/kernels/softmax-mia/softmax.c b/kernels/softmax_polynomial/softmax.c similarity index 100% rename from kernels/softmax-mia/softmax.c rename to kernels/softmax_polynomial/softmax.c From 7fb3bba2b9068bef9fbedca6e2e00c7acda9bc52 Mon Sep 17 00:00:00 2001 From: szerdick Date: Mon, 11 May 2026 00:16:33 +0200 Subject: [PATCH 16/33] edit makefile and delete print statements --- Makefile | 4 ++++ kernels/softmax_polynomial/main.c | 1 - 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/Makefile b/Makefile index c930c016..a76330a9 100644 --- a/Makefile +++ b/Makefile @@ -42,6 +42,10 @@ exp_macro: exp: snakemake --cores $(JOBS) --rerun-incomplete exp_micro exp_macro exp_polynomial +.PHONY: softmax_polynomial +softmax_polynomial: + snakemake --cores $(JOBS) --rerun-incomplete softmax_polynomial + .PHONY: clean clean: snakemake --delete-all-output --rerun-incomplete fast all pipeline low_level_representation exp_micro exp_macro exp_polynomial diff --git a/kernels/softmax_polynomial/main.c b/kernels/softmax_polynomial/main.c index 8476b400..e39612a6 100644 --- a/kernels/softmax_polynomial/main.c +++ b/kernels/softmax_polynomial/main.c @@ -46,7 +46,6 @@ int main() { // Correctness check int nerr = 0; for (int i = 0; i < N; i++) { - printf("x[%d] = %f, G[%d] = %f, z[%d] = %f\n", i, (double)local_x[i], i, (double)G[i], i, (double)local_z[i]); DTYPE d = FABSF(local_z[i] - G[i]); DTYPE ref = FABSF(G[i]); DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)2E-1 : (DTYPE)2E-1; From 9091950f88570f83ac254d9239d72a6b0633bff4 Mon Sep 17 00:00:00 2001 From: Mia Sophie Zerdick Date: Thu, 14 May 2026 17:20:52 +0100 Subject: [PATCH 17/33] safe variants for f16 --- Snakefile | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/Snakefile b/Snakefile index bb821aef..49a6e56c 100644 --- a/Snakefile +++ b/Snakefile @@ -297,11 +297,16 @@ TESTSET_EXP_MACRO = [ ] TESTSET_SOFTMAX_POLYNOMIAL = [ + *expand( + "softmax_polynomial/{N}xf16/{variant}", + N=range(16, 129, 16), + variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16, + ), *expand( "softmax_polynomial/{N}xf{precision}/{variant}", N=range(16, 129, 16), - precision=[16, 32, 64], - variant=XDSL_LINALG_ACC_BOUND_VARIANTS, + precision=[32, 64], + variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS, ), ] From 6531808071d0eb4ffbc533eb384fb879eb7b9cee Mon Sep 17 00:00:00 2001 From: szerdick Date: Tue, 12 May 2026 11:24:20 +0200 Subject: [PATCH 18/33] new plots for thesis, reran tests and add command to generate in snakemake --- Snakefile | 18 ++- kernels/exp_polynomial/main.c | 2 +- plots-mia-thesis/output/rq1_plots.pdf | Bin 0 -> 23351 bytes plots-mia-thesis/plot_rq1.py | 137 +++++++++++++++++++++ results/kernels.exp_polynomial.csv | 166 ++++++++++++++++++++++++++ 5 files changed, 320 insertions(+), 3 deletions(-) create mode 100644 plots-mia-thesis/output/rq1_plots.pdf create mode 100644 plots-mia-thesis/plot_rq1.py create mode 100644 results/kernels.exp_polynomial.csv diff --git a/Snakefile b/Snakefile index 49a6e56c..7cb45d2e 100644 --- a/Snakefile +++ b/Snakefile @@ -282,7 +282,7 @@ TESTSET_EXP_POLYNOMIAL = [ *expand( "exp_polynomial/{N}xf{precision}/{variant}", N=range(64, 129, 16), - precision=[616, 32, 4], + precision=[16, 32, 64], variant=XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS, ), ] @@ -368,6 +368,7 @@ def select_test_set_profiles(wildcards) -> list[str]: "pipeline": sorted(set(TESTSET_PIPELINE)), "exp_micro": sorted(set(TESTSET_EXP_MICRO)), "exp_macro": sorted(set(TESTSET_EXP_MACRO)), + "exp_polynomial": sorted(set(TESTSET_EXP_POLYNOMIAL)), "softmax_polynomial": sorted(set(TESTSET_SOFTMAX_POLYNOMIAL)), } name = wildcards.testset @@ -385,6 +386,7 @@ def select_test_set_regalloc_jsons(wildcards) -> list[str]: "pipeline": sorted(set(TESTSET_PIPELINE)), "exp_micro": sorted(set(TESTSET_EXP_MICRO)), "exp_macro": sorted(set(TESTSET_EXP_MACRO)), + "exp_polynomial": sorted(set(TESTSET_EXP_POLYNOMIAL)), "softmax_polynomial": sorted(set(TESTSET_SOFTMAX_POLYNOMIAL)), } name = wildcards.testset @@ -446,7 +448,19 @@ rule exp_macro: rule exp_polynomial: input: - "results/kernels.exp_polynomial.csv" + "results/kernels.exp_polynomial.csv", + "plots-mia-thesis/output/rq1_plots.pdf", + + +rule plot_rq1: + input: + micro="results/kernels.exp_micro.csv", + poly="results/kernels.exp_polynomial.csv", + script="plots-mia-thesis/plot_rq1.py", + output: + "plots-mia-thesis/output/rq1_plots.pdf", + shell: + "python {input.script} --exp-micro {input.micro} --exp-polynomial {input.poly} -o {output}" rule softmax_polynomial: input: diff --git a/kernels/exp_polynomial/main.c b/kernels/exp_polynomial/main.c index 975ffbbd..7a367c6e 100644 --- a/kernels/exp_polynomial/main.c +++ b/kernels/exp_polynomial/main.c @@ -46,7 +46,7 @@ int main() { // Correctness check. int nerr = 0; for (int i = 0; i < N; i++) { - printf("x[%d] = %f, G[%d] = %f, z[%d] = %f\n", i, local_x[i], i, G[i], i, local_z[i]); + // printf("x[%d] = %f, G[%d] = %f, z[%d] = %f\n", i, local_x[i], i, G[i], i, local_z[i]); DTYPE d = FABSF(local_z[i] - G[i]); DTYPE ref = FABSF(G[i]); DTYPE tol = ref > (DTYPE)1.0 ? ref * (DTYPE)2E-1 : (DTYPE)2E-1; diff --git a/plots-mia-thesis/output/rq1_plots.pdf b/plots-mia-thesis/output/rq1_plots.pdf new file mode 100644 index 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z5di_Gf4=d%xZ85!2>^b*m6s)OG3d|PT&-+C7Uq^$fNFje0g#?lVDI8Ahq^-byqpLW z39DrpupnuX(vm)vb1FQ<=A^esGF!OsF zu)y}aT>(o+C{Nrn` z;HCdA8x-hpKk?$}Zf@^r?S68>wT`{-w-rlm7Z=pve&R7GJKMN`P6qcAugk;J+}-nJ SNQFX>LJ&N5c6kj2y#EIy_3Ix1 literal 0 HcmV?d00001 diff --git a/plots-mia-thesis/plot_rq1.py b/plots-mia-thesis/plot_rq1.py new file mode 100644 index 00000000..9da55e6a --- /dev/null +++ b/plots-mia-thesis/plot_rq1.py @@ -0,0 +1,137 @@ +#!/usr/bin/env python3 +""" +RQ1 plot: how does the Chebyshev polynomial degree affect cycles/byte and FPU +utilization of the xDSL polynomial pipeline, compared to the libm baseline? + +For each precision (f16, f32, f64) produce two plots: + - degree vs. avg cycles/byte (averaged across input sizes N) + - degree vs. avg FPU utilization (averaged across input sizes N) +The libm baseline (from exp_micro) is drawn as a horizontal reference line. + +Usage: + python plot_rq1.py \ + [--exp-micro results/kernels.exp_micro.csv] \ + [--exp-polynomial results/kernels.exp_polynomial.csv] \ + [--output output/rq1_plots.pdf] +""" + +import argparse +import re +from pathlib import Path + +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt + +from plot_utils import savefig + + +PRECISION_BYTES = {"f16": 2, "f32": 4, "f64": 8} +PRECISIONS = ["f16", "f32", "f64"] +DEGREE_RE = re.compile(r"linalg_xdsl_d(\d+)$") + + +def _annotate(df: pd.DataFrame) -> pd.DataFrame: + parts = df["params"].str.split("x") + df = df.copy() + df["precision"] = parts.str[-1] + df["total_elements"] = parts.apply(lambda ps: int(np.prod([int(p) for p in ps[:-1]]))) + df["total_input_bytes"] = df.apply( + lambda r: r["total_elements"] * PRECISION_BYTES[r["precision"]], axis=1 + ) + df["cycles_per_byte"] = df["cycles"] / df["total_input_bytes"] + return df + + +def load_polynomial(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"].str.match(DEGREE_RE)].copy() + df["degree"] = df["impl"].str.extract(DEGREE_RE).astype(int) + return _annotate(df) + + +def load_micro_baseline(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"] == "baseline"].copy() + return _annotate(df) + + +def avg_per_degree(df: pd.DataFrame, precision: str, metric: str) -> pd.DataFrame: + return ( + df[df["precision"] == precision] + .groupby("degree")[metric] + .mean() + .sort_index() + ) + + +def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: + return df.loc[df["precision"] == precision, metric].mean() + + +def plot_rq1(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: + fig, axes = plt.subplots(2, len(PRECISIONS), figsize=(len(PRECISIONS) * 5, 8)) + + metrics = [ + ("cycles_per_byte", "Avg cycles / byte"), + ("fpss_fpu_occupancy", "Avg FPU utilization"), + ] + + for row_idx, (metric, ylabel) in enumerate(metrics): + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[row_idx, col_idx] + series = avg_per_degree(poly_df, precision, metric) + baseline = avg_baseline(baseline_df, precision, metric) + + if not series.empty: + ax.plot( + series.index, series.values, + marker="o", linestyle="none", color="#33a02c", + label="Chebyshev polynomial", + ) + if not np.isnan(baseline): + ax.axhline( + baseline, color="#1f78b4", linestyle="--", + label=f"libm baseline ({baseline:.3g})", + ) + + ax.set_title(f"{precision}") + ax.set_xlabel("Chebyshev degree") + ax.set_ylabel(ylabel) + if not series.empty: + ax.set_xticks(series.index) + ax.grid(True, alpha=0.3) + ax.legend(loc="best", fontsize=8) + + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--exp-micro", default="results/kernels.exp_micro.csv", + help="Input CSV with libm baseline measurements", + ) + parser.add_argument( + "--exp-polynomial", default="results/kernels.exp_polynomial.csv", + help="Input CSV with Chebyshev polynomial degree-variant measurements", + ) + parser.add_argument( + "--output", "-o", default="plots-mia-thesis/output/rq1_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + + poly_df = load_polynomial(args.exp_polynomial) + baseline_df = load_micro_baseline(args.exp_micro) + + fig = plot_rq1(poly_df, baseline_df) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/results/kernels.exp_polynomial.csv b/results/kernels.exp_polynomial.csv new file mode 100644 index 00000000..72242e69 --- /dev/null +++ b/results/kernels.exp_polynomial.csv @@ -0,0 +1,166 @@ +test,params,impl,cycles,end,end_fpss,fpss_avg_fpu_latency,fpss_avg_load_latency,fpss_fpu_fmadd_issues,fpss_fpu_issues,fpss_fpu_latency,fpss_fpu_occupancy,fpss_fpu_rel_occupancy,fpss_issues,fpss_load_latency,fpss_loads,fpss_occupancy,fpss_section_latency,fpss_stores,fseq_fpu_yield,fseq_yield,section,snitch_avg_load_latency,snitch_fseq_offloads,snitch_fseq_rel_offloads,snitch_issues,snitch_load_latency,snitch_loads,snitch_occupancy,snitch_stores,start,tend,total_ipc,tstart +exp_polynomial,112xf16,linalg_xdsl_d10,4764,6800,6796,0.0,0,0,1009,0,0.2117968094038623,0.6915695681973955,1459,0,0,0.306255247691016,0,0,1.0,1.0,1,0,1459,0.3923097606883571,2260,0,0,0.47439126784214947,896,2037,6804,0.7806465155331654,2039 +exp_polynomial,112xf16,linalg_xdsl_d11,5105,7182,7178,0.0,0,0,1093,0,0.21410381978452497,0.6957352005092298,1571,0,0,0.30773751224289914,0,0,1.0,1.0,1,0,1571,0.40416773861589916,2316,0,0,0.4536728697355534,952,2078,7186,0.7614103819784526,2080 +exp_polynomial,112xf16,linalg_xdsl_d12,5436,7516,7512,0.0,0,0,1177,0,0.21651949963208242,0.6993464052287581,1683,0,0,0.30960264900662254,0,0,1.0,1.0,1,0,1683,0.4150431565967941,2372,0,0,0.43635025754231055,1008,2081,7520,0.7459529065489331,2083 +exp_polynomial,112xf16,linalg_xdsl_d2,2132,4186,4182,0.0,0,0,337,0,0.15806754221388367,0.5985790408525755,563,0,0,0.26407129455909945,0,0,1.0,1.0,1,0,563,0.3305930710510863,1140,0,0,0.5347091932457786,448,2055,4190,0.7987804878048781,2057 +exp_polynomial,112xf16,linalg_xdsl_d3,2477,4496,4492,0.0,0,0,421,0,0.16996366572466692,0.6237037037037036,675,0,0,0.27250706499798144,0,0,1.0,1.0,1,0,675,0.340393343419062,1308,0,0,0.5280581348405329,504,2020,4500,0.8005651998385144,2022 +exp_polynomial,112xf16,linalg_xdsl_d4,2804,4884,4880,0.0,0,0,505,0,0.18009985734664766,0.6416772554002541,787,0,0,0.2806704707560628,0,0,1.0,1.0,1,0,787,0.34776844896155545,1476,0,0,0.5263908701854494,560,2081,4888,0.8070613409415122,2083 +exp_polynomial,112xf16,linalg_xdsl_d5,3145,5222,5218,0.0,0,0,589,0,0.18728139904610494,0.6551724137931034,899,0,0,0.28585055643879176,0,0,1.0,1.0,1,0,899,0.35351946519858435,1644,0,0,0.5227344992050874,616,2078,5226,0.8085850556438792,2080 +exp_polynomial,112xf16,linalg_xdsl_d6,3476,5512,5508,0.0,0,0,673,0,0.19361334867663982,0.6656775469831849,1011,0,0,0.29085155350978137,0,0,1.0,1.0,1,0,1011,0.35812964930924546,1812,0,0,0.5212888377445339,672,2037,5516,0.8121403912543153,2039 +exp_polynomial,112xf16,linalg_xdsl_d7,3812,5873,5869,0.0,0,0,757,0,0.19858342077649527,0.674087266251113,1123,0,0,0.29459601259181534,0,0,1.0,1.0,1,0,1123,0.36190783113116337,1980,0,0,0.5194123819517313,728,2062,5877,0.8140083945435467,2064 +exp_polynomial,112xf16,linalg_xdsl_d8,4155,6209,6205,0.0,0,0,841,0,0.20240673886883273,0.6809716599190283,1235,0,0,0.2972322503008424,0,0,1.0,1.0,1,0,1235,0.36506059710316285,2148,0,0,0.5169675090252708,784,2055,6213,0.8141997593261132,2057 +exp_polynomial,112xf16,linalg_xdsl_d9,4428,6489,6485,0.0,0,0,925,0,0.20889792231255647,0.6867112100965108,1347,0,0,0.30420054200542007,0,0,1.0,1.0,1,0,1347,0.3793297662630245,2204,0,0,0.4977416440831075,840,2062,6493,0.8019421860885276,2064 +exp_polynomial,112xf32,linalg_xdsl_d10,9557,11621,11617,0.0,0,0,2017,0,0.21104949251857277,0.6919382504288165,2915,0,0,0.30501203306476926,0,0,1.0,1.0,1,0,2915,0.3815944495352795,4724,0,0,0.49429737365281995,1792,2065,11625,0.7993094067175892,2067 +exp_polynomial,112xf32,linalg_xdsl_d11,10222,12309,12305,0.0,0,0,2185,0,0.2137546468401487,0.6960815546352341,3139,0,0,0.3070827626687537,0,0,1.0,1.0,1,0,3139,0.38285156726430053,5060,0,0,0.49501076110350223,1904,2088,12313,0.802093523772256,2090 +exp_polynomial,112xf32,linalg_xdsl_d12,10894,12939,12935,0.0,0,0,2353,0,0.2159904534606205,0.6996729110912875,3363,0,0,0.3087020378189829,0,0,1.0,1.0,1,0,3363,0.3839479392624729,5396,0,0,0.4953185239581421,2016,2046,12943,0.804020561777125,2048 +exp_polynomial,112xf32,linalg_xdsl_d2,4181,6245,6241,0.0,0,0,673,0,0.1609662760105238,0.5992876224398932,1123,0,0,0.2685960296579766,0,0,1.0,1.0,1,0,1123,0.35549224438113325,2036,0,0,0.4869648409471418,896,2065,6249,0.7555608706051185,2067 +exp_polynomial,112xf32,linalg_xdsl_d3,4846,6933,6929,0.0,0,0,841,0,0.17354519191085432,0.6243504083147736,1347,0,0,0.2779612051176228,0,0,1.0,1.0,1,0,1347,0.36219413820919605,2372,0,0,0.4894758563763929,1008,2088,6937,0.7674370614940157,2090 +exp_polynomial,112xf32,linalg_xdsl_d4,5518,7563,7559,0.0,0,0,1009,0,0.1828561072852483,0.642266072565245,1571,0,0,0.2847046031170714,0,0,1.0,1.0,1,0,1571,0.3671418555737322,2708,0,0,0.49075752084088436,1120,2046,7567,0.7754621239579558,2048 +exp_polynomial,112xf32,linalg_xdsl_d5,6199,8247,8243,0.0,0,0,1177,0,0.18986933376351026,0.6557103064066853,1795,0,0,0.28956283271495403,0,0,1.0,1.0,1,0,1795,0.3709444100020665,3044,0,0,0.49104694305533153,1232,2049,8251,0.7806097757702856,2051 +exp_polynomial,112xf32,linalg_xdsl_d6,6862,8932,8928,0.0,0,0,1345,0,0.19600699504517632,0.6661713719663199,2019,0,0,0.29422908772952494,0,0,1.0,1.0,1,0,2019,0.3739581403963697,3380,0,0,0.4925677645001457,1344,2071,8936,0.7867968522296707,2073 +exp_polynomial,112xf32,linalg_xdsl_d7,7539,9566,9562,0.0,0,0,1513,0,0.20068974665074943,0.6745430227374053,2243,0,0,0.2975195649290357,0,0,1.0,1.0,1,0,2243,0.37640543715388486,3716,0,0,0.49290356811248176,1456,2028,9570,0.7904231330415175,2030 +exp_polynomial,112xf32,linalg_xdsl_d8,8206,10251,10247,0.0,0,0,1681,0,0.20485010967584694,0.6813944061613295,2467,0,0,0.3006336826712162,0,0,1.0,1.0,1,0,2467,0.3784322748887866,4052,0,0,0.4937850353399951,1568,2046,10255,0.7944187180112113,2048 +exp_polynomial,112xf32,linalg_xdsl_d9,8878,10910,10906,0.0,0,0,1849,0,0.20826762784410904,0.6871051653660349,2691,0,0,0.30310880829015546,0,0,1.0,1.0,1,0,2691,0.38013843763243393,4388,0,0,0.4942554629421041,1680,2033,10914,0.7973642712322595,2035 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+exp_polynomial,96xf32,linalg_xdsl_d6,5886,7956,7952,0.0,0,0,1153,0,0.19588854909955827,0.6660889659156557,1731,0,0,0.29408766564729866,0,0,1.0,1.0,1,0,1731,0.37378535953357805,2900,0,0,0.4926945293917771,1152,2071,7960,0.7867821950390758,2073 +exp_polynomial,96xf32,linalg_xdsl_d7,6467,8494,8490,0.0,0,0,1297,0,0.2005566723364775,0.6744669786791472,1923,0,0,0.29735580640173187,0,0,1.0,1.0,1,0,1923,0.37624730972412446,3188,0,0,0.4929642801917427,1248,2028,8498,0.7903200865934745,2030 +exp_polynomial,96xf32,linalg_xdsl_d8,7038,9083,9079,0.0,0,0,1441,0,0.20474566638249503,0.6813238770685579,2115,0,0,0.30051150895140666,0,0,1.0,1.0,1,0,2115,0.3782865319263101,3476,0,0,0.49389030974708725,1344,2046,9087,0.7944018186984939,2048 +exp_polynomial,96xf32,linalg_xdsl_d9,7614,9646,9642,0.0,0,0,1585,0,0.2081691620698713,0.6870394451668834,2307,0,0,0.30299448384554767,0,0,1.0,1.0,1,0,2307,0.3800032943501894,3764,0,0,0.4943525085369057,1440,2033,9650,0.7973469923824534,2035 +exp_polynomial,96xf64,linalg_xdsl_d10,14338,16443,16439,0.0,0,0,3937,0,0.2745850188310783,0.7881881881881881,4995,0,0,0.3483749476914493,0,0,1.0,1.0,1,0,4995,0.4291605808059112,6644,0,0,0.46338401450690475,2112,2106,16447,0.8117589621983541,2108 +exp_polynomial,96xf64,linalg_xdsl_d11,15589,17722,17718,0.0,0,0,4225,0,0.27102444031047535,0.7854619817810002,5379,0,0,0.3450509974982359,0,0,1.0,1.0,1,0,5379,0.42053006019857714,7412,0,0,0.47546346782988,2304,2134,17726,0.820514465328116,2136 +exp_polynomial,96xf64,linalg_xdsl_d12,16543,18649,18645,0.0,0,0,4513,0,0.2728042072175543,0.7830990803401007,5763,0,0,0.3483648673154809,0,0,1.0,1.0,1,0,5763,0.4311363806388868,7604,0,0,0.4596506075077072,2496,2107,18653,0.808015474823188,2109 +exp_polynomial,96xf64,linalg_xdsl_d2,5216,7318,7314,0.0,0,0,1633,0,0.31307515337423314,0.8491939677587104,1923,0,0,0.3686733128834356,0,0,1.0,1.0,1,0,1923,0.47422934648582,2132,0,0,0.4087423312883436,576,2103,7322,0.7774156441717792,2105 +exp_polynomial,96xf64,linalg_xdsl_d3,6373,8506,8502,0.0,0,0,1921,0,0.30142789894868977,0.8326831382748158,2307,0,0,0.361995920288718,0,0,1.0,1.0,1,0,2307,0.45137937781256116,2804,0,0,0.439981170563314,768,2134,8510,0.8019770908520321,2136 +exp_polynomial,96xf64,linalg_xdsl_d4,7515,9660,9656,0.0,0,0,2209,0,0.29394544244843646,0.8208844295800818,2691,0,0,0.35808383233532937,0,0,1.0,1.0,1,0,2691,0.44325481798715205,3380,0,0,0.44976713240186295,960,2146,9664,0.8078509647371923,2148 +exp_polynomial,96xf64,linalg_xdsl_d5,8674,10779,10775,0.0,0,0,2497,0,0.287871800783952,0.8120325203252032,3075,0,0,0.35450772423334104,0,0,1.0,1.0,1,0,3075,0.4373488835158583,3956,0,0,0.4560756283145031,1152,2106,10783,0.8105833525478441,2108 +exp_polynomial,96xf64,linalg_xdsl_d6,9723,11886,11882,0.0,0,0,2785,0,0.28643422811889335,0.8051459959525874,3459,0,0,0.35575439679111387,0,0,1.0,1.0,1,0,3459,0.4435183997948455,4340,0,0,0.44636429085673146,1344,2164,11890,0.8021186876478453,2166 +exp_polynomial,96xf64,linalg_xdsl_d7,10971,13102,13098,0.0,0,0,3073,0,0.2801020873211193,0.7996357012750456,3843,0,0,0.3502871205906481,0,0,1.0,1.0,1,0,3843,0.429337504189476,5108,0,0,0.4655911038191596,1536,2132,13106,0.8158782244098077,2134 +exp_polynomial,96xf64,linalg_xdsl_d8,12037,14170,14166,0.0,0,0,3361,0,0.27922239760737727,0.7951265673054175,4227,0,0,0.3511672343607211,0,0,1.0,1.0,1,0,4227,0.43492128819837433,5492,0,0,0.4562598654149705,1728,2134,14174,0.8074270997756916,2136 +exp_polynomial,96xf64,linalg_xdsl_d9,13275,15438,15434,0.0,0,0,3649,0,0.27487758945386065,0.7913684667100412,4611,0,0,0.3473446327683616,0,0,1.0,1.0,1,0,4611,0.42415601140649434,6260,0,0,0.47156308851224105,1920,2164,15442,0.8189077212806026,2166 From e4c8b31e61a6ef41e3a92d49f17ca983e3a26936 Mon Sep 17 00:00:00 2001 From: szerdick Date: Tue, 12 May 2026 14:54:31 +0200 Subject: [PATCH 19/33] add plots for RQs and automate via Snakefile --- Snakefile | 62 ++++++++-- plots-mia-thesis/output/chebyshev_error.pdf | Bin 0 -> 48113 bytes plots-mia-thesis/output/rq1_plots.pdf | Bin 23351 -> 23351 bytes plots-mia-thesis/output/rq31_plots.pdf | Bin 0 -> 20604 bytes plots-mia-thesis/output/rq32_plots.pdf | Bin 0 -> 80736 bytes plots-mia-thesis/output/rq33_plots.pdf | Bin 0 -> 48098 bytes plots-mia-thesis/plot_rq1.py | 46 ++----- plots-mia-thesis/plot_rq31.py | 75 ++++++++++++ plots-mia-thesis/plot_rq32.py | 119 +++++++++++++++++++ plots-mia-thesis/plot_rq33.py | 75 ++++++++++++ plots-mia-thesis/plot_utils.py | 125 ++++++++++++++++++++ 11 files changed, 456 insertions(+), 46 deletions(-) create mode 100644 plots-mia-thesis/output/chebyshev_error.pdf create mode 100644 plots-mia-thesis/output/rq31_plots.pdf create mode 100644 plots-mia-thesis/output/rq32_plots.pdf create mode 100644 plots-mia-thesis/output/rq33_plots.pdf create mode 100644 plots-mia-thesis/plot_rq31.py create mode 100644 plots-mia-thesis/plot_rq32.py create mode 100644 plots-mia-thesis/plot_rq33.py diff --git a/Snakefile b/Snakefile index 7cb45d2e..f413e749 100644 --- a/Snakefile +++ b/Snakefile @@ -452,16 +452,6 @@ rule exp_polynomial: "plots-mia-thesis/output/rq1_plots.pdf", -rule plot_rq1: - input: - micro="results/kernels.exp_micro.csv", - poly="results/kernels.exp_polynomial.csv", - script="plots-mia-thesis/plot_rq1.py", - output: - "plots-mia-thesis/output/rq1_plots.pdf", - shell: - "python {input.script} --exp-micro {input.micro} --exp-polynomial {input.poly} -o {output}" - rule softmax_polynomial: input: "results/kernels.softmax_polynomial.csv" @@ -1003,3 +993,55 @@ rule xdsl_kernel_generate_source_chebyshev: | sed 's/scheme = "clenshaw"/scheme = "clenshaw", {params.bounds}/g' \ | {params.xdsl_opt} -p arith-add-fastmath > {output} """ + +########################################################### +# Mia Thesis plots rules +########################################################### + +PLOTS_DIR = "plots-mia-thesis" +PLOTS_OUTPUT = PLOTS_DIR + "/output" + +rule plot_rq1: + input: + script = PLOTS_DIR + "/plot_rq1.py", + utils = PLOTS_DIR + "/plot_utils.py", + micro = "results/kernels.exp_micro.csv", + poly = "results/kernels.exp_polynomial.csv", + output: + PLOTS_OUTPUT + "/rq1_plots.pdf", + shell: + "python {input.script} --exp-micro {input.micro} --exp-polynomial {input.poly} -o {output}" + +rule plot_rq31: + input: + script = PLOTS_DIR + "/plot_rq31.py", + utils = PLOTS_DIR + "/plot_utils.py", + output: + PLOTS_OUTPUT + "/rq31_plots.pdf", + shell: + "python {input.script} -o {output}" + +rule plot_rq32: + input: + script = PLOTS_DIR + "/plot_rq32.py", + utils = PLOTS_DIR + "/plot_utils.py", + output: + PLOTS_OUTPUT + "/rq32_plots.pdf", + shell: + "python {input.script} -o {output}" + +rule plot_rq33: + input: + script = PLOTS_DIR + "/plot_rq33.py", + utils = PLOTS_DIR + "/plot_utils.py", + output: + PLOTS_OUTPUT + "/rq33_plots.pdf", + shell: + "python {input.script} -o {output}" + +rule plots_mia_thesis: + input: + 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as pd import matplotlib.pyplot as plt -from plot_utils import savefig +from plot_utils import ( + PRECISIONS, + load_baseline_csv, + load_chebyshev_csv, + savefig, +) -PRECISION_BYTES = {"f16": 2, "f32": 4, "f64": 8} -PRECISIONS = ["f16", "f32", "f64"] -DEGREE_RE = re.compile(r"linalg_xdsl_d(\d+)$") - - -def _annotate(df: pd.DataFrame) -> pd.DataFrame: - parts = df["params"].str.split("x") - df = df.copy() - df["precision"] = parts.str[-1] - df["total_elements"] = parts.apply(lambda ps: int(np.prod([int(p) for p in ps[:-1]]))) - df["total_input_bytes"] = df.apply( - lambda r: r["total_elements"] * PRECISION_BYTES[r["precision"]], axis=1 - ) - df["cycles_per_byte"] = df["cycles"] / df["total_input_bytes"] - return df - - -def load_polynomial(csv_path: str) -> pd.DataFrame: - df = pd.read_csv(csv_path) - df = df[df["impl"].str.match(DEGREE_RE)].copy() - df["degree"] = df["impl"].str.extract(DEGREE_RE).astype(int) - return _annotate(df) - - -def load_micro_baseline(csv_path: str) -> pd.DataFrame: - df = pd.read_csv(csv_path) - df = df[df["impl"] == "baseline"].copy() - return _annotate(df) - - -def avg_per_degree(df: pd.DataFrame, precision: str, metric: str) -> pd.DataFrame: +def avg_per_degree(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: return ( df[df["precision"] == precision] .groupby("degree")[metric] @@ -125,8 +99,8 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) - poly_df = load_polynomial(args.exp_polynomial) - baseline_df = load_micro_baseline(args.exp_micro) + poly_df = load_chebyshev_csv(args.exp_polynomial) + baseline_df = load_baseline_csv(args.exp_micro) fig = plot_rq1(poly_df, baseline_df) savefig(fig, args.output) diff --git a/plots-mia-thesis/plot_rq31.py b/plots-mia-thesis/plot_rq31.py new file mode 100644 index 00000000..a2aaf533 --- /dev/null +++ b/plots-mia-thesis/plot_rq31.py @@ -0,0 +1,75 @@ +#!/usr/bin/env python3 +""" +RQ31 plot: signed approximation error p_d(x) - exp(x) on the interval +[CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER] for each Chebyshev degree d +in XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS. + +The polynomial p_d is the degree-d Chebyshev-Lobatto interpolant of exp, +computed with the same DCT-I formula used by the Snakefile rule +xdsl_kernel_generate_source_chebyshev — so the curves here correspond exactly +to what the xDSL pipeline emits. + +Usage: + python plot_rq31.py [--output plots-mia-thesis/output/rq31_plots.pdf] +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from plot_utils import ( + CHEBYSHEV_DEGREES, + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + DEGREE_COLORS, + DEGREE_LINESTYLES, + chebyshev_lobatto_coeffs, + eval_chebyshev, + savefig, +) + + +def plot_rq31() -> plt.Figure: + x = np.linspace(CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, 2001) + exp_x = np.exp(x) + + fig, ax = plt.subplots(figsize=(8, 5)) + for d in CHEBYSHEV_DEGREES: + approx = eval_chebyshev(chebyshev_lobatto_coeffs(d), x) + ax.plot( + x, approx - exp_x, + color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], + label=f"d={d}", + ) + + ax.axhline(0.0, color="black", linewidth=0.5) + ax.set_xlabel("x") + ax.set_ylabel(r"$p_d(x) - \exp(x)$") + ax.set_title( + f"Chebyshev-Lobatto approximation error on " + f"[{CHEBYSHEV_DOMAIN_LOWER}, {CHEBYSHEV_DOMAIN_UPPER}]" + ) + ax.grid(True, which="both", alpha=0.3) + ax.legend(ncol=2, fontsize=8, loc="best") + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--output", "-o", default="plots-mia-thesis/output/rq31_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_rq31() + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_rq32.py b/plots-mia-thesis/plot_rq32.py new file mode 100644 index 00000000..097dcc5d --- /dev/null +++ b/plots-mia-thesis/plot_rq32.py @@ -0,0 +1,119 @@ +#!/usr/bin/env python3 +""" +RQ32 plot: bits of mantissa lost by the Chebyshev approximation, per precision. + +For each precision (f16, f32, f64) and each degree d we compute + ulp_err(x) = |approx_DTYPE(x) − exp_rn_DTYPE(x)| / ulp_DTYPE(exp_rn(x)) +and plot + bits_lost(x) = log2(ulp_err(x)). + +bits_lost = 0 → 1 ULP off (last representable step from the correctly-rounded + result; precision floor). +bits_lost = k → bottom k bits of the mantissa are unreliable. +bits_lost = mantissa_bits[prec] → all precision gone. + +NOTE: the f64 reference is computed via np.exp(f64), itself accurate to ~1 +ULP, so the lowest bits_lost values for f64 conflate polynomial error with +libm's residual roundoff. Use mpmath for a strictly-correct f64 reference. + +Usage: + python plot_rq32.py [--output plots-mia-thesis/output/rq32_plots.pdf] +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from plot_utils import ( + CHEBYSHEV_DEGREES, + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + DEGREE_COLORS, + DEGREE_LINESTYLES, + PRECISION_MANTISSA_BITS, + PRECISION_NUMPY_DTYPE, + PRECISIONS, + chebyshev_lobatto_coeffs, + eval_chebyshev, + savefig, + ulp, +) + + +def plot_rq32(xmin: float, xmax: float, npoints: int) -> plt.Figure: + x = np.linspace(xmin, xmax, npoints) + exp_true = np.exp(x.astype(np.float64)) # high-precision reference value + + fig, axes = plt.subplots(1, len(PRECISIONS), figsize=(len(PRECISIONS) * 5, 5)) + + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[col_idx] + dtype = PRECISION_NUMPY_DTYPE[precision] + exp_rn = exp_true.astype(dtype) # correctly-rounded reference + ulp_rn = ulp(exp_true, precision) # ulp(exp_rn) in DTYPE + mantissa_bits = PRECISION_MANTISSA_BITS[precision] + for d in CHEBYSHEV_DEGREES: + approx = eval_chebyshev(chebyshev_lobatto_coeffs(d), x).astype(dtype) + ulp_err = np.abs( + approx.astype(np.float64) - exp_rn.astype(np.float64) + ) / ulp_rn + with np.errstate(divide="ignore"): + bits_lost = np.log2(ulp_err) + # exact matches → -inf; drop them so the line is broken there + bits_lost = np.where(np.isfinite(bits_lost), bits_lost, np.nan) + ax.plot( + x, bits_lost, + color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], + linewidth=0.8, + label=f"d={d}", + ) + + ax.axhline(0.0, color="black", linestyle="--", linewidth=0.8, + label="1 ULP (0 bits lost)") + ax.axhline(mantissa_bits, color="red", linestyle="--", linewidth=0.8, + label=f"all mantissa bits lost") + ax.set_ylim(-2, mantissa_bits + 4) + ax.set_xlabel("x") + ax.set_title(precision) + ax.grid(True, which="both", alpha=0.3) + + axes[0].set_ylabel(r"bits lost $=\log_2(|\mathrm{ULP\ error}|)$") + axes[-1].legend(ncol=2, fontsize=7, loc="best") + fig.suptitle( + f"Chebyshev approximation: mantissa bits lost vs correctly-rounded " + f"exp on [{xmin}, {xmax}]" + ) + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--output", "-o", default="plots-mia-thesis/output/rq32_plots.pdf", + help="Output plot file", + ) + parser.add_argument( + "--xmin", type=float, default=CHEBYSHEV_DOMAIN_LOWER, + help="Left edge of x window", + ) + parser.add_argument( + "--xmax", type=float, default=CHEBYSHEV_DOMAIN_UPPER, + help="Right edge of x window", + ) + parser.add_argument( + "--npoints", type=int, default=2001, + help="Number of x samples in the window", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_rq32(args.xmin, args.xmax, args.npoints) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_rq33.py b/plots-mia-thesis/plot_rq33.py new file mode 100644 index 00000000..bc03365c --- /dev/null +++ b/plots-mia-thesis/plot_rq33.py @@ -0,0 +1,75 @@ +#!/usr/bin/env python3 +""" +RQ33 plot: absolute approximation error |p_d(x) - exp(x)| on the interval +[CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER] for each Chebyshev degree d +in XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS. + +The polynomial p_d is the degree-d Chebyshev-Lobatto interpolant of exp, +computed with the same DCT-I formula used by the Snakefile rule +xdsl_kernel_generate_source_chebyshev — so the curves here correspond exactly +to what the xDSL pipeline emits. + +Usage: + python plot_rq33.py [--output plots-mia-thesis/output/rq33_plots.pdf] +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from plot_utils import ( + CHEBYSHEV_DEGREES, + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + DEGREE_COLORS, + DEGREE_LINESTYLES, + chebyshev_lobatto_coeffs, + eval_chebyshev, + savefig, +) + + +def plot_rq33() -> plt.Figure: + x = np.linspace(CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, 2001) + exp_x = np.exp(x) + + fig, ax = plt.subplots(figsize=(8, 5)) + for d in CHEBYSHEV_DEGREES: + approx = eval_chebyshev(chebyshev_lobatto_coeffs(d), x) + ax.plot( + x, np.abs(approx - exp_x), + color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], + label=f"d={d}", + ) + + ax.set_yscale("log") + ax.set_xlabel("x") + ax.set_ylabel(r"$|p_d(x) - \exp(x)|$") + ax.set_title( + f"Chebyshev-Lobatto approximation error on " + f"[{CHEBYSHEV_DOMAIN_LOWER}, {CHEBYSHEV_DOMAIN_UPPER}]" + ) + ax.grid(True, which="both", alpha=0.3) + ax.legend(ncol=2, fontsize=8, loc="best") + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--output", "-o", default="plots-mia-thesis/output/rq33_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_rq33() + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_utils.py b/plots-mia-thesis/plot_utils.py index bfbbfea2..82e75e97 100644 --- a/plots-mia-thesis/plot_utils.py +++ b/plots-mia-thesis/plot_utils.py @@ -1,6 +1,8 @@ from collections.abc import Iterable from typing import ClassVar, Sequence, cast +import math import os +import re import pandas as pd import matplotlib.pyplot as plt from matplotlib.axes import Axes @@ -12,7 +14,11 @@ from data import Impl from abc import ABC, abstractmethod + +########################################################### # Color palette +########################################################### + light_gray = "#cacaca" dark_gray = "#827b7b" light_blue = "#a6cee3" @@ -36,6 +42,125 @@ ] +########################################################### +# RQ shared constants & helpers (plot_rq*.py) +########################################################### + +# Precision metadata — sizes in bytes and IEEE-754 mantissa widths (with hidden bit). +PRECISIONS: list[str] = ["f16", "f32", "f64"] +PRECISION_BYTES: dict[str, int] = {"f16": 2, "f32": 4, "f64": 8} +PRECISION_MANTISSA_BITS: dict[str, int] = {"f16": 11, "f32": 24, "f64": 53} +PRECISION_NUMPY_DTYPE: dict[str, type] = { + "f16": np.float16, "f32": np.float32, "f64": np.float64, +} + +# Chebyshev domain & degree variants — must match the Snakefile. +CHEBYSHEV_DOMAIN_LOWER: float = -2.0 +CHEBYSHEV_DOMAIN_UPPER: float = 0.0 +CHEBYSHEV_DEGREES: list[int] = list(range(2, 13)) + +# Regex matching the variant names in XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS. +CHEBYSHEV_DEGREE_RE: re.Pattern[str] = re.compile(r"linalg_xdsl_d(\d+)$") + +# One (color, linestyle) per Chebyshev degree — used by plot_rq31 / plot_rq3 to +# keep curves directly comparable across plots. There are 11 degrees but only +# 8 colors in the project palette, so we cycle the colors and switch to a +# dashed style on wrap-around — every (color, linestyle) pair is unique. +_DEGREE_LINESTYLE_CYCLE: tuple[str, ...] = ("-", "--", ":") +DEGREE_COLORS: dict[int, str] = { + d: COLORS[i % len(COLORS)] + for i, d in enumerate(CHEBYSHEV_DEGREES) +} +DEGREE_LINESTYLES: dict[int, str] = { + d: _DEGREE_LINESTYLE_CYCLE[(i // len(COLORS)) % len(_DEGREE_LINESTYLE_CYCLE)] + for i, d in enumerate(CHEBYSHEV_DEGREES) +} + + +def chebyshev_lobatto_coeffs(degree: int) -> list[float]: + """DCT-I coefficients of the degree-`degree` Lobatto interpolant of exp + on [CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER]. + + Mirrors get_chebyshev_coeffs_from_variant in the Snakefile. The returned + coefficients use the "double-prime" convention: c_0 and c_n are NOT + pre-halved, so eval_chebyshev applies a 1/2 weight to the endpoints. + """ + n = degree + nodes = [math.cos(math.pi * j / n) for j in range(n + 1)] + mid = (CHEBYSHEV_DOMAIN_UPPER + CHEBYSHEV_DOMAIN_LOWER) / 2.0 + half = (CHEBYSHEV_DOMAIN_UPPER - CHEBYSHEV_DOMAIN_LOWER) / 2.0 + values = [math.exp(half * t + mid) for t in nodes] + coeffs: list[float] = [] + for k in range(n + 1): + s = 0.0 + for j in range(n + 1): + w = 0.5 if (j == 0 or j == n) else 1.0 + s += w * values[j] * math.cos(math.pi * k * j / n) + coeffs.append(2.0 * s / n) + return coeffs + + +def eval_chebyshev(coeffs: Sequence[float], x: np.ndarray) -> np.ndarray: + """Evaluate the double-prime Chebyshev expansion at x ∈ [domain_lower, domain_upper].""" + mid = (CHEBYSHEV_DOMAIN_UPPER + CHEBYSHEV_DOMAIN_LOWER) / 2.0 + half = (CHEBYSHEV_DOMAIN_UPPER - CHEBYSHEV_DOMAIN_LOWER) / 2.0 + t = (x - mid) / half + n = len(coeffs) - 1 + tk_prev = np.ones_like(t) + tk = t.copy() + result = 0.5 * coeffs[0] * tk_prev + (coeffs[1] * tk if n >= 1 else 0.0) + for k in range(2, n + 1): + tk_next = 2.0 * t * tk - tk_prev + weight = 0.5 if k == n else 1.0 + result = result + weight * coeffs[k] * tk_next + tk_prev, tk = tk, tk_next + return result + + +def ulp(values: np.ndarray, precision: str) -> np.ndarray: + """ULP of each value, evaluated in the given precision (f16/f32/f64).""" + dtype = PRECISION_NUMPY_DTYPE[precision] + v = np.asarray(values, dtype=dtype) + return (np.nextafter(v, np.array(np.inf, dtype=dtype)) - v).astype(np.float64) + + +def annotate_kernel_df(df: pd.DataFrame) -> pd.DataFrame: + """Add precision, total_elements, total_input_bytes, cycles_per_byte columns + derived from the kernel `params` string (e.g. "64xf32"). + """ + parts = df["params"].str.split("x") + df = df.copy() + df["precision"] = parts.str[-1] + df["total_elements"] = parts.apply( + lambda ps: int(np.prod([int(p) for p in ps[:-1]])) + ) + df["total_input_bytes"] = df.apply( + lambda r: r["total_elements"] * PRECISION_BYTES[r["precision"]], axis=1 + ) + df["cycles_per_byte"] = df["cycles"] / df["total_input_bytes"] + return df + + +def load_chebyshev_csv(csv_path: str) -> pd.DataFrame: + """Load exp_polynomial measurements, keep only Chebyshev-degree variants, + and add a `degree` column.""" + df = pd.read_csv(csv_path) + df = df[df["impl"].str.match(CHEBYSHEV_DEGREE_RE)].copy() + df["degree"] = df["impl"].str.extract(CHEBYSHEV_DEGREE_RE).astype(int) + return annotate_kernel_df(df) + + +def load_baseline_csv(csv_path: str) -> pd.DataFrame: + """Load exp_micro measurements and keep only the libm baseline rows.""" + df = pd.read_csv(csv_path) + df = df[df["impl"] == "baseline"].copy() + return annotate_kernel_df(df) + + +########################################################### +# Existing project plotting infrastructure +########################################################### + IMPL_COLORS = { Impl.OURS.value: 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Columns are values of the +`max_bits_lost` attribute the user might attach to math.exp: + + -1 → correctly-rounded (every mantissa bit guaranteed correct) + 0 → 1 ULP / libm-grade + k → 2^k ULPs of tolerated error + +Each cell is the smallest Chebyshev-Lobatto degree the pass would pick. A `*` +prefix marks cases that hit the pass's `_MAX_DEGREE` cap (the bound isn't met +within the budget, but the polynomial is still emitted at that degree). + +Mirrors `_choose_polynomial` in + xdsl/transforms/lower_exp_to_polynomial.py +verbatim, so the numbers here are exactly what the pass picks at compile time. + +Usage: + python plot_rq34.py [--xmin -2.0] [--xmax 0.0] \\ + [--bits-lost -1 0 1 2 4 8 16] \\ + [-o plots-mia-thesis/output/rq34_plots.pdf] +""" + +import argparse +import math as pymath +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import seaborn as sns + +from plot_utils import ( + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + PRECISION_MANTISSA_BITS, + PRECISIONS, + savefig, +) + + +# Must match _MAX_DEGREE in xdsl.transforms.lower_exp_to_polynomial. +_MAX_DEGREE = 30 + +DEFAULT_BITS_LOST = [-1, 0, 1, 2, 4, 8, 16] + + +def chosen_degree( + max_bits_lost: float, lower: float, upper: float, precision_bits: int, +) -> tuple[int, bool]: + """Mirror of xdsl._choose_polynomial's degree-picking loop. + + Returns (degree, capped) — `capped` is True iff the loop exited because it + hit _MAX_DEGREE without satisfying the bound. + """ + width = upper - lower + degree = 0 + bits_lost = ( + width * pymath.log2(pymath.e) + + pymath.log2(width) + + (precision_bits - 1) + ) + while bits_lost > max_bits_lost and degree < _MAX_DEGREE: + degree += 1 + bits_lost += pymath.log2(width) - 2 - pymath.log2(degree + 1) + capped = bits_lost > max_bits_lost + return degree, capped + + +def plot_rq34( + xmin: float, xmax: float, bits_lost_values: list[int], +) -> plt.Figure: + rows = PRECISIONS + cols = bits_lost_values + + degrees = np.zeros((len(rows), len(cols)), dtype=int) + capped = np.zeros((len(rows), len(cols)), dtype=bool) + for i, prec in enumerate(rows): + precision_bits = PRECISION_MANTISSA_BITS[prec] + for j, b in enumerate(cols): + d, c = chosen_degree(b, xmin, xmax, precision_bits) + degrees[i, j] = d + capped[i, j] = c + + # Annotate each cell with its degree; mark capped cells with a trailing *. + annot = np.array([ + [f"{d}{'*' if c else ''}" for d, c in zip(row_d, row_c)] + for row_d, row_c in zip(degrees, capped) + ]) + + fig, ax = plt.subplots( + figsize=(2.2 + 0.7 * len(cols), 1.6 + 0.55 * len(rows)) + ) + sns.heatmap( + degrees, + annot=annot, + fmt="", + cmap="RdYlGn_r", + vmin=0, vmax=_MAX_DEGREE, + xticklabels=[str(b) for b in cols], + yticklabels=rows, + cbar=False, + linewidths=0.5, + linecolor="white", + annot_kws={"fontsize": 11, "fontweight": "bold"}, + square=False, + ax=ax, + ) + plt.setp(ax.get_xticklabels(), rotation=0, fontsize=10) + plt.setp(ax.get_yticklabels(), rotation=0, fontsize=10) + ax.set_xlabel( + r"bits lost $=\log_2(|\mathrm{ULP\ error}|)$", + fontsize=11, + labelpad=10, + ) + ax.set_ylabel("precision", fontsize=11) + ax.xaxis.set_label_position("top") + ax.xaxis.tick_top() + + fig.suptitle( + f"Chebyshev polynomial degree picked by the pass on [{xmin}, {xmax}]", + fontsize=10, + ) + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--output", "-o", default="plots-mia-thesis/output/rq34_plots.pdf", + help="Output plot file", + ) + parser.add_argument( + "--xmin", type=float, default=CHEBYSHEV_DOMAIN_LOWER, + help="Domain lower bound passed to the pass", + ) + parser.add_argument( + "--xmax", type=float, default=CHEBYSHEV_DOMAIN_UPPER, + help="Domain upper bound passed to the pass", + ) + parser.add_argument( + "--bits-lost", type=int, nargs="+", default=DEFAULT_BITS_LOST, + help="max_bits_lost column values", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_rq34(args.xmin, args.xmax, args.bits_lost) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_rq35.py b/plots-mia-thesis/plot_rq35.py new file mode 100644 index 00000000..e5899e1d --- /dev/null +++ b/plots-mia-thesis/plot_rq35.py @@ -0,0 +1,125 @@ +#!/usr/bin/env python3 +""" +RQ35 plot: accuracy vs performance Pareto, one panel per precision (f16/f32/f64). + + x = max_bits_lost (the accuracy bound passed to lower-exp-to-polynomial; + moving right = looser accuracy) + y = avg cycles / byte across input sizes N (lower = faster) + +The lower-left corner is "best" (more accurate AND faster). A reasonable +pipeline should produce a monotone-decreasing curve: relaxing the bound buys +performance. + +Source data is `kernels.exp_micro.csv`. The plot expects rows with +`impl = linalg_xdsl_b` where is the integer `max_bits_lost` (negative +allowed, e.g. `linalg_xdsl_b-1` for correctly-rounded). The Snakefile does +not yet emit these variants — once it does, the plot picks them up +automatically. Until then only the libm baseline reference line is drawn. + +Usage: + python plot_rq35.py [-i results/kernels.exp_micro.csv] \\ + [-o plots-mia-thesis/output/rq35_plots.pdf] +""" + +import argparse +import re +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd + +from plot_utils import ( + PRECISIONS, + annotate_kernel_df, + load_baseline_csv, + savefig, +) + + +# Inferred naming: `linalg_xdsl_b` where is the integer max_bits_lost +# the pass was invoked with (e.g. `linalg_xdsl_b-1`, `linalg_xdsl_b0`, +# `linalg_xdsl_b4`). Negative values are correctly-rounded; 0 is libm-grade; +# higher values relax the bound. +BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") + + +def load_bits_lost_csv(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"].str.match(BITS_LOST_VARIANT_RE)].copy() + df["max_bits_lost"] = df["impl"].str.extract(BITS_LOST_VARIANT_RE).astype(int) + return annotate_kernel_df(df) + + +def avg_per_bits_lost(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: + return ( + df[df["precision"] == precision] + .groupby("max_bits_lost")[metric] + .mean() + .sort_index() + ) + + +def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: + return df.loc[df["precision"] == precision, metric].mean() + + +def plot_rq35(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: + fig, axes = plt.subplots( + 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False + ) + + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[col_idx] + series = avg_per_bits_lost(poly_df, precision, "cycles_per_byte") + baseline = avg_baseline(baseline_df, precision, "cycles_per_byte") + + if not series.empty: + ax.plot( + series.index, series.values, + marker="o", color="#33a02c", linewidth=1.4, + label="Chebyshev polynomial", + ) + if not np.isnan(baseline): + ax.axhline( + baseline, color="#1f78b4", linestyle="--", + label=f"libm baseline ({baseline:.3g})", + ) + + ax.set_title(precision) + ax.set_xlabel(r"max_bits_lost (looser $\rightarrow$)") + ax.set_ylabel("avg cycles / byte") + if not series.empty: + ax.set_xticks(series.index) + ax.grid(True, alpha=0.3) + ax.legend(loc="best", fontsize=8) + + fig.suptitle("Accuracy / performance Pareto for exp_micro") + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--input", "-i", + default="results/kernels.exp_micro.csv", + help="Input CSV with exp_micro measurements", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq35_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + poly_df = load_bits_lost_csv(args.input) + baseline_df = load_baseline_csv(args.input) + fig = plot_rq35(poly_df, baseline_df) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() From da76ce664909c8a09f3ddffecb37863f4c91ae19 Mon Sep 17 00:00:00 2001 From: Mia Sophie Zerdick Date: Thu, 14 May 2026 12:32:24 +0100 Subject: [PATCH 21/33] correctness check disabled --- kernels/exp_micro/main.c | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/kernels/exp_micro/main.c b/kernels/exp_micro/main.c index 98b28c12..842deaad 100644 --- a/kernels/exp_micro/main.c +++ b/kernels/exp_micro/main.c @@ -43,7 +43,7 @@ int main() { snrt_fpu_fence(); (void)snrt_mcycle(); - // Correctness check: We emit this part because some variants allow large to fully wrong results + // Correctness check: We emit this part because some variants allow large to fully wrong results int nerr = 0; for (int i = 0; i < N; i++) { DTYPE d = FABSF(local_z[i] - G[i]); From a897494569dd2ead460593c80f52b0fd46a02ee5 Mon Sep 17 00:00:00 2001 From: Mia Sophie Zerdick Date: Thu, 14 May 2026 14:28:46 +0100 Subject: [PATCH 22/33] new plot --- Snakefile | 20 ++++++++++++++++++++ plots-mia-thesis/output/rq31_plots.pdf | Bin 20604 -> 20604 bytes plots-mia-thesis/output/rq32_plots.pdf | Bin 80736 -> 80469 bytes plots-mia-thesis/output/rq33_plots.pdf | Bin 48098 -> 48076 bytes plots-mia-thesis/output/rq34_plots.pdf | Bin 21285 -> 21285 bytes plots-mia-thesis/output/rq35_plots.pdf | Bin 0 -> 20179 bytes plots-mia-thesis/plot_rq35.py | 4 ++-- 7 files changed, 22 insertions(+), 2 deletions(-) create mode 100644 plots-mia-thesis/output/rq35_plots.pdf diff --git a/Snakefile b/Snakefile index f413e749..a074c237 100644 --- a/Snakefile +++ b/Snakefile @@ -1039,9 +1039,29 @@ rule plot_rq33: shell: "python {input.script} -o {output}" +rule plot_rq34: + input: + script = PLOTS_DIR + "/plot_rq34.py", + utils = PLOTS_DIR + "/plot_utils.py", + output: + PLOTS_OUTPUT + "/rq34_plots.pdf", + shell: + "python {input.script} -o {output}" + +rule plot_rq35: + input: + script = PLOTS_DIR + "/plot_rq35.py", + utils = PLOTS_DIR + "/plot_utils.py", + output: + PLOTS_OUTPUT + "/rq35_plots.pdf", + shell: + "python {input.script} -o {output}" + + rule plots_mia_thesis: input: PLOTS_OUTPUT + "/rq1_plots.pdf", PLOTS_OUTPUT + "/rq31_plots.pdf", PLOTS_OUTPUT + "/rq32_plots.pdf", PLOTS_OUTPUT + "/rq33_plots.pdf", + PLOTS_OUTPUT + "/rq34_plots.pdf", \ No newline at end of file diff --git a/plots-mia-thesis/output/rq31_plots.pdf b/plots-mia-thesis/output/rq31_plots.pdf index a55e53b90a4e4313d6974013db277406c2610a93..acf887b3f335ebdf6329ec806f3eb89d282b6b76 100644 GIT binary patch delta 22 dcmeyffbq`)#tk~&>?VfBMuvtan~l9aSpj7w2S@+_ delta 22 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plot_rq35(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: if not series.empty: ax.plot( series.index, series.values, - marker="o", color="#33a02c", linewidth=1.4, + marker="o", linestyle="none", color="#33a02c", label="Chebyshev polynomial", ) if not np.isnan(baseline): @@ -94,7 +94,7 @@ def plot_rq35(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: ax.grid(True, alpha=0.3) ax.legend(loc="best", fontsize=8) - fig.suptitle("Accuracy / performance Pareto for exp_micro") + fig.suptitle("Accuracy vs performance Pareto for our polynomial approximation of exp(x)") fig.tight_layout() return fig From b1101e4ca7c17ab0325d95ce1904488375895179 Mon Sep 17 00:00:00 2001 From: Mia Sophie Zerdick Date: Fri, 15 May 2026 14:22:55 +0100 Subject: [PATCH 23/33] run fast test and change macro plotting --- Snakefile | 28 +- default.yaml | 1 + plots-mia-thesis/output/rq41_plots.pdf | Bin 0 -> 62903 bytes plots-mia-thesis/output/rq42_plots.pdf | Bin 0 -> 23402 bytes plots-mia-thesis/plot_exp_macro.py | 2 + plots-mia-thesis/plot_rq41.py | 137 +++++++++ plots-mia-thesis/plot_rq42.py | 245 ++++++++++++++++ results/kernels.csv | 36 ++- results/kernels.fast.csv | 36 ++- results/kernels.softmax_polynomial.csv | 385 +++++++++++++++++++++++++ results/pivoted.csv | 18 +- results/pivoted.fast.csv | 18 +- results/pivoted_ipc.csv | 2 +- results/pivoted_ipc.fast.csv | 2 +- 14 files changed, 863 insertions(+), 47 deletions(-) create mode 100644 plots-mia-thesis/output/rq41_plots.pdf create mode 100644 plots-mia-thesis/output/rq42_plots.pdf create mode 100644 plots-mia-thesis/plot_rq41.py create mode 100644 plots-mia-thesis/plot_rq42.py create mode 100644 results/kernels.softmax_polynomial.csv diff --git a/Snakefile b/Snakefile index a074c237..829608cc 100644 --- a/Snakefile +++ b/Snakefile @@ -633,7 +633,7 @@ def cc_link_inputs(wildcards): f"kernels/{wildcards.kernel}/{wildcards.shape}/data.o", f"kernels/{wildcards.kernel}/{wildcards.shape}/main.o", ] - if wildcards.kernel == "softmax-polynomial": + if wildcards.kernel == "softmax_polynomial": base.append(f"kernels/{wildcards.kernel}/{wildcards.shape}/softmax.o") return base @@ -784,7 +784,7 @@ rule cc_compile_shared_softmax: output: "kernels/{kernel}/{shape}/softmax.S", wildcard_constraints: - kernel="softmax-polynomial", + kernel="softmax_polynomial", params: cc=config["cc"], cflags=config["cflags"], @@ -1057,6 +1057,26 @@ rule plot_rq35: shell: "python {input.script} -o {output}" +rule plot_rq41: + input: + script = PLOTS_DIR + "/plot_rq41.py", + utils = PLOTS_DIR + "/plot_utils.py", + output: + PLOTS_OUTPUT + "/rq41_plots.pdf", + shell: + "python {input.script} -o {output}" + +rule plot_rq42: + input: + script = PLOTS_DIR + "/plot_rq42.py", + utils = PLOTS_DIR + "/plot_utils.py", + rq34 = PLOTS_DIR + "/plot_rq34.py", + softmax = "results/kernels.softmax_polynomial.csv", + output: + PLOTS_OUTPUT + "/rq42_plots.pdf", + shell: + "python {input.script} -i {input.softmax} -o {output}" + rule plots_mia_thesis: input: @@ -1064,4 +1084,6 @@ rule plots_mia_thesis: PLOTS_OUTPUT + "/rq31_plots.pdf", PLOTS_OUTPUT + "/rq32_plots.pdf", PLOTS_OUTPUT + "/rq33_plots.pdf", - PLOTS_OUTPUT + "/rq34_plots.pdf", \ No newline at end of file + PLOTS_OUTPUT + "/rq34_plots.pdf", + PLOTS_OUTPUT + "/rq41_plots.pdf", + PLOTS_OUTPUT + "/rq42_plots.pdf", \ No newline at end of file diff --git a/default.yaml b/default.yaml index 85862d2b..e16a074b 100644 --- a/default.yaml +++ b/default.yaml @@ -41,6 +41,7 @@ cflags: - -ffast-math - -fno-builtin-printf - -fno-common + - -mno-fdiv - -O3 - -D__DEFINED_uint64_t - -I/opt/snitch_cluster/target/snitch_cluster/sw/runtime/rtl/src diff --git a/plots-mia-thesis/output/rq41_plots.pdf b/plots-mia-thesis/output/rq41_plots.pdf new file mode 100644 index 0000000000000000000000000000000000000000..bb6c41c1987323c2b00663b571c918603db152bc GIT binary patch literal 62903 zcmZU)1yG#9(l&|&39ER9U9>@7$*|7X?N!9>N(l|%=8te6DY6f;j(5+-Ro 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hide_xlabel: @@ -93,6 +94,7 @@ def plot_grid_cell(cls, ax: Axes, df: pd.DataFrame, *, hide_xlabel: bool) -> Non ax.plot( df.index, df[col], color=IMPL_COLORS[col], marker=IMPL_MARKERS[col], + linestyle="none", ) ax.set_xticks(df.index) if not hide_xlabel: diff --git a/plots-mia-thesis/plot_rq41.py b/plots-mia-thesis/plot_rq41.py new file mode 100644 index 00000000..4ca7441e --- /dev/null +++ b/plots-mia-thesis/plot_rq41.py @@ -0,0 +1,137 @@ +#!/usr/bin/env python3 +""" +RQ41 plot: per-element comparison of correctly-rounded exp(x_i) against the +degree-d Chebyshev-Lobatto approximation, for d = 2..12 and three input +vectors per precision (f16, f32, f64). + +Inputs are generated the way the softmax_polynomial kernel sees them: + x ~ uniform(-1, 1, N) (mirrors softmax_polynomial/gendata.py) + x' = x - max(x) (the max-shift the kernel performs before exp) +so every x'_i lies in [CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER] = +[-2, 0] — the domain on which the pass fits exp. The Chebyshev coefficients +are computed with the same DCT-I formula used by xdsl_kernel_generate_source_chebyshev +in the Snakefile, so the curves here correspond exactly to what the xDSL +pipeline emits. + +Three different random seeds give three different input vectors per precision. +Each panel: + x-axis = element index i + y-axis = exp(x'_i) +with a "true" curve (correctly-rounded exp in the target precision) and one +curve per degree d in [CHEBYSHEV_DEGREES][2..12]. + +Usage: + python plot_rq41.py [--n 16] [--seeds 0 1 2] \\ + [-o plots-mia-thesis/output/rq41_plots.pdf] +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from plot_utils import ( + CHEBYSHEV_DEGREES, + DEGREE_COLORS, + DEGREE_LINESTYLES, + PRECISION_NUMPY_DTYPE, + PRECISIONS, + chebyshev_lobatto_coeffs, + eval_chebyshev, + savefig, +) + + +DEFAULT_N = 16 +DEFAULT_SEEDS = [0, 1, 2] + + +def softmax_xprime(seed: int, n: int, precision: str) -> np.ndarray: + """Reproduce the per-element input that softmax_polynomial feeds to + exp_kernel: gendata's uniform(-1, 1, N) sequence cast to `precision`, + then x - max(x). Uses the legacy global RNG to match gendata.py.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + np.random.seed(seed) + x = np.random.uniform(-1.0, 1.0, n).astype(dtype) + return (x - x.max()).astype(dtype) + + +def chebyshev_approx(x_prime: np.ndarray, degree: int, precision: str) -> np.ndarray: + """Degree-d Chebyshev-Lobatto interpolant of exp on [-2, 0], evaluated in + float64 then rounded to `precision` to match the dtype of the kernel.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + approx = eval_chebyshev(chebyshev_lobatto_coeffs(degree), x_prime.astype(np.float64)) + return approx.astype(dtype) + + +def plot_rq41(n: int, seeds: list[int]) -> plt.Figure: + fig, axes = plt.subplots( + len(PRECISIONS), len(seeds), + figsize=(len(seeds) * 4.0, len(PRECISIONS) * 3.0), + sharex=True, + ) + + for row, precision in enumerate(PRECISIONS): + dtype = PRECISION_NUMPY_DTYPE[precision] + for col, seed in enumerate(seeds): + ax = axes[row][col] + x_prime = softmax_xprime(seed, n, precision) + idx = np.arange(n) + + exp_true = np.exp(x_prime.astype(np.float64)).astype(dtype) + ax.plot( + idx, exp_true, + color="black", marker="o", linestyle="-", linewidth=1.4, + label="exp(x) (correctly rounded)" if (row == 0 and col == 0) else None, + ) + + for d in CHEBYSHEV_DEGREES: + approx = chebyshev_approx(x_prime, d, precision) + ax.plot( + idx, approx, + color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], + marker="x", markersize=4, linewidth=0.8, + label=f"d={d}" if (row == 0 and col == 0) else None, + ) + + if col == 0: + ax.set_ylabel(f"{precision}\nexp(x'_i)") + if row == len(PRECISIONS) - 1: + ax.set_xlabel("element index i") + ax.set_title(f"seed={seed}, N={n}") + ax.grid(True, alpha=0.3) + + axes[0][0].legend(ncol=2, fontsize=7, loc="upper left", bbox_to_anchor=(0.0, -0.0)) + fig.suptitle( + "Softmax exp inputs: correctly-rounded vs degree-d Chebyshev approximation" + ) + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--n", type=int, default=DEFAULT_N, + help="Number of elements per input vector", + ) + parser.add_argument( + "--seeds", type=int, nargs="+", default=DEFAULT_SEEDS, + help="Random seeds for the three input vectors", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq41_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_rq41(args.n, args.seeds) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_rq42.py b/plots-mia-thesis/plot_rq42.py new file mode 100644 index 00000000..0e8126d8 --- /dev/null +++ b/plots-mia-thesis/plot_rq42.py @@ -0,0 +1,245 @@ +#!/usr/bin/env python3 +""" +RQ42 plot: Does the kernel-level exp accuracy/perf trade-off translate to +the softmax operator? Mirrors rq35's layout so the two plots can be +compared directly: same x-axis (`max_bits_lost`), same left y-axis +(avg cycles/byte). Adds a twin right y-axis showing the end-to-end softmax +output accuracy (avg bits lost in the softmax output across 100 sampled +input vectors). + +Performance is loaded from `results/kernels.softmax_polynomial.csv` — same +processing as rq35. Accuracy is measured offline: + for each (precision, max_bits_lost): + 1. recover the Chebyshev degree the pass picks (chosen_degree) + 2. sample 100 input vectors of size DEFAULT_N from uniform(-1, 1) + 3. run the softmax kernel in target precision: max-shift, + Chebyshev approx of exp on [-2, 0], sum, normalize + 4. reference = softmax in float64, rounded to target precision + 5. per output element i: bits_lost_i = log2(max(1, ULP error_i)) + 6. average over output elements per vector, then over the 100 vectors. + +Caveat: the float64 reference is itself ~1 ULP off correctly-rounded for +f64; the bottom of the f64 accuracy curve conflates polynomial error with +libm's residual roundoff (same caveat as plot_rq32). + +Usage: + python plot_rq42.py [-i results/kernels.softmax_polynomial.csv] \\ + [--n 64] [--samples 100] [-o plots-mia-thesis/output/rq42_plots.pdf] +""" + +import argparse +import re +from functools import lru_cache +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd + +from plot_rq34 import chosen_degree +from plot_utils import ( + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + PRECISION_MANTISSA_BITS, + PRECISION_NUMPY_DTYPE, + PRECISIONS, + annotate_kernel_df, + chebyshev_lobatto_coeffs, + eval_chebyshev, + savefig, + ulp, +) + + +BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") + +DEFAULT_N = 64 +DEFAULT_SAMPLES = 100 +DEFAULT_SEED = 0 + +PERF_COLOR = "#33a02c" # matches rq35 +ACC_COLOR = "#e31a1c" + + +@lru_cache(maxsize=None) +def _cached_coeffs(degree: int) -> tuple[float, ...]: + return tuple(chebyshev_lobatto_coeffs(degree)) + + +def load_softmax_csv(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"].str.match(BITS_LOST_VARIANT_RE)].copy() + df["max_bits_lost"] = df["impl"].str.extract(BITS_LOST_VARIANT_RE).astype(int) + return annotate_kernel_df(df) + + +def softmax_approx(x: np.ndarray, degree: int, precision: str) -> np.ndarray: + """Reproduce softmax_polynomial kernel arithmetic in `precision`: + m = max(x) (in dtype) + e = approx_d(x - m) (Chebyshev eval, in dtype) + s = sum(e) (in dtype) + z = e / s (in dtype) + Polynomial eval is done in float64 and cast to dtype — same approach + plot_rq32 uses; the kernel's Clenshaw eval in DTYPE differs slightly but + not enough to matter for the translation question.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + x = x.astype(dtype) + m = x.max() + xp = (x - m).astype(dtype) + coeffs = list(_cached_coeffs(degree)) + e = eval_chebyshev(coeffs, xp.astype(np.float64)).astype(dtype) + s = dtype(e.sum()) + return (e / s).astype(dtype) + + +def softmax_reference_f64(x: np.ndarray) -> np.ndarray: + """Reference softmax computed entirely in float64.""" + x64 = x.astype(np.float64) + m = x64.max() + e = np.exp(x64 - m) + return e / e.sum() + + +def per_vector_bits_lost(x: np.ndarray, degree: int, precision: str) -> float: + """Average over output elements of bits_lost_i = log2(max(1, ULP_err_i)).""" + dtype = PRECISION_NUMPY_DTYPE[precision] + approx = softmax_approx(x, degree, precision) + ref_f64 = softmax_reference_f64(x) + ref_rn = ref_f64.astype(dtype) + ulps = ulp(ref_f64, precision) # ULP at the true value, in target precision + diff = np.abs(approx.astype(np.float64) - ref_rn.astype(np.float64)) + with np.errstate(divide="ignore", invalid="ignore"): + ulp_err = diff / ulps + ulp_err = np.where(np.isfinite(ulp_err), ulp_err, 0.0) + bits = np.log2(np.maximum(1.0, ulp_err)) + return float(bits.mean()) + + +def measure_accuracy( + precision: str, bits_lost: int, n: int, samples: int, seed: int, +) -> float: + mantissa = PRECISION_MANTISSA_BITS[precision] + degree, _ = chosen_degree( + bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa + ) + rng = np.random.default_rng(np.uint64(seed) ^ np.uint64(bits_lost & 0xFFFF)) + vecs = [rng.uniform(-1.0, 1.0, n) for _ in range(samples)] + return float(np.mean([per_vector_bits_lost(x, degree, precision) for x in vecs])) + + +def aggregate( + df: pd.DataFrame, n: int, samples: int, seed: int, +) -> pd.DataFrame: + """One row per (precision, max_bits_lost): + - cycles_per_byte_mean = avg over the N values benchmarked + - softmax_output_bits_lost = avg over `samples` input vectors of size n + """ + rows = [] + for (precision, bits_lost), group in df.groupby(["precision", "max_bits_lost"]): + mantissa = PRECISION_MANTISSA_BITS[precision] + degree, capped = chosen_degree( + bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa + ) + bits = measure_accuracy( + precision, int(bits_lost), n=n, samples=samples, seed=seed, + ) + rows.append({ + "precision": precision, + "max_bits_lost": int(bits_lost), + "degree": degree, + "capped": capped, + "cycles_per_byte_mean": group["cycles_per_byte"].mean(), + "softmax_output_bits_lost": bits, + }) + return pd.DataFrame(rows).sort_values(["precision", "max_bits_lost"]) + + +def plot_rq42(agg: pd.DataFrame) -> plt.Figure: + fig, axes = plt.subplots( + 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 5.0, 4.5), sharey=False, + ) + for i, precision in enumerate(PRECISIONS): + ax = axes[i] + sub = agg[agg["precision"] == precision].sort_values("max_bits_lost") + if sub.empty: + ax.set_title(f"{precision} (no data)") + ax.grid(True, alpha=0.3) + continue + + # Left axis: avg cycles/byte (mirrors rq35). + l_perf, = ax.plot( + sub["max_bits_lost"], sub["cycles_per_byte_mean"], + marker="o", linestyle="-", color=PERF_COLOR, + label="avg cycles / byte (softmax)", + ) + + # Right axis: softmax output bits lost. + ax2 = ax.twinx() + l_acc, = ax2.plot( + sub["max_bits_lost"], sub["softmax_output_bits_lost"], + marker="s", linestyle="--", color=ACC_COLOR, + label="avg bits lost in softmax output", + ) + + # Reference y = x line: "exp bound translates 1:1 to softmax output". + xs = sub["max_bits_lost"].to_numpy() + l_ref, = ax2.plot( + xs, np.maximum(xs, 0.0), + color="black", linestyle=":", linewidth=1.0, + label="ideal: output bits lost = max_bits_lost", + ) + + ax.set_xticks(xs) + ax.set_xlabel(r"max_bits_lost (looser $\rightarrow$)") + ax.set_ylabel("avg cycles / byte", color=PERF_COLOR) + ax2.set_ylabel("softmax output bits lost", color=ACC_COLOR) + ax.tick_params(axis="y", labelcolor=PERF_COLOR) + ax2.tick_params(axis="y", labelcolor=ACC_COLOR) + ax.set_title(precision) + ax.grid(True, alpha=0.3) + if i == 0: + ax.legend(handles=[l_perf, l_acc, l_ref], loc="best", fontsize=7) + + fig.suptitle( + "RQ4: Softmax operator — does the kernel-level exp trade-off translate?" + ) + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--input", "-i", + default="results/kernels.softmax_polynomial.csv", + help="softmax_polynomial measurement CSV", + ) + parser.add_argument( + "--n", type=int, default=DEFAULT_N, + help="Size of each sample input vector for the accuracy measurement", + ) + parser.add_argument( + "--samples", type=int, default=DEFAULT_SAMPLES, + help="Number of sample input vectors per variant", + ) + parser.add_argument( + "--seed", type=int, default=DEFAULT_SEED, + help="Base seed for input-vector sampling", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq42_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + df = load_softmax_csv(args.input) + agg = aggregate(df, n=args.n, samples=args.samples, seed=args.seed) + fig = plot_rq42(agg) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/results/kernels.csv b/results/kernels.csv index 93d1b8e2..e674b54f 100644 --- a/results/kernels.csv +++ b/results/kernels.csv @@ -15,18 +15,30 @@ dense,8x8xf64,snitch_stream,2693,4830,4827,0.0,0,512,706,0,0.2621611585592276,0. dense,8x8xf64,snrt,2673,4794,4791,0.0,0,512,706,0,0.26412270856715303,0.9145077720207254,772,0,0,0.2888140665918444,0,0,1.9896907216494844,1.9896907216494846,1,0.0,388,0.7744510978043913,113,0,0,0.04227459783015339,0,2122,4798,0.3310886644219978,2124 exp_macro,128xf64,snrt,2855,6196,6193,0.0,0,384,1287,0,0.4507880910683012,0.9801980198019802,1313,0,0,0.45989492119089315,0,0,11.222222222222223,11.222222222222221,1,4.47242206235012,117,0.06074766355140187,1809,1865,417,0.6336252189141857,305,3342,6200,1.093520140105079,3344 exp_macro,64xf64,snrt,1897,4593,4590,0.0,0,192,646,0,0.34053769109119664,0.9656203288490284,669,0,0,0.3526620980495519,0,0,9.422535211267606,9.422535211267606,1,4.342592592592593,71,0.06484018264840183,1024,938,216,0.5397996837111229,174,2697,4597,0.8924617817606748,2699 -exp_micro,16xf16,baseline,1636,4228,4225,0.0,0,48,225,0,0.13753056234718827,0.5844155844155844,385,0,0,0.23533007334963324,0,0,1.0,1.0,1,7.686274509803922,385,0.5099337748344371,370,392,51,0.22616136919315402,35,2593,4232,0.4614914425427873,2595 -exp_micro,16xf32,baseline,1542,4150,4147,0.0,0,48,193,0,0.1251621271076524,0.546742209631728,353,0,0,0.22892347600518806,0,0,1.0,1.0,1,7.745098039215686,353,0.4889196675900277,369,395,51,0.23929961089494164,35,2609,4154,0.4682230869001297,2611 -exp_micro,16xf64,baseline,1748,4283,4280,0.0,0,112,209,0,0.11956521739130435,0.48267898383371827,433,0,0,0.2477116704805492,0,0,1.0,1.0,1,12.35820895522388,433,0.5191846522781774,401,828,67,0.2294050343249428,35,2536,4287,0.477116704805492,2538 -exp_micro,32xf16,baseline,3236,5828,5825,0.0,0,96,449,0,0.13875154511742893,0.5838751625487646,769,0,0,0.2376390605686032,0,0,1.0,1.0,1,7.6767676767676765,769,0.5157612340710932,722,760,99,0.223114956736712,67,2593,5832,0.4607540173053152,2595 -exp_micro,32xf32,baseline,3047,5666,5663,0.0,0,96,385,0,0.1263537906137184,0.5460992907801419,705,0,0,0.23137512307187397,0,0,1.0,1.0,1,7.707070707070707,705,0.4940434477925718,722,763,99,0.2369543813587135,67,2620,5670,0.46832950443058746,2622 -exp_micro,32xf64,baseline,3467,6028,6025,0.0,0,224,417,0,0.1202768964522642,0.4820809248554913,865,0,0,0.2494952408422267,0,0,1.0,1.0,1,12.549618320610687,865,0.5239248940036342,786,1644,131,0.22670897029131815,67,2562,6032,0.47620421113354483,2564 -exp_micro,48xf16,baseline,4832,7424,7421,0.0,0,144,673,0,0.13927980132450332,0.5836947094535994,1153,0,0,0.23861754966887416,0,0,1.0,1.0,1,7.583892617449664,1153,0.4754639175257732,1272,1130,149,0.2632450331125828,101,2593,7428,0.5018625827814569,2595 -exp_micro,48xf32,baseline,4551,7175,7172,0.0,0,144,577,0,0.12678532190727312,0.5458845789971618,1057,0,0,0.23225664689079323,0,0,1.0,1.0,1,7.6938775510204085,1057,0.4960112623181605,1074,1131,147,0.23599208965062624,99,2625,7179,0.46824873654141946,2627 -exp_micro,48xf64,baseline,5189,7747,7744,0.0,0,336,625,0,0.12044709963384082,0.4818812644564379,1297,0,0,0.24995182116014647,0,0,1.0,1.0,1,12.615384615384615,1297,0.5257397648966355,1170,2460,195,0.22547697051455,99,2559,7751,0.4754287916746965,2561 -exp_micro,64xf16,baseline,6432,9024,9021,0.0,0,192,897,0,0.1394589552238806,0.5836044242029929,1537,0,0,0.23896144278606965,0,0,1.0,1.0,1,7.604060913705584,1537,0.4765891472868217,1688,1498,197,0.26243781094527363,133,2593,9028,0.5013992537313433,2595 -exp_micro,64xf32,baseline,6046,8706,8703,0.0,0,192,769,0,0.12719153159113464,0.5457771469127041,1409,0,0,0.23304664240820377,0,0,1.0,1.0,1,7.619289340101523,1409,0.45495640942847915,1688,1501,197,0.2791928547800199,133,2661,8710,0.5122394971882236,2663 -exp_micro,64xf64,baseline,6886,9458,9455,0.0,0,448,833,0,0.12097008422887016,0.4817813765182186,1729,0,0,0.2510891664246297,0,0,1.0,1.0,1,12.582375478927203,1729,0.48772919605077575,1816,3284,261,0.26372349695033404,133,2573,9462,0.5148126633749637,2575 +exp_micro,16xf16,baseline,1628,4248,4245,0.0,0,48,225,0,0.1382063882063882,0.5844155844155844,385,0,0,0.23648648648648649,0,0,1.0,1.0,1,7.686274509803922,385,0.5112881806108898,368,392,51,0.22604422604422605,35,2621,4252,0.46253071253071254,2623 +exp_micro,16xf16,linalg_xdsl_b4,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf32,baseline,1535,4155,4152,0.0,0,48,193,0,0.1257328990228013,0.546742209631728,353,0,0,0.22996742671009773,0,0,1.0,1.0,1,7.745098039215686,353,0.4895977808599168,368,395,51,0.23973941368078175,35,2621,4159,0.4697068403908795,2623 +exp_micro,16xf32,linalg_xdsl_b4,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf64,baseline,1750,4321,4318,0.0,0,112,209,0,0.11942857142857143,0.48267898383371827,433,0,0,0.24742857142857144,0,0,1.0,1.0,1,12.35820895522388,433,0.5198079231692677,400,828,67,0.22857142857142856,35,2572,4325,0.476,2574 +exp_micro,16xf64,linalg_xdsl_b4,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,32xf16,baseline,3229,5849,5846,0.0,0,96,449,0,0.13905233818519666,0.5838751625487646,769,0,0,0.2381542273149582,0,0,1.0,1.0,1,7.6767676767676765,769,0.5164539959704499,720,760,99,0.22297925054196346,67,2621,5853,0.46113347785692166,2623 +exp_micro,32xf16,linalg_xdsl_b4,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf32,baseline,3039,5659,5656,0.0,0,96,385,0,0.12668641000329056,0.5460992907801419,705,0,0,0.23198420533070088,0,0,1.0,1.0,1,7.707070707070707,705,0.49473684210526314,720,763,99,0.23692003948667326,67,2621,5663,0.46890424481737414,2623 +exp_micro,32xf32,linalg_xdsl_b4,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf64,baseline,3463,6039,6036,0.0,0,224,417,0,0.12041582442968525,0.4820809248554913,865,0,0,0.2497834247762056,0,0,1.0,1.0,1,12.549618320610687,865,0.5245603395997575,784,1644,131,0.22639330060641064,67,2577,6043,0.47617672538261624,2579 +exp_micro,32xf64,linalg_xdsl_b4,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,48xf16,baseline,4832,7452,7449,0.0,0,144,673,0,0.13927980132450332,0.5836947094535994,1153,0,0,0.23861754966887416,0,0,1.0,1.0,1,7.583892617449664,1153,0.47585637639290135,1270,1130,149,0.2628311258278146,101,2621,7456,0.5014486754966887,2623 +exp_micro,48xf16,linalg_xdsl_b4,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf32,baseline,4544,7169,7166,0.0,0,144,577,0,0.1269806338028169,0.5458845789971618,1057,0,0,0.2326144366197183,0,0,1.0,1.0,1,7.6938775510204085,1057,0.4964772193518084,1072,1131,147,0.23591549295774647,99,2626,7173,0.46852992957746475,2628 +exp_micro,48xf32,linalg_xdsl_b4,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf64,baseline,5177,7754,7751,0.0,0,336,625,0,0.12072628935677034,0.4818812644564379,1297,0,0,0.2505311956731698,0,0,1.0,1.0,1,12.615384615384615,1297,0.5261663286004057,1168,2460,195,0.2256132895499324,99,2578,7758,0.47614448522310215,2580 +exp_micro,48xf64,linalg_xdsl_b4,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,64xf16,baseline,6432,9052,9049,0.0,0,192,897,0,0.1394589552238806,0.5836044242029929,1537,0,0,0.23896144278606965,0,0,1.0,1.0,1,7.604060913705584,1537,0.47688488985417316,1686,1498,197,0.2621268656716418,133,2621,9056,0.5010883084577115,2623 +exp_micro,64xf16,linalg_xdsl_b4,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf32,baseline,6046,8659,8656,0.0,0,192,769,0,0.12719153159113464,0.5457771469127041,1409,0,0,0.23304664240820377,0,0,1.0,1.0,1,7.619289340101523,1409,0.4552504038772213,1686,1501,197,0.2788620575587165,133,2614,8663,0.5119086999669202,2616 +exp_micro,64xf32,linalg_xdsl_b4,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf64,baseline,6878,9508,9505,0.0,0,448,833,0,0.1211107880197732,0.4817813765182186,1729,0,0,0.2513812154696133,0,0,1.0,1.0,1,12.582375478927203,1729,0.4880045159469376,1814,3284,261,0.26373945914510033,133,2631,9512,0.5151206746147137,2633 +exp_micro,64xf64,linalg_xdsl_b4,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 fill,4x4xf64,baseline,35,2087,2084,0.0,0,0,1,0,0.02857142857142857,0.058823529411764705,17,0,0,0.4857142857142857,0,0,1.0,1.0,1,0.0,17,0.7391304347826086,6,0,0,0.17142857142857143,0,2053,2091,0.6571428571428571,2055 fill,4x4xf64,linalg,35,2087,2084,0.0,0,0,1,0,0.02857142857142857,0.058823529411764705,17,0,0,0.4857142857142857,0,0,1.0,1.0,1,0.0,17,0.7391304347826086,6,0,0,0.17142857142857143,0,2053,2091,0.6571428571428571,2055 fill,4x4xf64,linalg_xdsl,39,2088,2085,0.0,0,0,18,0,0.46153846153846156,0.9,20,0,0,0.5128205128205128,0,0,3.333333333333333,3.3333333333333335,1,0.0,6,0.3,14,0,0,0.358974358974359,0,2050,2092,0.8717948717948718,2052 diff --git a/results/kernels.fast.csv b/results/kernels.fast.csv index 93d1b8e2..e674b54f 100644 --- a/results/kernels.fast.csv +++ b/results/kernels.fast.csv @@ -15,18 +15,30 @@ dense,8x8xf64,snitch_stream,2693,4830,4827,0.0,0,512,706,0,0.2621611585592276,0. dense,8x8xf64,snrt,2673,4794,4791,0.0,0,512,706,0,0.26412270856715303,0.9145077720207254,772,0,0,0.2888140665918444,0,0,1.9896907216494844,1.9896907216494846,1,0.0,388,0.7744510978043913,113,0,0,0.04227459783015339,0,2122,4798,0.3310886644219978,2124 exp_macro,128xf64,snrt,2855,6196,6193,0.0,0,384,1287,0,0.4507880910683012,0.9801980198019802,1313,0,0,0.45989492119089315,0,0,11.222222222222223,11.222222222222221,1,4.47242206235012,117,0.06074766355140187,1809,1865,417,0.6336252189141857,305,3342,6200,1.093520140105079,3344 exp_macro,64xf64,snrt,1897,4593,4590,0.0,0,192,646,0,0.34053769109119664,0.9656203288490284,669,0,0,0.3526620980495519,0,0,9.422535211267606,9.422535211267606,1,4.342592592592593,71,0.06484018264840183,1024,938,216,0.5397996837111229,174,2697,4597,0.8924617817606748,2699 -exp_micro,16xf16,baseline,1636,4228,4225,0.0,0,48,225,0,0.13753056234718827,0.5844155844155844,385,0,0,0.23533007334963324,0,0,1.0,1.0,1,7.686274509803922,385,0.5099337748344371,370,392,51,0.22616136919315402,35,2593,4232,0.4614914425427873,2595 -exp_micro,16xf32,baseline,1542,4150,4147,0.0,0,48,193,0,0.1251621271076524,0.546742209631728,353,0,0,0.22892347600518806,0,0,1.0,1.0,1,7.745098039215686,353,0.4889196675900277,369,395,51,0.23929961089494164,35,2609,4154,0.4682230869001297,2611 -exp_micro,16xf64,baseline,1748,4283,4280,0.0,0,112,209,0,0.11956521739130435,0.48267898383371827,433,0,0,0.2477116704805492,0,0,1.0,1.0,1,12.35820895522388,433,0.5191846522781774,401,828,67,0.2294050343249428,35,2536,4287,0.477116704805492,2538 -exp_micro,32xf16,baseline,3236,5828,5825,0.0,0,96,449,0,0.13875154511742893,0.5838751625487646,769,0,0,0.2376390605686032,0,0,1.0,1.0,1,7.6767676767676765,769,0.5157612340710932,722,760,99,0.223114956736712,67,2593,5832,0.4607540173053152,2595 -exp_micro,32xf32,baseline,3047,5666,5663,0.0,0,96,385,0,0.1263537906137184,0.5460992907801419,705,0,0,0.23137512307187397,0,0,1.0,1.0,1,7.707070707070707,705,0.4940434477925718,722,763,99,0.2369543813587135,67,2620,5670,0.46832950443058746,2622 -exp_micro,32xf64,baseline,3467,6028,6025,0.0,0,224,417,0,0.1202768964522642,0.4820809248554913,865,0,0,0.2494952408422267,0,0,1.0,1.0,1,12.549618320610687,865,0.5239248940036342,786,1644,131,0.22670897029131815,67,2562,6032,0.47620421113354483,2564 -exp_micro,48xf16,baseline,4832,7424,7421,0.0,0,144,673,0,0.13927980132450332,0.5836947094535994,1153,0,0,0.23861754966887416,0,0,1.0,1.0,1,7.583892617449664,1153,0.4754639175257732,1272,1130,149,0.2632450331125828,101,2593,7428,0.5018625827814569,2595 -exp_micro,48xf32,baseline,4551,7175,7172,0.0,0,144,577,0,0.12678532190727312,0.5458845789971618,1057,0,0,0.23225664689079323,0,0,1.0,1.0,1,7.6938775510204085,1057,0.4960112623181605,1074,1131,147,0.23599208965062624,99,2625,7179,0.46824873654141946,2627 -exp_micro,48xf64,baseline,5189,7747,7744,0.0,0,336,625,0,0.12044709963384082,0.4818812644564379,1297,0,0,0.24995182116014647,0,0,1.0,1.0,1,12.615384615384615,1297,0.5257397648966355,1170,2460,195,0.22547697051455,99,2559,7751,0.4754287916746965,2561 -exp_micro,64xf16,baseline,6432,9024,9021,0.0,0,192,897,0,0.1394589552238806,0.5836044242029929,1537,0,0,0.23896144278606965,0,0,1.0,1.0,1,7.604060913705584,1537,0.4765891472868217,1688,1498,197,0.26243781094527363,133,2593,9028,0.5013992537313433,2595 -exp_micro,64xf32,baseline,6046,8706,8703,0.0,0,192,769,0,0.12719153159113464,0.5457771469127041,1409,0,0,0.23304664240820377,0,0,1.0,1.0,1,7.619289340101523,1409,0.45495640942847915,1688,1501,197,0.2791928547800199,133,2661,8710,0.5122394971882236,2663 -exp_micro,64xf64,baseline,6886,9458,9455,0.0,0,448,833,0,0.12097008422887016,0.4817813765182186,1729,0,0,0.2510891664246297,0,0,1.0,1.0,1,12.582375478927203,1729,0.48772919605077575,1816,3284,261,0.26372349695033404,133,2573,9462,0.5148126633749637,2575 +exp_micro,16xf16,baseline,1628,4248,4245,0.0,0,48,225,0,0.1382063882063882,0.5844155844155844,385,0,0,0.23648648648648649,0,0,1.0,1.0,1,7.686274509803922,385,0.5112881806108898,368,392,51,0.22604422604422605,35,2621,4252,0.46253071253071254,2623 +exp_micro,16xf16,linalg_xdsl_b4,428,2571,2567,0.0,0,0,73,0,0.1705607476635514,0.6347826086956522,115,0,0,0.26869158878504673,0,0,1.0,1.0,1,0.0,115,0.33724340175953077,226,0,0,0.5280373831775701,80,2144,2575,0.7967289719626168,2146 +exp_micro,16xf32,baseline,1535,4155,4152,0.0,0,48,193,0,0.1257328990228013,0.546742209631728,353,0,0,0.22996742671009773,0,0,1.0,1.0,1,7.745098039215686,353,0.4895977808599168,368,395,51,0.23973941368078175,35,2621,4159,0.4697068403908795,2623 +exp_micro,16xf32,linalg_xdsl_b4,1196,3322,3318,0.0,0,0,241,0,0.20150501672240803,0.6788732394366197,355,0,0,0.2968227424749164,0,0,1.0,1.0,1,0.0,355,0.37407797681770283,594,0,0,0.49665551839464883,224,2127,3326,0.7934782608695652,2129 +exp_micro,16xf64,baseline,1750,4321,4318,0.0,0,112,209,0,0.11942857142857143,0.48267898383371827,433,0,0,0.24742857142857144,0,0,1.0,1.0,1,12.35820895522388,433,0.5198079231692677,400,828,67,0.22857142857142856,35,2572,4325,0.476,2574 +exp_micro,16xf64,linalg_xdsl_b4,3195,5316,5312,0.0,0,0,849,0,0.26572769953051645,0.7781851512373968,1091,0,0,0.341471048513302,0,0,1.0,1.0,1,0.0,1091,0.41498668695321417,1538,0,0,0.481377151799687,480,2122,5320,0.822848200312989,2124 +exp_micro,32xf16,baseline,3229,5849,5846,0.0,0,96,449,0,0.13905233818519666,0.5838751625487646,769,0,0,0.2381542273149582,0,0,1.0,1.0,1,7.6767676767676765,769,0.5164539959704499,720,760,99,0.22297925054196346,67,2621,5853,0.46113347785692166,2623 +exp_micro,32xf16,linalg_xdsl_b4,824,2967,2963,0.0,0,0,145,0,0.17597087378640777,0.6387665198237885,227,0,0,0.27548543689320387,0,0,1.0,1.0,1,0.0,227,0.3434190620272315,434,0,0,0.5266990291262136,160,2144,2971,0.8021844660194175,2146 +exp_micro,32xf32,baseline,3039,5659,5656,0.0,0,96,385,0,0.12668641000329056,0.5460992907801419,705,0,0,0.23198420533070088,0,0,1.0,1.0,1,7.707070707070707,705,0.49473684210526314,720,763,99,0.23692003948667326,67,2621,5663,0.46890424481737414,2623 +exp_micro,32xf32,linalg_xdsl_b4,2364,4490,4486,0.0,0,0,481,0,0.20346869712351945,0.6803394625176803,707,0,0,0.2990693739424704,0,0,1.0,1.0,1,0.0,707,0.3766648907831646,1170,0,0,0.4949238578680203,448,2127,4494,0.7939932318104908,2129 +exp_micro,32xf64,baseline,3463,6039,6036,0.0,0,224,417,0,0.12041582442968525,0.4820809248554913,865,0,0,0.2497834247762056,0,0,1.0,1.0,1,12.549618320610687,865,0.5245603395997575,784,1644,131,0.22639330060641064,67,2577,6043,0.47617672538261624,2579 +exp_micro,32xf64,linalg_xdsl_b4,6363,8489,8485,0.0,0,0,1697,0,0.2666980983812667,0.778797613584213,2179,0,0,0.3424485305673424,0,0,1.0,1.0,1,0.0,2179,0.4160779071987779,3058,0,0,0.4805909162344806,960,2127,8493,0.823039446801823,2129 +exp_micro,48xf16,baseline,4832,7452,7449,0.0,0,144,673,0,0.13927980132450332,0.5836947094535994,1153,0,0,0.23861754966887416,0,0,1.0,1.0,1,7.583892617449664,1153,0.47585637639290135,1270,1130,149,0.2628311258278146,101,2621,7456,0.5014486754966887,2623 +exp_micro,48xf16,linalg_xdsl_b4,1220,3363,3359,0.0,0,0,217,0,0.1778688524590164,0.640117994100295,339,0,0,0.2778688524590164,0,0,1.0,1.0,1,0.0,339,0.345565749235474,642,0,0,0.5262295081967213,240,2144,3367,0.8040983606557377,2146 +exp_micro,48xf32,baseline,4544,7169,7166,0.0,0,144,577,0,0.1269806338028169,0.5458845789971618,1057,0,0,0.2326144366197183,0,0,1.0,1.0,1,7.6938775510204085,1057,0.4964772193518084,1072,1131,147,0.23591549295774647,99,2626,7173,0.46852992957746475,2628 +exp_micro,48xf32,linalg_xdsl_b4,3532,5663,5659,0.0,0,0,721,0,0.20413363533408835,0.6808309726156752,1059,0,0,0.29983012457531144,0,0,1.0,1.0,1,0.0,1059,0.3775401069518717,1746,0,0,0.4943374858437146,672,2132,5667,0.7941676104190261,2134 +exp_micro,48xf64,baseline,5177,7754,7751,0.0,0,336,625,0,0.12072628935677034,0.4818812644564379,1297,0,0,0.2505311956731698,0,0,1.0,1.0,1,12.615384615384615,1297,0.5261663286004057,1168,2460,195,0.2256132895499324,99,2578,7758,0.47614448522310215,2580 +exp_micro,48xf64,linalg_xdsl_b4,9531,11657,11653,0.0,0,0,2545,0,0.26702339733501207,0.7790021426385063,3267,0,0,0.34277620396600567,0,0,1.0,1.0,1,0.0,3267,0.4164435946462715,4578,0,0,0.4803273528485993,1440,2127,11661,0.823103556814605,2129 +exp_micro,64xf16,baseline,6432,9052,9049,0.0,0,192,897,0,0.1394589552238806,0.5836044242029929,1537,0,0,0.23896144278606965,0,0,1.0,1.0,1,7.604060913705584,1537,0.47688488985417316,1686,1498,197,0.2621268656716418,133,2621,9056,0.5010883084577115,2623 +exp_micro,64xf16,linalg_xdsl_b4,1616,3759,3755,0.0,0,0,289,0,0.17883663366336633,0.6407982261640798,451,0,0,0.2790841584158416,0,0,1.0,1.0,1,0.0,451,0.3466564181398924,850,0,0,0.525990099009901,320,2144,3763,0.8050742574257426,2146 +exp_micro,64xf32,baseline,6046,8659,8656,0.0,0,192,769,0,0.12719153159113464,0.5457771469127041,1409,0,0,0.23304664240820377,0,0,1.0,1.0,1,7.619289340101523,1409,0.4552504038772213,1686,1501,197,0.2788620575587165,133,2614,8663,0.5119086999669202,2616 +exp_micro,64xf32,linalg_xdsl_b4,4700,6831,6827,0.0,0,0,961,0,0.20446808510638298,0.6810772501771793,1411,0,0,0.3002127659574468,0,0,1.0,1.0,1,0.0,1411,0.37798017680150015,2322,0,0,0.4940425531914894,896,2132,6835,0.7942553191489361,2134 +exp_micro,64xf64,baseline,6878,9508,9505,0.0,0,448,833,0,0.1211107880197732,0.4817813765182186,1729,0,0,0.2513812154696133,0,0,1.0,1.0,1,12.582375478927203,1729,0.4880045159469376,1814,3284,261,0.26373945914510033,133,2631,9512,0.5151206746147137,2633 +exp_micro,64xf64,linalg_xdsl_b4,12699,14830,14826,0.0,0,0,3393,0,0.2671863926293409,0.7791044776119403,4355,0,0,0.3429403890070084,0,0,1.0,1.0,1,0.0,4355,0.4166268057017124,6098,0,0,0.48019529096779273,1920,2132,14834,0.8231356799748011,2134 fill,4x4xf64,baseline,35,2087,2084,0.0,0,0,1,0,0.02857142857142857,0.058823529411764705,17,0,0,0.4857142857142857,0,0,1.0,1.0,1,0.0,17,0.7391304347826086,6,0,0,0.17142857142857143,0,2053,2091,0.6571428571428571,2055 fill,4x4xf64,linalg,35,2087,2084,0.0,0,0,1,0,0.02857142857142857,0.058823529411764705,17,0,0,0.4857142857142857,0,0,1.0,1.0,1,0.0,17,0.7391304347826086,6,0,0,0.17142857142857143,0,2053,2091,0.6571428571428571,2055 fill,4x4xf64,linalg_xdsl,39,2088,2085,0.0,0,0,18,0,0.46153846153846156,0.9,20,0,0,0.5128205128205128,0,0,3.333333333333333,3.3333333333333335,1,0.0,6,0.3,14,0,0,0.358974358974359,0,2050,2092,0.8717948717948718,2052 diff --git a/results/kernels.softmax_polynomial.csv b/results/kernels.softmax_polynomial.csv new file mode 100644 index 00000000..a761f9e8 --- /dev/null +++ b/results/kernels.softmax_polynomial.csv @@ -0,0 +1,385 @@ +test,params,impl,cycles,end,end_fpss,fpss_avg_fpu_latency,fpss_avg_load_latency,fpss_fpu_fmadd_issues,fpss_fpu_issues,fpss_fpu_latency,fpss_fpu_occupancy,fpss_fpu_rel_occupancy,fpss_issues,fpss_load_latency,fpss_loads,fpss_occupancy,fpss_section_latency,fpss_stores,fseq_fpu_yield,fseq_yield,section,snitch_avg_load_latency,snitch_fseq_offloads,snitch_fseq_rel_offloads,snitch_issues,snitch_load_latency,snitch_loads,snitch_occupancy,snitch_stores,start,tend,total_ipc,tstart +softmax_polynomial,112xf16,linalg_xdsl_b-1,6939,9060,9057,0.0,0,0,1124,0,0.16198299466781957,0.5186894323950162,2167,0,0,0.31229283758466636,0,0,1.0,1.0,1,3.03125,2167,0.3809105290912287,3522,194,64,0.5075659316904453,717,2122,9064,0.8198587692751116,2124 +softmax_polynomial,112xf16,linalg_xdsl_b0,6603,8700,8697,0.0,0,0,1040,0,0.15750416477358775,0.5060827250608273,2055,0,0,0.3112221717401181,0,0,1.0,1.0,1,3.03125,2055,0.37992235163616195,3354,194,64,0.5079509313948205,661,2098,8704,0.8191731031349386,2100 +softmax_polynomial,112xf16,linalg_xdsl_b1,6603,8700,8697,0.0,0,0,1040,0,0.15750416477358775,0.5060827250608273,2055,0,0,0.3112221717401181,0,0,1.0,1.0,1,3.03125,2055,0.37992235163616195,3354,194,64,0.5079509313948205,661,2098,8704,0.8191731031349386,2100 +softmax_polynomial,112xf16,linalg_xdsl_b10,5585,7700,7697,0.0,0,0,788,0,0.14109221128021487,0.4584060500290867,1719,0,0,0.3077887197851388,0,0,1.0,1.0,1,3.03125,1719,0.37623112278397897,2850,194,64,0.5102954341987467,493,2116,7704,0.8180841539838855,2118 +softmax_polynomial,112xf16,linalg_xdsl_b2,6603,8700,8697,0.0,0,0,1040,0,0.15750416477358775,0.5060827250608273,2055,0,0,0.3112221717401181,0,0,1.0,1.0,1,3.03125,2055,0.37992235163616195,3354,194,64,0.5079509313948205,661,2098,8704,0.8191731031349386,2100 +softmax_polynomial,112xf16,linalg_xdsl_b3,6256,8399,8396,0.0,0,0,956,0,0.15281329923273657,0.49202264539372104,1943,0,0,0.31058184143222506,0,0,1.0,1.0,1,3.03125,1943,0.3788262819263014,3186,194,64,0.5092710997442456,605,2144,8403,0.8198529411764706,2146 +softmax_polynomial,112xf16,linalg_xdsl_b4,6256,8399,8396,0.0,0,0,956,0,0.15281329923273657,0.49202264539372104,1943,0,0,0.31058184143222506,0,0,1.0,1.0,1,3.03125,1943,0.3788262819263014,3186,194,64,0.5092710997442456,605,2144,8403,0.8198529411764706,2146 +softmax_polynomial,112xf16,linalg_xdsl_b5,6256,8399,8396,0.0,0,0,956,0,0.15281329923273657,0.49202264539372104,1943,0,0,0.31058184143222506,0,0,1.0,1.0,1,3.03125,1943,0.3788262819263014,3186,194,64,0.5092710997442456,605,2144,8403,0.8198529411764706,2146 +softmax_polynomial,112xf16,linalg_xdsl_b6,6256,8399,8396,0.0,0,0,956,0,0.15281329923273657,0.49202264539372104,1943,0,0,0.31058184143222506,0,0,1.0,1.0,1,3.03125,1943,0.3788262819263014,3186,194,64,0.5092710997442456,605,2144,8403,0.8198529411764706,2146 +softmax_polynomial,112xf16,linalg_xdsl_b7,5938,8059,8056,0.0,0,0,872,0,0.1468507915122937,0.4762424904423812,1831,0,0,0.3083529808016167,0,0,1.0,1.0,1,3.03125,1831,0.37760362961435345,3018,194,64,0.5082519366790165,549,2122,8063,0.8166049174806331,2124 +softmax_polynomial,112xf16,linalg_xdsl_b8,5938,8059,8056,0.0,0,0,872,0,0.1468507915122937,0.4762424904423812,1831,0,0,0.3083529808016167,0,0,1.0,1.0,1,3.03125,1831,0.37760362961435345,3018,194,64,0.5082519366790165,549,2122,8063,0.8166049174806331,2124 +softmax_polynomial,112xf16,linalg_xdsl_b9,5938,8059,8056,0.0,0,0,872,0,0.1468507915122937,0.4762424904423812,1831,0,0,0.3083529808016167,0,0,1.0,1.0,1,3.03125,1831,0.37760362961435345,3018,194,64,0.5082519366790165,549,2122,8063,0.8166049174806331,2124 +softmax_polynomial,112xf32,linalg_xdsl_b-1,12319,14419,14416,0.0,0,0,2298,0,0.18654111535027193,0.5976592977893368,3845,0,0,0.3121194902183619,0,0,1.0,1.0,1,3.03125,3845,0.3867042140199135,6098,194,64,0.49500771166490787,1725,2101,14423,0.8071272018832698,2103 +softmax_polynomial,112xf32,linalg_xdsl_b0,12319,14419,14416,0.0,0,0,2298,0,0.18654111535027193,0.5976592977893368,3845,0,0,0.3121194902183619,0,0,1.0,1.0,1,3.03125,3845,0.3867042140199135,6098,194,64,0.49500771166490787,1725,2101,14423,0.8071272018832698,2103 +softmax_polynomial,112xf32,linalg_xdsl_b1,11671,13792,13789,0.0,0,0,2130,0,0.182503641504584,0.5882352941176471,3621,0,0,0.3102561905577928,0,0,1.0,1.0,1,3.03125,3621,0.3859106895449217,5762,194,64,0.49370233913117983,1613,2122,13796,0.8039585296889726,2124 +softmax_polynomial,112xf32,linalg_xdsl_b10,10305,12448,12445,0.0,0,0,1794,0,0.17409024745269286,0.5653955247399937,3173,0,0,0.30790878214459,0,0,1.0,1.0,1,3.046875,3173,0.3840009681713663,5090,195,64,0.49393498301795247,1389,2144,12452,0.8018437651625425,2146 +softmax_polynomial,112xf32,linalg_xdsl_b11,10305,12448,12445,0.0,0,0,1794,0,0.17409024745269286,0.5653955247399937,3173,0,0,0.30790878214459,0,0,1.0,1.0,1,3.046875,3173,0.3840009681713663,5090,195,64,0.49393498301795247,1389,2144,12452,0.8018437651625425,2146 +softmax_polynomial,112xf32,linalg_xdsl_b12,10305,12448,12445,0.0,0,0,1794,0,0.17409024745269286,0.5653955247399937,3173,0,0,0.30790878214459,0,0,1.0,1.0,1,3.046875,3173,0.3840009681713663,5090,195,64,0.49393498301795247,1389,2144,12452,0.8018437651625425,2146 +softmax_polynomial,112xf32,linalg_xdsl_b13,9670,11791,11788,0.0,0,0,1626,0,0.16814891416752845,0.5513733468972533,2949,0,0,0.30496380558428127,0,0,1.0,1.0,1,3.03125,2949,0.3828378553810204,4754,194,64,0.49162357807652535,1277,2122,11795,0.7965873836608066,2124 +softmax_polynomial,112xf32,linalg_xdsl_b14,9670,11791,11788,0.0,0,0,1626,0,0.16814891416752845,0.5513733468972533,2949,0,0,0.30496380558428127,0,0,1.0,1.0,1,3.03125,2949,0.3828378553810204,4754,194,64,0.49162357807652535,1277,2122,11795,0.7965873836608066,2124 +softmax_polynomial,112xf32,linalg_xdsl_b15,9670,11791,11788,0.0,0,0,1626,0,0.16814891416752845,0.5513733468972533,2949,0,0,0.30496380558428127,0,0,1.0,1.0,1,3.03125,2949,0.3828378553810204,4754,194,64,0.49162357807652535,1277,2122,11795,0.7965873836608066,2124 +softmax_polynomial,112xf32,linalg_xdsl_b16,8984,11099,11096,0.0,0,0,1458,0,0.16228851291184326,0.535045871559633,2725,0,0,0.30331700801424755,0,0,1.0,1.0,1,3.03125,2725,0.38149237015259696,4418,194,64,0.49176313446126446,1165,2116,11103,0.7950801424755121,2118 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+softmax_polynomial,96xf32,linalg_xdsl_b13,8374,10495,10492,0.0,0,0,1394,0,0.16646763792691666,0.5503355704697986,2533,0,0,0.30248387867208026,0,0,1.0,1.0,1,3.03125,2533,0.38107416879795397,4114,194,64,0.49128254119894915,1101,2122,10499,0.7937664198710295,2124 +softmax_polynomial,96xf32,linalg_xdsl_b14,8374,10495,10492,0.0,0,0,1394,0,0.16646763792691666,0.5503355704697986,2533,0,0,0.30248387867208026,0,0,1.0,1.0,1,3.03125,2533,0.38107416879795397,4114,194,64,0.49128254119894915,1101,2122,10499,0.7937664198710295,2124 +softmax_polynomial,96xf32,linalg_xdsl_b15,8374,10495,10492,0.0,0,0,1394,0,0.16646763792691666,0.5503355704697986,2533,0,0,0.30248387867208026,0,0,1.0,1.0,1,3.03125,2533,0.38107416879795397,4114,194,64,0.49128254119894915,1101,2122,10499,0.7937664198710295,2124 +softmax_polynomial,96xf32,linalg_xdsl_b16,7784,9899,9896,0.0,0,0,1250,0,0.1605858170606372,0.5339598462195643,2341,0,0,0.30074511819116134,0,0,1.0,1.0,1,3.03125,2341,0.3796011026431004,3826,194,64,0.49152106885919833,1005,2116,9903,0.7922661870503597,2118 +softmax_polynomial,96xf32,linalg_xdsl_b2,10087,12208,12205,0.0,0,0,1826,0,0.18102508178844057,0.587327114827919,3109,0,0,0.3082184990581937,0,0,1.0,1.0,1,3.03125,3109,0.38444416965500183,4978,194,64,0.4935064935064935,1389,2122,12212,0.8017249925646872,2124 +softmax_polynomial,96xf32,linalg_xdsl_b3,10087,12208,12205,0.0,0,0,1826,0,0.18102508178844057,0.587327114827919,3109,0,0,0.3082184990581937,0,0,1.0,1.0,1,3.03125,3109,0.38444416965500183,4978,194,64,0.4935064935064935,1389,2122,12212,0.8017249925646872,2124 +softmax_polynomial,96xf32,linalg_xdsl_b4,10087,12208,12205,0.0,0,0,1826,0,0.18102508178844057,0.587327114827919,3109,0,0,0.3082184990581937,0,0,1.0,1.0,1,3.03125,3109,0.38444416965500183,4978,194,64,0.4935064935064935,1389,2122,12212,0.8017249925646872,2124 +softmax_polynomial,96xf32,linalg_xdsl_b5,9503,11600,11597,0.0,0,0,1682,0,0.17699673787225087,0.5766198148782996,2917,0,0,0.3069556982005682,0,0,1.0,1.0,1,3.03125,2917,0.38346260023662415,4690,194,64,0.49352835946543194,1293,2098,11604,0.8004840576660002,2100 +softmax_polynomial,96xf32,linalg_xdsl_b6,9503,11600,11597,0.0,0,0,1682,0,0.17699673787225087,0.5766198148782996,2917,0,0,0.3069556982005682,0,0,1.0,1.0,1,3.03125,2917,0.38346260023662415,4690,194,64,0.49352835946543194,1293,2098,11604,0.8004840576660002,2100 +softmax_polynomial,96xf32,linalg_xdsl_b7,9503,11600,11597,0.0,0,0,1682,0,0.17699673787225087,0.5766198148782996,2917,0,0,0.3069556982005682,0,0,1.0,1.0,1,3.03125,2917,0.38346260023662415,4690,194,64,0.49352835946543194,1293,2098,11604,0.8004840576660002,2100 +softmax_polynomial,96xf32,linalg_xdsl_b8,9503,11600,11597,0.0,0,0,1682,0,0.17699673787225087,0.5766198148782996,2917,0,0,0.3069556982005682,0,0,1.0,1.0,1,3.03125,2917,0.38346260023662415,4690,194,64,0.49352835946543194,1293,2098,11604,0.8004840576660002,2100 +softmax_polynomial,96xf32,linalg_xdsl_b9,8913,11056,11053,0.0,0,0,1538,0,0.17255693930214294,0.5644036697247706,2725,0,0,0.3057331986985302,0,0,1.0,1.0,1,3.046875,2725,0.38234881436789675,4402,195,64,0.4938853360260294,1197,2144,11060,0.7996185347245597,2146 +softmax_polynomial,96xf64,linalg_xdsl_b-1,23567,25628,25625,0.0,0,0,5762,0,0.24449442016378836,0.7285371096219497,7909,0,0,0.33559638477532144,0,0,1.0,1.0,1,3.0,7909,0.4087127280243915,11442,384,128,0.48550939873552,3169,2062,25632,0.8211057835108415,2064 +softmax_polynomial,96xf64,linalg_xdsl_b0,23567,25628,25625,0.0,0,0,5762,0,0.24449442016378836,0.7285371096219497,7909,0,0,0.33559638477532144,0,0,1.0,1.0,1,3.0,7909,0.4087127280243915,11442,384,128,0.48550939873552,3169,2062,25632,0.8211057835108415,2064 +softmax_polynomial,96xf64,linalg_xdsl_b1,23567,25628,25625,0.0,0,0,5762,0,0.24449442016378836,0.7285371096219497,7909,0,0,0.33559638477532144,0,0,1.0,1.0,1,3.0,7909,0.4087127280243915,11442,384,128,0.48550939873552,3169,2062,25632,0.8211057835108415,2064 +softmax_polynomial,96xf64,linalg_xdsl_b10,21265,23300,23297,0.0,0,0,5186,0,0.24387491182694568,0.7262288194930682,7141,0,0,0.33581001645897013,0,0,1.0,1.0,1,3.0,7141,0.4096724226951982,10290,384,128,0.4838937220785328,2785,2036,23304,0.819703738537503,2038 +softmax_polynomial,96xf64,linalg_xdsl_b11,21265,23300,23297,0.0,0,0,5186,0,0.24387491182694568,0.7262288194930682,7141,0,0,0.33581001645897013,0,0,1.0,1.0,1,3.0,7141,0.4096724226951982,10290,384,128,0.4838937220785328,2785,2036,23304,0.819703738537503,2038 +softmax_polynomial,96xf64,linalg_xdsl_b12,19929,21965,21962,0.0,0,0,4898,0,0.24577249234783483,0.7248779043954418,6757,0,0,0.33905364042350344,0,0,1.0,1.0,1,3.0078125,6757,0.4200285945173121,9330,385,128,0.4681619750112901,2593,2037,21969,0.8072156154347936,2039 +softmax_polynomial,96xf64,linalg_xdsl_b13,19929,21965,21962,0.0,0,0,4898,0,0.24577249234783483,0.7248779043954418,6757,0,0,0.33905364042350344,0,0,1.0,1.0,1,3.0078125,6757,0.4200285945173121,9330,385,128,0.4681619750112901,2593,2037,21969,0.8072156154347936,2039 +softmax_polynomial,96xf64,linalg_xdsl_b14,19929,21965,21962,0.0,0,0,4898,0,0.24577249234783483,0.7248779043954418,6757,0,0,0.33905364042350344,0,0,1.0,1.0,1,3.0078125,6757,0.4200285945173121,9330,385,128,0.4681619750112901,2593,2037,21969,0.8072156154347936,2039 +softmax_polynomial,96xf64,linalg_xdsl_b15,19929,21965,21962,0.0,0,0,4898,0,0.24577249234783483,0.7248779043954418,6757,0,0,0.33905364042350344,0,0,1.0,1.0,1,3.0078125,6757,0.4200285945173121,9330,385,128,0.4681619750112901,2593,2037,21969,0.8072156154347936,2039 +softmax_polynomial,96xf64,linalg_xdsl_b16,19929,21965,21962,0.0,0,0,4898,0,0.24577249234783483,0.7248779043954418,6757,0,0,0.33905364042350344,0,0,1.0,1.0,1,3.0078125,6757,0.4200285945173121,9330,385,128,0.4681619750112901,2593,2037,21969,0.8072156154347936,2039 +softmax_polynomial,96xf64,linalg_xdsl_b2,22405,24467,24464,0.0,0,0,5474,0,0.2443204641821022,0.7274418604651163,7525,0,0,0.33586253068511496,0,0,1.0,1.0,1,3.0,7525,0.4091675275950193,10866,384,128,0.4849810310198616,2977,2063,24471,0.8208435617049765,2065 +softmax_polynomial,96xf64,linalg_xdsl_b3,22405,24467,24464,0.0,0,0,5474,0,0.2443204641821022,0.7274418604651163,7525,0,0,0.33586253068511496,0,0,1.0,1.0,1,3.0,7525,0.4091675275950193,10866,384,128,0.4849810310198616,2977,2063,24471,0.8208435617049765,2065 +softmax_polynomial,96xf64,linalg_xdsl_b4,22405,24467,24464,0.0,0,0,5474,0,0.2443204641821022,0.7274418604651163,7525,0,0,0.33586253068511496,0,0,1.0,1.0,1,3.0,7525,0.4091675275950193,10866,384,128,0.4849810310198616,2977,2063,24471,0.8208435617049765,2065 +softmax_polynomial,96xf64,linalg_xdsl_b5,22405,24467,24464,0.0,0,0,5474,0,0.2443204641821022,0.7274418604651163,7525,0,0,0.33586253068511496,0,0,1.0,1.0,1,3.0,7525,0.4091675275950193,10866,384,128,0.4849810310198616,2977,2063,24471,0.8208435617049765,2065 +softmax_polynomial,96xf64,linalg_xdsl_b6,22405,24467,24464,0.0,0,0,5474,0,0.2443204641821022,0.7274418604651163,7525,0,0,0.33586253068511496,0,0,1.0,1.0,1,3.0,7525,0.4091675275950193,10866,384,128,0.4849810310198616,2977,2063,24471,0.8208435617049765,2065 +softmax_polynomial,96xf64,linalg_xdsl_b7,21265,23300,23297,0.0,0,0,5186,0,0.24387491182694568,0.7262288194930682,7141,0,0,0.33581001645897013,0,0,1.0,1.0,1,3.0,7141,0.4096724226951982,10290,384,128,0.4838937220785328,2785,2036,23304,0.819703738537503,2038 +softmax_polynomial,96xf64,linalg_xdsl_b8,21265,23300,23297,0.0,0,0,5186,0,0.24387491182694568,0.7262288194930682,7141,0,0,0.33581001645897013,0,0,1.0,1.0,1,3.0,7141,0.4096724226951982,10290,384,128,0.4838937220785328,2785,2036,23304,0.819703738537503,2038 +softmax_polynomial,96xf64,linalg_xdsl_b9,21265,23300,23297,0.0,0,0,5186,0,0.24387491182694568,0.7262288194930682,7141,0,0,0.33581001645897013,0,0,1.0,1.0,1,3.0,7141,0.4096724226951982,10290,384,128,0.4838937220785328,2785,2036,23304,0.819703738537503,2038 diff --git a/results/pivoted.csv b/results/pivoted.csv index 1de171e0..f437de25 100644 --- a/results/pivoted.csv +++ b/results/pivoted.csv @@ -4,18 +4,18 @@ ddot 128xf64,924,924,,177,546 dense 8x8xf64,5551,3843,,2693,2673 exp_macro 128xf64,,,,,2855 exp_macro 64xf64,,,,,1897 -exp_micro 16xf16,1636,,,, -exp_micro 16xf32,1542,,,, -exp_micro 16xf64,1748,,,, -exp_micro 32xf16,3236,,,, -exp_micro 32xf32,3047,,,, -exp_micro 32xf64,3467,,,, +exp_micro 16xf16,1628,,,, +exp_micro 16xf32,1535,,,, +exp_micro 16xf64,1750,,,, +exp_micro 32xf16,3229,,,, +exp_micro 32xf32,3039,,,, +exp_micro 32xf64,3463,,,, exp_micro 48xf16,4832,,,, -exp_micro 48xf32,4551,,,, -exp_micro 48xf64,5189,,,, +exp_micro 48xf32,4544,,,, +exp_micro 48xf64,5177,,,, exp_micro 64xf16,6432,,,, exp_micro 64xf32,6046,,,, -exp_micro 64xf64,6886,,,, +exp_micro 64xf64,6878,,,, fill 4x4xf64,35,35,39,, fill 4x8xf32,43,43,47,, matmul 4x16x8xf64,2880,2567,668,, diff --git a/results/pivoted.fast.csv b/results/pivoted.fast.csv index 1de171e0..f437de25 100644 --- a/results/pivoted.fast.csv +++ b/results/pivoted.fast.csv @@ -4,18 +4,18 @@ ddot 128xf64,924,924,,177,546 dense 8x8xf64,5551,3843,,2693,2673 exp_macro 128xf64,,,,,2855 exp_macro 64xf64,,,,,1897 -exp_micro 16xf16,1636,,,, -exp_micro 16xf32,1542,,,, -exp_micro 16xf64,1748,,,, -exp_micro 32xf16,3236,,,, -exp_micro 32xf32,3047,,,, -exp_micro 32xf64,3467,,,, +exp_micro 16xf16,1628,,,, +exp_micro 16xf32,1535,,,, +exp_micro 16xf64,1750,,,, +exp_micro 32xf16,3229,,,, +exp_micro 32xf32,3039,,,, +exp_micro 32xf64,3463,,,, exp_micro 48xf16,4832,,,, -exp_micro 48xf32,4551,,,, -exp_micro 48xf64,5189,,,, +exp_micro 48xf32,4544,,,, +exp_micro 48xf64,5177,,,, exp_micro 64xf16,6432,,,, exp_micro 64xf32,6046,,,, -exp_micro 64xf64,6886,,,, +exp_micro 64xf64,6878,,,, fill 4x4xf64,35,35,39,, fill 4x8xf32,43,43,47,, matmul 4x16x8xf64,2880,2567,668,, diff --git a/results/pivoted_ipc.csv b/results/pivoted_ipc.csv index 8879f221..5ee1d96a 100644 --- a/results/pivoted_ipc.csv +++ b/results/pivoted_ipc.csv @@ -15,7 +15,7 @@ exp_micro 48xf32,0.47,,,, exp_micro 48xf64,0.48,,,, exp_micro 64xf16,0.50,,,, exp_micro 64xf32,0.51,,,, -exp_micro 64xf64,0.51,,,, +exp_micro 64xf64,0.52,,,, fill 4x4xf64,0.66,0.66,0.87,, fill 4x8xf32,0.91,0.91,0.72,, matmul 4x16x8xf64,0.63,0.56,0.98,, diff --git a/results/pivoted_ipc.fast.csv b/results/pivoted_ipc.fast.csv index 8879f221..5ee1d96a 100644 --- a/results/pivoted_ipc.fast.csv +++ b/results/pivoted_ipc.fast.csv @@ -15,7 +15,7 @@ exp_micro 48xf32,0.47,,,, exp_micro 48xf64,0.48,,,, exp_micro 64xf16,0.50,,,, exp_micro 64xf32,0.51,,,, -exp_micro 64xf64,0.51,,,, +exp_micro 64xf64,0.52,,,, fill 4x4xf64,0.66,0.66,0.87,, fill 4x8xf32,0.91,0.91,0.72,, matmul 4x16x8xf64,0.63,0.56,0.98,, From d60f9b1811afdaeb6cd2939d7bd0a90c6825ccd6 Mon Sep 17 00:00:00 2001 From: szerdick Date: Sat, 30 May 2026 09:29:40 +0100 Subject: [PATCH 24/33] renamed plots, and small modifications, new plots for actuall error --- Snakefile | 29 ++-- .../output/{rq31_plots.pdf => rq11_plots.pdf} | Bin 20604 -> 20624 bytes plots-mia-thesis/output/rq12_plots.pdf | Bin 0 -> 81169 bytes plots-mia-thesis/output/rq13_plots.pdf | Bin 0 -> 107720 bytes plots-mia-thesis/output/rq1_plots.pdf | Bin 23351 -> 23699 bytes plots-mia-thesis/output/rq32_plots.pdf | Bin 80469 -> 0 bytes plots-mia-thesis/plot_rq1.py | 24 ++- .../{plot_rq31.py => plot_rq11.py} | 10 +- .../{plot_rq32.py => plot_rq12.py} | 10 +- plots-mia-thesis/plot_rq13.py | 140 ++++++++++++++++++ plots-mia-thesis/plot_rq42.py | 4 +- plots-mia-thesis/plot_utils.py | 73 ++++++++- 12 files changed, 266 insertions(+), 24 deletions(-) rename plots-mia-thesis/output/{rq31_plots.pdf => rq11_plots.pdf} (74%) create mode 100644 plots-mia-thesis/output/rq12_plots.pdf create mode 100644 plots-mia-thesis/output/rq13_plots.pdf delete mode 100644 plots-mia-thesis/output/rq32_plots.pdf rename plots-mia-thesis/{plot_rq31.py => plot_rq11.py} (88%) rename plots-mia-thesis/{plot_rq32.py => plot_rq12.py} (92%) create mode 100644 plots-mia-thesis/plot_rq13.py diff --git a/Snakefile b/Snakefile index 829608cc..f49f428b 100644 --- a/Snakefile +++ b/Snakefile @@ -1007,26 +1007,36 @@ rule plot_rq1: utils = PLOTS_DIR + "/plot_utils.py", micro = "results/kernels.exp_micro.csv", poly = "results/kernels.exp_polynomial.csv", + macro = "results/kernels.exp_macro.csv", output: PLOTS_OUTPUT + "/rq1_plots.pdf", shell: - "python {input.script} --exp-micro {input.micro} --exp-polynomial {input.poly} -o {output}" + "python {input.script} --exp-micro {input.micro} --exp-polynomial {input.poly} --exp-macro {input.macro} -o {output}" -rule plot_rq31: +rule plot_rq11: input: - script = PLOTS_DIR + "/plot_rq31.py", + script = PLOTS_DIR + "/plot_rq11.py", utils = PLOTS_DIR + "/plot_utils.py", output: - PLOTS_OUTPUT + "/rq31_plots.pdf", + PLOTS_OUTPUT + "/rq11_plots.pdf", shell: "python {input.script} -o {output}" -rule plot_rq32: +rule plot_rq12: input: - script = PLOTS_DIR + "/plot_rq32.py", + script = PLOTS_DIR + "/plot_rq12.py", utils = PLOTS_DIR + "/plot_utils.py", output: - PLOTS_OUTPUT + "/rq32_plots.pdf", + PLOTS_OUTPUT + "/rq12_plots.pdf", + shell: + "python {input.script} -o {output}" + +rule plot_rq13: + input: + script = PLOTS_DIR + "/plot_rq13.py", + utils = PLOTS_DIR + "/plot_utils.py", + output: + PLOTS_OUTPUT + "/rq13_plots.pdf", shell: "python {input.script} -o {output}" @@ -1081,8 +1091,9 @@ rule plot_rq42: rule plots_mia_thesis: input: PLOTS_OUTPUT + "/rq1_plots.pdf", - PLOTS_OUTPUT + "/rq31_plots.pdf", - PLOTS_OUTPUT + "/rq32_plots.pdf", + PLOTS_OUTPUT + "/rq11_plots.pdf", + PLOTS_OUTPUT + "/rq12_plots.pdf", + PLOTS_OUTPUT + "/rq13_plots.pdf", PLOTS_OUTPUT + "/rq33_plots.pdf", PLOTS_OUTPUT + "/rq34_plots.pdf", PLOTS_OUTPUT + "/rq41_plots.pdf", diff --git a/plots-mia-thesis/output/rq31_plots.pdf b/plots-mia-thesis/output/rq11_plots.pdf similarity index 74% rename from plots-mia-thesis/output/rq31_plots.pdf rename to plots-mia-thesis/output/rq11_plots.pdf index acf887b3f335ebdf6329ec806f3eb89d282b6b76..61b79ecbe997c90fd8ff1668a92830707c9d3219 100644 GIT binary patch delta 5313 zcmZWqcRZE-`_HNn;z3r~o8#gU zYZFY7`TwE 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pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: +def plot_rq1( + poly_df: pd.DataFrame, + baseline_df: pd.DataFrame, + vendor_df: pd.DataFrame, +) -> plt.Figure: fig, axes = plt.subplots(2, len(PRECISIONS), figsize=(len(PRECISIONS) * 5, 8)) metrics = [ @@ -56,6 +64,7 @@ def plot_rq1(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: ax = axes[row_idx, col_idx] series = avg_per_degree(poly_df, precision, metric) baseline = avg_baseline(baseline_df, precision, metric) + vendor = avg_baseline(vendor_df, precision, metric) if not series.empty: ax.plot( @@ -68,6 +77,12 @@ def plot_rq1(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: baseline, color="#1f78b4", linestyle="--", label=f"libm baseline ({baseline:.3g})", ) + # vendor kernel (snrt) is only measured in f64 -> NaN elsewhere + if not np.isnan(vendor): + ax.axhline( + vendor, color="#e31a1c", linestyle="-.", + label=f"vendor kernel ({vendor:.3g})", + ) ax.set_title(f"{precision}") ax.set_xlabel("Chebyshev degree") @@ -91,6 +106,10 @@ def main() -> None: "--exp-polynomial", default="results/kernels.exp_polynomial.csv", help="Input CSV with Chebyshev polynomial degree-variant measurements", ) + parser.add_argument( + "--exp-macro", default="results/kernels.exp_macro.csv", + help="Input CSV with vendor kernel (snrt) measurements", + ) parser.add_argument( "--output", "-o", default="plots-mia-thesis/output/rq1_plots.pdf", help="Output plot file", @@ -101,8 +120,9 @@ def main() -> None: poly_df = load_chebyshev_csv(args.exp_polynomial) baseline_df = load_baseline_csv(args.exp_micro) + vendor_df = load_vendor_csv(args.exp_macro) - fig = plot_rq1(poly_df, baseline_df) + fig = plot_rq1(poly_df, baseline_df, vendor_df) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq31.py b/plots-mia-thesis/plot_rq11.py similarity index 88% rename from plots-mia-thesis/plot_rq31.py rename to plots-mia-thesis/plot_rq11.py index a2aaf533..c237220f 100644 --- a/plots-mia-thesis/plot_rq31.py +++ b/plots-mia-thesis/plot_rq11.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """ -RQ31 plot: signed approximation error p_d(x) - exp(x) on the interval +RQ11 plot: signed approximation error p_d(x) - exp(x) on the interval [CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER] for each Chebyshev degree d in XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS. @@ -10,7 +10,7 @@ to what the xDSL pipeline emits. Usage: - python plot_rq31.py [--output plots-mia-thesis/output/rq31_plots.pdf] + python plot_rq11.py [--output plots-mia-thesis/output/rq11_plots.pdf] """ import argparse @@ -31,7 +31,7 @@ ) -def plot_rq31() -> plt.Figure: +def plot_rq11() -> plt.Figure: x = np.linspace(CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, 2001) exp_x = np.exp(x) @@ -60,13 +60,13 @@ def plot_rq31() -> plt.Figure: def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument( - "--output", "-o", default="plots-mia-thesis/output/rq31_plots.pdf", + "--output", "-o", default="plots-mia-thesis/output/rq11_plots.pdf", help="Output plot file", ) args = parser.parse_args() Path(args.output).parent.mkdir(parents=True, exist_ok=True) - fig = plot_rq31() + fig = plot_rq11() savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq32.py b/plots-mia-thesis/plot_rq12.py similarity index 92% rename from plots-mia-thesis/plot_rq32.py rename to plots-mia-thesis/plot_rq12.py index 097dcc5d..e8423a7f 100644 --- a/plots-mia-thesis/plot_rq32.py +++ b/plots-mia-thesis/plot_rq12.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """ -RQ32 plot: bits of mantissa lost by the Chebyshev approximation, per precision. +RQ12 plot: bits of mantissa lost by the Chebyshev approximation, per precision. For each precision (f16, f32, f64) and each degree d we compute ulp_err(x) = |approx_DTYPE(x) − exp_rn_DTYPE(x)| / ulp_DTYPE(exp_rn(x)) @@ -17,7 +17,7 @@ libm's residual roundoff. Use mpmath for a strictly-correct f64 reference. Usage: - python plot_rq32.py [--output plots-mia-thesis/output/rq32_plots.pdf] + python plot_rq12.py [--output plots-mia-thesis/output/rq12_plots.pdf] """ import argparse @@ -42,7 +42,7 @@ ) -def plot_rq32(xmin: float, xmax: float, npoints: int) -> plt.Figure: +def plot_rq12(xmin: float, xmax: float, npoints: int) -> plt.Figure: x = np.linspace(xmin, xmax, npoints) exp_true = np.exp(x.astype(np.float64)) # high-precision reference value @@ -92,7 +92,7 @@ def plot_rq32(xmin: float, xmax: float, npoints: int) -> plt.Figure: def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument( - "--output", "-o", default="plots-mia-thesis/output/rq32_plots.pdf", + "--output", "-o", default="plots-mia-thesis/output/rq12_plots.pdf", help="Output plot file", ) parser.add_argument( @@ -110,7 +110,7 @@ def main() -> None: args = parser.parse_args() Path(args.output).parent.mkdir(parents=True, exist_ok=True) - fig = plot_rq32(args.xmin, args.xmax, args.npoints) + fig = plot_rq12(args.xmin, args.xmax, args.npoints) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq13.py b/plots-mia-thesis/plot_rq13.py new file mode 100644 index 00000000..f8c099ec --- /dev/null +++ b/plots-mia-thesis/plot_rq13.py @@ -0,0 +1,140 @@ +#!/usr/bin/env python3 +""" +RQ13 plot: bits of mantissa lost by the Chebyshev approximation *as the +compiler actually evaluates it*, per precision. + +This is the realised-error twin of plot_rq12.py. Where plot_rq12 sums the +Chebyshev series in f64 and rounds only the final value (it measures the +mathematical error of the polynomial), this plot reproduces the exact +arithmetic emitted by the xDSL lowering + + math.exp --lower-exp-to-polynomial--> polynomial.eval + --expand-polynomial-eval---> arith.{mulf,addf,subf} + +i.e. Clenshaw's recurrence with the domain map, the constant 2.0, every +Chebyshev coefficient and c_0/2 materialised as arith.constants of the element +type (rounded to the precision) and *every* mul/add/sub rounded back to the +precision. The Chebyshev-Lobatto coefficients carried by the `polynomial.eval` +op are the same ones plot_rq12 uses; the only difference is how they are +evaluated. eval_chebyshev_clenshaw_lowered has been validated +bit-for-bit against running `expand-polynomial-eval` on the generated IR. + +For each precision (f16, f32, f64) and each degree d we compute + ulp_err(x) = |approx_DTYPE(x) − exp_rn_DTYPE(x)| / ulp_DTYPE(exp_rn(x)) +and plot + bits_lost(x) = log2(ulp_err(x)). + +bits_lost = 0 → 1 ULP off (last representable step from the correctly-rounded + result; precision floor). +bits_lost = k → bottom k bits of the mantissa are unreliable. +bits_lost = mantissa_bits[prec] → all precision gone. + +NOTE: the f64 reference is computed via np.exp(f64), itself accurate to ~1 +ULP, so the lowest bits_lost values for f64 conflate polynomial/roundoff error +with libm's residual roundoff. Use mpmath for a strictly-correct f64 reference. + +Usage: + python plot_rq13.py [--output plots-mia-thesis/output/rq13_plots.pdf] +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from plot_utils import ( + CHEBYSHEV_DEGREES, + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + DEGREE_COLORS, + DEGREE_LINESTYLES, + PRECISION_MANTISSA_BITS, + PRECISION_NUMPY_DTYPE, + PRECISIONS, + chebyshev_lobatto_coeffs, + eval_chebyshev_clenshaw_lowered, + savefig, + ulp, +) + + +def plot_rq13(xmin: float, xmax: float, npoints: int) -> plt.Figure: + x = np.linspace(xmin, xmax, npoints) + exp_true = np.exp(x.astype(np.float64)) # high-precision reference value + + fig, axes = plt.subplots(1, len(PRECISIONS), figsize=(len(PRECISIONS) * 5, 5)) + + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[col_idx] + dtype = PRECISION_NUMPY_DTYPE[precision] + exp_rn = exp_true.astype(dtype) # correctly-rounded reference + ulp_rn = ulp(exp_true, precision) # ulp(exp_rn) in DTYPE + mantissa_bits = PRECISION_MANTISSA_BITS[precision] + for d in CHEBYSHEV_DEGREES: + # evaluate exactly as the lowering passes do, in the element type + approx = eval_chebyshev_clenshaw_lowered( + chebyshev_lobatto_coeffs(d), x, precision + ) + ulp_err = np.abs( + approx.astype(np.float64) - exp_rn.astype(np.float64) + ) / ulp_rn + with np.errstate(divide="ignore"): + bits_lost = np.log2(ulp_err) + # exact matches → -inf; drop them so the line is broken there + bits_lost = np.where(np.isfinite(bits_lost), bits_lost, np.nan) + ax.plot( + x, bits_lost, + color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], + linewidth=0.8, + label=f"d={d}", + ) + + ax.axhline(0.0, color="black", linestyle="--", linewidth=0.8, + label="1 ULP (0 bits lost)") + ax.axhline(mantissa_bits, color="red", linestyle="--", linewidth=0.8, + label=f"all mantissa bits lost") + ax.set_ylim(-2, mantissa_bits + 4) + ax.set_xlabel("x") + ax.set_title(precision) + ax.grid(True, which="both", alpha=0.3) + + axes[0].set_ylabel(r"bits lost $=\log_2(|\mathrm{ULP\ error}|)$") + axes[-1].legend(ncol=2, fontsize=7, loc="best") + fig.suptitle( + f"Chebyshev approximation (as lowered): mantissa bits lost vs " + f"correctly-rounded exp on [{xmin}, {xmax}]" + ) + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq13_plots.pdf", + help="Output plot file", + ) + parser.add_argument( + "--xmin", type=float, default=CHEBYSHEV_DOMAIN_LOWER, + help="Left edge of x window", + ) + parser.add_argument( + "--xmax", type=float, default=CHEBYSHEV_DOMAIN_UPPER, + help="Right edge of x window", + ) + parser.add_argument( + "--npoints", type=int, default=2001, + help="Number of x samples in the window", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_rq13(args.xmin, args.xmax, args.npoints) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_rq42.py b/plots-mia-thesis/plot_rq42.py index 0e8126d8..f9472d38 100644 --- a/plots-mia-thesis/plot_rq42.py +++ b/plots-mia-thesis/plot_rq42.py @@ -20,7 +20,7 @@ Caveat: the float64 reference is itself ~1 ULP off correctly-rounded for f64; the bottom of the f64 accuracy curve conflates polynomial error with -libm's residual roundoff (same caveat as plot_rq32). +libm's residual roundoff (same caveat as plot_rq12). Usage: python plot_rq42.py [-i results/kernels.softmax_polynomial.csv] \\ @@ -80,7 +80,7 @@ def softmax_approx(x: np.ndarray, degree: int, precision: str) -> np.ndarray: s = sum(e) (in dtype) z = e / s (in dtype) Polynomial eval is done in float64 and cast to dtype — same approach - plot_rq32 uses; the kernel's Clenshaw eval in DTYPE differs slightly but + plot_rq12 uses; the kernel's Clenshaw eval in DTYPE differs slightly but not enough to matter for the translation question.""" dtype = PRECISION_NUMPY_DTYPE[precision] x = x.astype(dtype) diff --git a/plots-mia-thesis/plot_utils.py b/plots-mia-thesis/plot_utils.py index 82e75e97..adf3d6c4 100644 --- a/plots-mia-thesis/plot_utils.py +++ b/plots-mia-thesis/plot_utils.py @@ -62,7 +62,7 @@ # Regex matching the variant names in XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS. CHEBYSHEV_DEGREE_RE: re.Pattern[str] = re.compile(r"linalg_xdsl_d(\d+)$") -# One (color, linestyle) per Chebyshev degree — used by plot_rq31 / plot_rq3 to +# One (color, linestyle) per Chebyshev degree — used by plot_rq11 / plot_rq3 to # keep curves directly comparable across plots. There are 11 degrees but only # 8 colors in the project palette, so we cycle the colors and switch to a # dashed style on wrap-around — every (color, linestyle) pair is unique. @@ -117,6 +117,66 @@ def eval_chebyshev(coeffs: Sequence[float], x: np.ndarray) -> np.ndarray: return result +def eval_chebyshev_clenshaw_lowered( + coeffs: Sequence[float], + x: np.ndarray, + precision: str, + domain_lower: float = CHEBYSHEV_DOMAIN_LOWER, + domain_upper: float = CHEBYSHEV_DOMAIN_UPPER, +) -> np.ndarray: + """Evaluate the Chebyshev series the way the xDSL lowering actually does. + + Mirrors, bit-for-bit, the arithmetic emitted by the two passes + `lower-exp-to-polynomial` -> `expand-polynomial-eval` (function + `expand_clenshaw` in xdsl/transforms/expand_polynomial_eval.py): + + * `coeffs` are the *double-precision* Chebyshev-Lobatto coefficients + carried by the `polynomial.eval` op (see `chebyshev_lobatto_coeffs` — + the same DCT-I values the Snakefile bakes into the IR); + * the domain-map scale/offset, the constant 2.0, every coefficient and + `coeffs[0]/2` are materialised as `arith.constant`s of the *element + type*, i.e. each is rounded to `precision` (exactly what `FloatAttr` + does); + * every `mulf`/`addf`/`subf` rounds its result back to `precision`. + + Unlike `eval_chebyshev` (which sums the double-prime series in f64 and only + rounds the final result), this reproduces the rounding error introduced at + every operation, so it measures the error of the code the compiler emits. + + Validated bit-identical to running `expand-polynomial-eval` on the + generated IR for f16/f32/f64 and degrees 2..12 across [domain_lower, + domain_upper]. + """ + dtype = PRECISION_NUMPY_DTYPE[precision] + R = lambda v: dtype(v) # round a python float to the element type # noqa: E731 + xt = np.asarray(x, dtype=dtype) + n = len(coeffs) - 1 + + # domain map: t = x * scale + offset (each op in the element type) + scale = R(2.0 / (domain_upper - domain_lower)) + offset = R(-(domain_upper + domain_lower) / (domain_upper - domain_lower)) + scaled = (xt * scale).astype(dtype) + t = (scaled + offset).astype(dtype) + + # Clenshaw recurrence, all arithmetic in the element type + two = R(2.0) + two_t = (two * t).astype(dtype) + b_prev2 = np.full_like(xt, R(0.0)) # b_{n+2} + b_prev1 = np.full_like(xt, R(0.0)) # b_{n+1} + for k in range(n, 0, -1): + c_k = R(coeffs[k]) + two_t_b = (two_t * b_prev1).astype(dtype) + sub = (two_t_b - b_prev2).astype(dtype) + b_k = (sub + c_k).astype(dtype) + b_prev2, b_prev1 = b_prev1, b_k + + # final: result = c_0/2 + t * b_1 - b_2 + c0_half = R(coeffs[0] / 2.0) + t_b1 = (t * b_prev1).astype(dtype) + add = (c0_half + t_b1).astype(dtype) + return (add - b_prev2).astype(dtype) + + def ulp(values: np.ndarray, precision: str) -> np.ndarray: """ULP of each value, evaluated in the given precision (f16/f32/f64).""" dtype = PRECISION_NUMPY_DTYPE[precision] @@ -157,6 +217,17 @@ def load_baseline_csv(csv_path: str) -> pd.DataFrame: return annotate_kernel_df(df) +def load_vendor_csv(csv_path: str) -> pd.DataFrame: + """Load exp_macro measurements and keep only the vendor kernel (snrt) rows. + + The vendor kernel is only measured in f64, so the returned frame contains + f64 rows only. + """ + df = pd.read_csv(csv_path) + df = df[df["impl"] == "snrt"].copy() + return annotate_kernel_df(df) + + ########################################################### # Existing project plotting infrastructure ########################################################### From b539c5db7f13340a703b1d1ffb63af05fd8ecde1 Mon Sep 17 00:00:00 2001 From: szerdick Date: Sun, 31 May 2026 23:52:50 +0100 Subject: [PATCH 25/33] add more plots for rq4 --- plots-mia-thesis/output/rq40_plots.pdf | Bin 0 -> 20898 bytes plots-mia-thesis/plot_rq40.py | 256 +++++++++++++++++++++++++ 2 files changed, 256 insertions(+) create mode 100644 plots-mia-thesis/output/rq40_plots.pdf create mode 100644 plots-mia-thesis/plot_rq40.py diff --git a/plots-mia-thesis/output/rq40_plots.pdf b/plots-mia-thesis/output/rq40_plots.pdf new file mode 100644 index 0000000000000000000000000000000000000000..c94fed491b096cd062e310bfcbe73de3e7e11ce7 GIT binary patch literal 20898 zcmd^nby!tP^r*CSmk1n0MDi5p&J#qR1u_Aq&pR)K|nxSQ9^{b z59+-JzjyuK_x^hC;J9b6J+Wr3wP(f5Y&JD186GGv9|2p*1gN-{01ASDoXxKih=_o| zTHY>JAh4tv%FMyp1_V|!v$1jm!GHo9ATcolD*Y#P%}fJtX!Qy2=pxhSku%3&qCKF(Jz%>`j|;nKR)P64_v+3@?zxf67aw3-PL=u(<^}u4^{%H{12-vk5aBik!BWY zBgeRrG4t~qH@)^vp2TPS9=<2@S(8*s-rQ@MZCj7MKJj%z^r&fer;jCS2}k|TLED0R z=%Y(}>kE%)Z|&_iwT!2;k2p`=tY3caJ96XJt{CFo3deh8<_el&Wd+Oo@&g2_>gr%$ z8^nI%V^m#SwmFT4CCiISUiD8Z*g5Y$10|Ay63Jw~IRPUVt>$Qq=5N-@ariJ+M7ssj z4dyB(78XQOJ-^b}kdc)#buMa5{j8Sk*u_Z)8T!EsDv^cUQLr1^171`)!Vkl9JgM5= zh+VaCchZm|<`ZXGV* zA$u)gmAKWA`P~JpT;+^2ntErWp^TDRRGmYNBQ4j2?@(Gi%5b^B&%x^W7O44FYNY9D zL}ALrxu|K?vuv}&cA+bp@pOadRT2v?M#a^V4%_hrpQm*<%6Ob3aE2)@L1_M;c8PaX z6~SuU4z6x*qu%Pi9-pc2QSOvW7eM4c5orCS5Xn1pfnRog=`0tiY)_VFpK_W%(y>#- z$|_?Shr0}+(xR*$I58lqgYjyt@7lsajdC)Dq8@dG1zkq&n5ETxlo(W|SFF*y2Tlm@ z&y^2;P(pwUv3LKl+kBx)W_^jwKF^mn0OpD&Pemb=`nCVs8lpC-eCoC`Q`y7-+c56E z)FG93NPq};0U|Iu`f@~MYq-W+uzGHXJq@-GnMKV1^Dx4U%Afs_b9#@SKubhtt#R7@ z&?BBo#-+Q^=#%K1ofR&TFSZ)>esU4#Mut! zP;(0h_FEYI)4Q3A42BM);Kf8Q{z=-h2k?^YJluMonbN+k2eNb2Db#EA-OAM}wB{R; 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for f16, via f32 like + softmax.c's __divsf3 fallback) + z_i = e_i * inv (DTYPE) + +Two runs differ only in `exp_target`: + reference: exp(x_i - m) computed in f64, rounded to DTYPE + (correctly-rounded libm exp at the target precision). + approximated: degree-d Chebyshev-Lobatto interpolant on [-2, 0] + evaluated *exactly as the xDSL passes lower it* — + same arithmetic as plot_rq13's + eval_chebyshev_clenshaw_lowered (every coefficient + rounded to DTYPE, every mul/add/sub rounded back to + DTYPE). The degree d is the one the pass picks at + this (precision, max_bits_lost) — see plot_rq34's + chosen_degree. + +Per (precision, max_bits_lost) we draw `samples` input vectors of size +`n` from uniform(-1, 1) (same distribution as +softmax_polynomial/gendata.py), compute + + ulp_err_i = |approx_i - ref_i| / ulp_DTYPE(ref_i) + +per output element, average across elements and across vectors, then +report + + bits_lost = log2(max(1, mean ulp_err)) + +so the floor of 0 bits corresponds to "within 1 ULP of the reference" +(matches plot_rq42's convention). + +f16 cap: XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 drops bN with N >= 11 +because f16 has 11 mantissa bits and the pass's Chebyshev fit becomes +degenerate (degree 0 -> ZeroDivisionError). We mirror that by skipping +those points on the f16 curve. + +Usage: + python plot_rq40.py [--n 64] [--samples 100] [--seed 0] \\ + [-o plots-mia-thesis/output/rq40_plots.pdf] +""" + +import argparse +import math as pymath +from functools import lru_cache +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from plot_rq34 import chosen_degree +from plot_utils import ( + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + PRECISION_MANTISSA_BITS, + PRECISION_NUMPY_DTYPE, + PRECISIONS, + chebyshev_lobatto_coeffs, + eval_chebyshev_clenshaw_lowered, + savefig, + ulp, +) + + +# Full XDSL_LINALG_MAX_BITS_LOST_VARIANTS range from the Snakefile. +BITS_LOST_VALUES: list[int] = list(range(-1, 17)) +# f16: snakefile's XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 keeps only N < 11. +F16_BITS_LOST_CAP = 11 + +DEFAULT_N = 64 +DEFAULT_SAMPLES = 100 +DEFAULT_SEED = 0 + +REF_COLOR = "#e31a1c" +IDEAL_COLOR = "#000000" +MANTISSA_LIMIT_COLOR = "#827b7b" + + +@lru_cache(maxsize=None) +def _cached_coeffs(degree: int) -> tuple[float, ...]: + return tuple(chebyshev_lobatto_coeffs(degree)) + + +def _seq_sum(e: np.ndarray, precision: str) -> np.ndarray: + """Sequential sum in DTYPE, matching softmax.c's `s += e[i];` loop.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + s = dtype(0) + for v in e: + s = dtype(s + dtype(v)) + return s + + +def _reciprocal(s: np.ndarray, precision: str) -> np.ndarray: + """1/s as softmax.c does it: f32-emulated for f16 (__divsf3), DTYPE-native otherwise.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + if precision == "f16": + return dtype(np.float32(1.0) / np.float32(s)) + return dtype(dtype(1.0) / s) + + +def _softmax_finish(e: np.ndarray, precision: str) -> np.ndarray: + """Steps 2b/3 of softmax.c: sum(e), 1/s, e *= inv_s.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + s = _seq_sum(e, precision) + inv = _reciprocal(s, precision) + return (e * inv).astype(dtype) + + +def softmax_reference(x: np.ndarray, precision: str) -> np.ndarray: + """softmax.c arithmetic in DTYPE with exp replaced by correctly-rounded + libm exp at the target precision (computed in f64, rounded to DTYPE).""" + dtype = PRECISION_NUMPY_DTYPE[precision] + xd = x.astype(dtype) + m = xd.max() + xp = (xd - m).astype(dtype) + e = np.exp(xp.astype(np.float64)).astype(dtype) + return _softmax_finish(e, precision) + + +def softmax_approx(x: np.ndarray, degree: int, precision: str) -> np.ndarray: + """softmax.c arithmetic in DTYPE with exp replaced by the Chebyshev + approximation as the xDSL passes lower it (same lowered Clenshaw as + plot_rq13). The degree is the one the pass picks at this + (precision, max_bits_lost).""" + dtype = PRECISION_NUMPY_DTYPE[precision] + xd = x.astype(dtype) + m = xd.max() + xp = (xd - m).astype(dtype) + coeffs = list(_cached_coeffs(degree)) + e = eval_chebyshev_clenshaw_lowered(coeffs, xp, precision) + return _softmax_finish(e, precision) + + +def per_vector_mean_ulp_err( + x: np.ndarray, degree: int, precision: str, +) -> float: + """Average over output elements of |approx_i - ref_i| / ulp(ref_i).""" + approx = softmax_approx(x, degree, precision).astype(np.float64) + ref = softmax_reference(x, precision).astype(np.float64) + ulps = ulp(ref, precision) + diff = np.abs(approx - ref) + with np.errstate(divide="ignore", invalid="ignore"): + ulp_err = diff / ulps + ulp_err = np.where(np.isfinite(ulp_err), ulp_err, 0.0) + return float(ulp_err.mean()) + + +def measure_bits_lost( + precision: str, bits_lost: int, n: int, samples: int, seed: int, +) -> float | None: + if precision == "f16" and bits_lost >= F16_BITS_LOST_CAP: + return None + mantissa = PRECISION_MANTISSA_BITS[precision] + degree, _ = chosen_degree( + bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa, + ) + rng = np.random.default_rng(np.uint64(seed) ^ np.uint64(bits_lost & 0xFFFF)) + errs = [ + per_vector_mean_ulp_err(rng.uniform(-1.0, 1.0, n), degree, precision) + for _ in range(samples) + ] + return pymath.log2(max(1.0, float(np.mean(errs)))) + + +def plot_rq40(n: int, samples: int, seed: int) -> plt.Figure: + fig, axes = plt.subplots( + 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 5.0, 4.5), + ) + for col, precision in enumerate(PRECISIONS): + ax = axes[col] + mantissa = PRECISION_MANTISSA_BITS[precision] + + xs: list[int] = [] + ys: list[float] = [] + for b in BITS_LOST_VALUES: + v = measure_bits_lost(precision, b, n, samples, seed) + if v is None: + continue + xs.append(b) + ys.append(v) + + ax.plot( + xs, ys, + marker="o", linestyle="-", color=REF_COLOR, + label="measured softmax error", + ) + ideal_y = np.maximum(np.array(xs, dtype=float), 0.0) + ax.plot( + xs, ideal_y, + color=IDEAL_COLOR, linestyle=":", linewidth=1.0, + label="User-specified bound (max_bits_lost)", + ) + ax.axhline( + mantissa, + color=MANTISSA_LIMIT_COLOR, linestyle="--", linewidth=0.8, + label="all mantissa bits lost", + ) + + ax.set_xticks(BITS_LOST_VALUES) + ax.set_xlim(BITS_LOST_VALUES[0] - 0.5, BITS_LOST_VALUES[-1] + 0.5) + ax.set_ylim(-1, mantissa + 4) + ax.set_xlabel( + r"User-specified exp accuracy bound (max bits lost, looser $\rightarrow$)" + ) + ax.set_title(precision) + ax.grid(True, alpha=0.3) + if col == 0: + ax.set_ylabel( + r"measured bits lost $=\log_2(\max(1,\,\overline{\mathrm{ULP\ error}}))$" + ) + ax.legend(loc="best", fontsize=7) + + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--n", type=int, default=DEFAULT_N, + help="Size of each sample input vector", + ) + parser.add_argument( + "--samples", type=int, default=DEFAULT_SAMPLES, + help="Number of sample input vectors per (precision, max_bits_lost)", + ) + parser.add_argument( + "--seed", type=int, default=DEFAULT_SEED, + help="Base seed for input-vector sampling", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq40_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_rq40(args.n, args.samples, args.seed) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() From 258666b746f3f1c105afe0b165a925a5d187de0a Mon Sep 17 00:00:00 2001 From: szerdick Date: Mon, 1 Jun 2026 14:34:21 +0100 Subject: [PATCH 26/33] name change for the rq plots, added new rq4 plots --- Snakefile | 40 ++- .../softmax_polynomial/baseline.c.template | 24 ++ kernels/softmax_polynomial/data.h.template | 3 + .../output/{rq35_plots.pdf => rq2_plots.pdf} | Bin 20179 -> 20149 bytes plots-mia-thesis/output/rq43_plots.pdf | Bin 0 -> 20412 bytes plots-mia-thesis/output/rq44_plots.pdf | Bin 0 -> 22284 bytes .../{plot_rq35.py => plot_rq2.py} | 12 +- plots-mia-thesis/plot_rq42.py | 8 +- plots-mia-thesis/plot_rq43.py | 138 ++++++++++ plots-mia-thesis/plot_rq44.py | 242 ++++++++++++++++++ 10 files changed, 453 insertions(+), 14 deletions(-) create mode 100644 kernels/softmax_polynomial/baseline.c.template rename plots-mia-thesis/output/{rq35_plots.pdf => rq2_plots.pdf} (71%) create mode 100644 plots-mia-thesis/output/rq43_plots.pdf create mode 100644 plots-mia-thesis/output/rq44_plots.pdf rename plots-mia-thesis/{plot_rq35.py => plot_rq2.py} (90%) create mode 100644 plots-mia-thesis/plot_rq43.py create mode 100644 plots-mia-thesis/plot_rq44.py diff --git a/Snakefile b/Snakefile index f49f428b..1c676c13 100644 --- a/Snakefile +++ b/Snakefile @@ -308,6 +308,13 @@ TESTSET_SOFTMAX_POLYNOMIAL = [ precision=[32, 64], variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS, ), + # libm reference (exp_kernel calls expf/exp directly) for the perf + # comparison in plot_rq43 / plot_rq44. + *expand( + "softmax_polynomial/{N}xf{precision}/baseline", + N=range(16, 129, 16), + precision=[16, 32, 64], + ), ] # Full set. Contains all tests needed by plots in the paper. Beware: it's huge. @@ -1058,12 +1065,12 @@ rule plot_rq34: shell: "python {input.script} -o {output}" -rule plot_rq35: +rule plot_rq2: input: - script = PLOTS_DIR + "/plot_rq35.py", + script = PLOTS_DIR + "/plot_rq2.py", utils = PLOTS_DIR + "/plot_utils.py", output: - PLOTS_OUTPUT + "/rq35_plots.pdf", + PLOTS_OUTPUT + "/rq2_plots.pdf", shell: "python {input.script} -o {output}" @@ -1087,6 +1094,29 @@ rule plot_rq42: shell: "python {input.script} -i {input.softmax} -o {output}" +rule plot_rq43: + input: + script = PLOTS_DIR + "/plot_rq43.py", + utils = PLOTS_DIR + "/plot_utils.py", + softmax = "results/kernels.softmax_polynomial.csv", + output: + PLOTS_OUTPUT + "/rq43_plots.pdf", + shell: + "python {input.script} -i {input.softmax} -o {output}" + +rule plot_rq44: + input: + script = PLOTS_DIR + "/plot_rq44.py", + utils = PLOTS_DIR + "/plot_utils.py", + rq34 = PLOTS_DIR + "/plot_rq34.py", + rq40 = PLOTS_DIR + "/plot_rq40.py", + rq43 = PLOTS_DIR + "/plot_rq43.py", + softmax = "results/kernels.softmax_polynomial.csv", + output: + PLOTS_OUTPUT + "/rq44_plots.pdf", + shell: + "python {input.script} -i {input.softmax} -o {output}" + rule plots_mia_thesis: input: @@ -1097,4 +1127,6 @@ rule plots_mia_thesis: PLOTS_OUTPUT + "/rq33_plots.pdf", PLOTS_OUTPUT + "/rq34_plots.pdf", PLOTS_OUTPUT + "/rq41_plots.pdf", - PLOTS_OUTPUT + "/rq42_plots.pdf", \ No newline at end of file + PLOTS_OUTPUT + "/rq42_plots.pdf", + PLOTS_OUTPUT + "/rq43_plots.pdf", + PLOTS_OUTPUT + "/rq44_plots.pdf", \ No newline at end of file diff --git a/kernels/softmax_polynomial/baseline.c.template b/kernels/softmax_polynomial/baseline.c.template new file mode 100644 index 00000000..a2689091 --- /dev/null +++ b/kernels/softmax_polynomial/baseline.c.template @@ -0,0 +1,24 @@ +#include "data.h" + +#include + +#include +#include + +#ifdef __cplusplus +extern "C" { +#endif + +// Reference exp_kernel for softmax_polynomial: libm exp (no Chebyshev pass). +// softmax.c calls this symbol from softmax_kernel, so this variant produces +// the libm-grade reference runtime against which the xDSL polynomial variants +// (linalg_xdsl_b) are compared. +void exp_kernel(const DTYPE *x, DTYPE *z) { + for (uint32_t i = 0; i < N; ++i) { + z[i] = EXPF(x[i]); + } +} + +#ifdef __cplusplus +} +#endif diff --git a/kernels/softmax_polynomial/data.h.template b/kernels/softmax_polynomial/data.h.template index a0505e53..f2cc5374 100644 --- a/kernels/softmax_polynomial/data.h.template +++ b/kernels/softmax_polynomial/data.h.template @@ -3,12 +3,15 @@ #define PRECISION {{precision}} #if PRECISION == 16 #define DTYPE _Float16 +#define EXPF expf #define FABSF fabsf #elif PRECISION == 32 #define DTYPE float +#define EXPF expf #define FABSF fabsf #elif PRECISION == 64 #define DTYPE double +#define EXPF exp #define FABSF fabs #else #error Unsupported precision diff --git a/plots-mia-thesis/output/rq35_plots.pdf b/plots-mia-thesis/output/rq2_plots.pdf similarity index 71% rename from 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zV6yT@UVyzn>5vfpw|e;zNCb)e`=>7mfPrbp?`e=f^(O%PqhCS<1pm}29I){3 float: return df.loc[df["precision"] == precision, metric].mean() -def plot_rq35(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: +def plot_rq2(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: fig, axes = plt.subplots( 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False ) @@ -108,7 +108,7 @@ def main() -> None: ) parser.add_argument( "--output", "-o", - default="plots-mia-thesis/output/rq35_plots.pdf", + default="plots-mia-thesis/output/rq2_plots.pdf", help="Output plot file", ) args = parser.parse_args() @@ -116,7 +116,7 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) poly_df = load_bits_lost_csv(args.input) baseline_df = load_baseline_csv(args.input) - fig = plot_rq35(poly_df, baseline_df) + fig = plot_rq2(poly_df, baseline_df) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq42.py b/plots-mia-thesis/plot_rq42.py index f9472d38..ef86d5e8 100644 --- a/plots-mia-thesis/plot_rq42.py +++ b/plots-mia-thesis/plot_rq42.py @@ -1,14 +1,14 @@ #!/usr/bin/env python3 """ RQ42 plot: Does the kernel-level exp accuracy/perf trade-off translate to -the softmax operator? Mirrors rq35's layout so the two plots can be +the softmax operator? Mirrors rq2's layout so the two plots can be compared directly: same x-axis (`max_bits_lost`), same left y-axis (avg cycles/byte). Adds a twin right y-axis showing the end-to-end softmax output accuracy (avg bits lost in the softmax output across 100 sampled input vectors). Performance is loaded from `results/kernels.softmax_polynomial.csv` — same -processing as rq35. Accuracy is measured offline: +processing as rq2. Accuracy is measured offline: for each (precision, max_bits_lost): 1. recover the Chebyshev degree the pass picks (chosen_degree) 2. sample 100 input vectors of size DEFAULT_N from uniform(-1, 1) @@ -57,7 +57,7 @@ DEFAULT_SAMPLES = 100 DEFAULT_SEED = 0 -PERF_COLOR = "#33a02c" # matches rq35 +PERF_COLOR = "#33a02c" # matches rq2 ACC_COLOR = "#e31a1c" @@ -166,7 +166,7 @@ def plot_rq42(agg: pd.DataFrame) -> plt.Figure: ax.grid(True, alpha=0.3) continue - # Left axis: avg cycles/byte (mirrors rq35). + # Left axis: avg cycles/byte (mirrors rq2). l_perf, = ax.plot( sub["max_bits_lost"], sub["cycles_per_byte_mean"], marker="o", linestyle="-", color=PERF_COLOR, diff --git a/plots-mia-thesis/plot_rq43.py b/plots-mia-thesis/plot_rq43.py new file mode 100644 index 00000000..7d3adbea --- /dev/null +++ b/plots-mia-thesis/plot_rq43.py @@ -0,0 +1,138 @@ +#!/usr/bin/env python3 +""" +RQ43 plot: per-precision performance of the softmax_polynomial kernel as a +function of the `max_bits_lost` attribute attached to math.exp. Mirrors +plot_rq2's layout for the exp kernel — same x-axis (max_bits_lost), +same y-axis (avg cycles / byte), one panel per precision (f16/f32/f64) — +but draws softmax_polynomial measurements instead of exp_micro. + +Data source: `results/kernels.softmax_polynomial.csv`. The plot picks up +every row with `impl = linalg_xdsl_b` (the Snakefile's +XDSL_LINALG_MAX_BITS_LOST_VARIANTS), groups by precision and +max_bits_lost, and averages cycles/byte across the input sizes that were +benchmarked. The `baseline` rows (libm exp_kernel — added by the +baseline.c.template in kernels/softmax_polynomial) are drawn as a +horizontal reference line per panel. + +If the CSV does not yet contain baseline rows (the variants are +registered in the Snakefile but the run hasn't been triggered yet) the +baseline line is omitted and only the polynomial curve is drawn. + +Usage: + python plot_rq43.py [-i results/kernels.softmax_polynomial.csv] \\ + [-o plots-mia-thesis/output/rq43_plots.pdf] +""" + +import argparse +import re +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd + +from plot_utils import ( + PRECISIONS, + annotate_kernel_df, + savefig, +) + + +BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") + +POLY_COLOR = "#33a02c" # matches rq2 +BASELINE_COLOR = "#1f78b4" # matches rq2 + + +def load_bits_lost_csv(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"].str.match(BITS_LOST_VARIANT_RE)].copy() + df["max_bits_lost"] = df["impl"].str.extract(BITS_LOST_VARIANT_RE).astype(int) + return annotate_kernel_df(df) + + +def load_baseline_csv(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"] == "baseline"].copy() + if df.empty: + return df + return annotate_kernel_df(df) + + +def avg_per_bits_lost(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: + return ( + df[df["precision"] == precision] + .groupby("max_bits_lost")[metric] + .mean() + .sort_index() + ) + + +def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: + if df.empty or "precision" not in df.columns or metric not in df.columns: + return float("nan") + sub = df.loc[df["precision"] == precision, metric] + return float("nan") if sub.empty else float(sub.mean()) + + +def plot_rq43(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: + fig, axes = plt.subplots( + 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False, + ) + + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[col_idx] + series = avg_per_bits_lost(poly_df, precision, "cycles_per_byte") + baseline = avg_baseline(baseline_df, precision, "cycles_per_byte") + + if not series.empty: + ax.plot( + series.index, series.values, + marker="o", linestyle="-", color=POLY_COLOR, + label="Chebyshev polynomial (softmax)", + ) + if not np.isnan(baseline): + ax.axhline( + baseline, color=BASELINE_COLOR, linestyle="--", + label=f"libm baseline ({baseline:.3g})", + ) + + ax.set_title(precision) + ax.set_xlabel( + r"User-specified exp accuracy bound (max bits lost, looser $\rightarrow$)" + ) + if col_idx == 0: + ax.set_ylabel("avg cycles / byte") + if not series.empty: + ax.set_xticks(series.index) + ax.grid(True, alpha=0.3) + ax.legend(loc="best", fontsize=8) + + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--input", "-i", + default="results/kernels.softmax_polynomial.csv", + help="Input CSV with softmax_polynomial measurements", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq43_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + poly_df = load_bits_lost_csv(args.input) + baseline_df = load_baseline_csv(args.input) + fig = plot_rq43(poly_df, baseline_df) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_rq44.py b/plots-mia-thesis/plot_rq44.py new file mode 100644 index 00000000..dac36b25 --- /dev/null +++ b/plots-mia-thesis/plot_rq44.py @@ -0,0 +1,242 @@ +#!/usr/bin/env python3 +""" +RQ44 plot: accuracy vs performance Pareto scatter for the +softmax_polynomial kernel, one panel per precision (f16/f32/f64). + + x = measured average ULP error of the softmax output + (computed exactly as in plot_rq40 — softmax.c arithmetic in DTYPE + with exp replaced by the lowered Clenshaw Chebyshev approximation, + compared against the same kernel with correctly-rounded libm exp, + averaged over `samples` random input vectors of size `n`) + y = avg cycles / byte for the softmax_polynomial kernel + (same number as plot_rq43, loaded from + results/kernels.softmax_polynomial.csv) + +Each (precision, max_bits_lost) variant becomes one scatter point. Points +are connected in order of increasing max_bits_lost and labelled with the +corresponding `bN` (or `bN..M` when several adjacent budgets pick the +same chosen degree and therefore land on the same (cycles, ulp) point). + +A libm `baseline` reference (a single horizontal line at the baseline +cycles/byte mean for that precision) is drawn when the CSV contains the +baseline rows registered by the Snakefile (kernels/softmax_polynomial/ +baseline.c.template). + +x-axis is log-scaled. ULP errors below 1 are floored to 1 so "within 1 +ULP of the reference" sits at the left edge instead of running off to +-inf; this matches the floor plot_rq40 / plot_rq42 use for the bits +conversion. + +Usage: + python plot_rq44.py [-i results/kernels.softmax_polynomial.csv] \\ + [--n 64] [--samples 100] [--seed 0] \\ + [-o plots-mia-thesis/output/rq44_plots.pdf] +""" + +import argparse +import re +from functools import lru_cache +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd + +from plot_rq34 import chosen_degree +from plot_rq40 import ( + F16_BITS_LOST_CAP, + per_vector_mean_ulp_err, +) +from plot_rq43 import ( + BITS_LOST_VARIANT_RE, + avg_baseline, + load_baseline_csv, + load_bits_lost_csv, +) +from plot_utils import ( + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + PRECISION_MANTISSA_BITS, + PRECISIONS, + savefig, +) + + +DEFAULT_N = 64 +DEFAULT_SAMPLES = 100 +DEFAULT_SEED = 0 + +# Sub-ULP runs are clipped to this floor so log10(x) is finite. +ULP_FLOOR = 1.0 + +POINT_COLOR = "#33a02c" +BASELINE_COLOR = "#1f78b4" + + +@lru_cache(maxsize=None) +def _measure_for_degree( + precision: str, degree: int, n: int, samples: int, seed: int, +) -> float: + """Mean ULP error of the softmax output for a given (precision, degree). + Keyed on `degree` (not `max_bits_lost`) and seeded deterministically so + that all max_bits_lost variants that resolve to the same chosen_degree + produce *identical* measurements — they emit the same code, so the plot + should treat them as the same Pareto point.""" + rng = np.random.default_rng(np.uint64(seed)) + errs = [ + per_vector_mean_ulp_err(rng.uniform(-1.0, 1.0, n), degree, precision) + for _ in range(samples) + ] + return float(np.mean(errs)) + + +def _measure_ulp_err( + precision: str, bits_lost: int, n: int, samples: int, seed: int, +) -> float | None: + """Mean ULP error of the softmax output for (precision, max_bits_lost), + via the chosen_degree the pass would pick at that budget. Mirrors + plot_rq40 except it returns the raw ULP error (not log2).""" + if precision == "f16" and bits_lost >= F16_BITS_LOST_CAP: + return None + mantissa = PRECISION_MANTISSA_BITS[precision] + degree, _ = chosen_degree( + bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa, + ) + return _measure_for_degree(precision, degree, n, samples, seed) + + +def collect_points( + poly_df: pd.DataFrame, n: int, samples: int, seed: int, +) -> pd.DataFrame: + """One row per (precision, max_bits_lost) in poly_df, carrying both + the measured ULP error (computed offline, à la rq40) and the avg + cycles/byte (averaged over input sizes, à la rq43).""" + rows = [] + for (precision, bits_lost), group in poly_df.groupby(["precision", "max_bits_lost"]): + ulp_err = _measure_ulp_err( + precision, int(bits_lost), n, samples, seed, + ) + if ulp_err is None: + continue + rows.append({ + "precision": precision, + "max_bits_lost": int(bits_lost), + "ulp_err": ulp_err, + "cycles_per_byte": float(group["cycles_per_byte"].mean()), + }) + return pd.DataFrame(rows) + + +def _format_bits_label(bs: list[int]) -> str: + """Collapse a sorted list of max_bits_lost values into a compact label + (`b3` / `b-1..1` / `b-1,2,5`) for annotating coincident points.""" + if len(bs) == 1: + return f"b{bs[0]}" + if bs == list(range(bs[0], bs[-1] + 1)): + return f"b{bs[0]}..{bs[-1]}" + return "b" + ",".join(str(b) for b in bs) + + +def plot_rq44( + points: pd.DataFrame, baseline_df: pd.DataFrame, +) -> plt.Figure: + fig, axes = plt.subplots( + 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False, + ) + + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[col_idx] + sub = points[points["precision"] == precision].copy() + baseline = avg_baseline(baseline_df, precision, "cycles_per_byte") + + if not sub.empty: + sub["x"] = np.maximum(sub["ulp_err"].to_numpy(), ULP_FLOOR) + # Variants whose chosen_degree collapses to the same value land + # on the same (cycles, ulp) point — group them so the line and + # annotations don't stack on top of each other. + grp = sub.groupby( + [sub["x"].round(9), sub["cycles_per_byte"].round(6)], + sort=False, + ) + groups = [] + for (x, y), g in grp: + bs = sorted(int(b) for b in g["max_bits_lost"]) + groups.append((float(x), float(y), bs)) + groups.sort(key=lambda t: min(t[2])) + + xs = [g[0] for g in groups] + ys = [g[1] for g in groups] + ax.plot( + xs, ys, + marker="o", linestyle="-", color=POINT_COLOR, + label="Chebyshev polynomial (per max_bits_lost)", + ) + for x, y, bs in groups: + ax.annotate( + _format_bits_label(bs), + (x, y), + textcoords="offset points", + xytext=(8, 8), + fontsize=8, + ha="left", va="bottom", + bbox=dict( + boxstyle="round,pad=0.15", + fc="white", ec="none", alpha=0.75, + ), + ) + + if not np.isnan(baseline): + ax.axhline( + baseline, color=BASELINE_COLOR, linestyle="--", + label=f"libm baseline ({baseline:.3g})", + ) + + ax.set_xscale("log") + ax.set_title(precision) + ax.set_xlabel("measured average ULP error (softmax output)") + if col_idx == 0: + ax.set_ylabel("avg cycles / byte") + ax.grid(True, which="both", alpha=0.3) + ax.legend(loc="best", fontsize=8) + + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--input", "-i", + default="results/kernels.softmax_polynomial.csv", + help="softmax_polynomial measurement CSV", + ) + parser.add_argument( + "--n", type=int, default=DEFAULT_N, + help="Size of each sample input vector for the accuracy measurement", + ) + parser.add_argument( + "--samples", type=int, default=DEFAULT_SAMPLES, + help="Number of sample input vectors per (precision, max_bits_lost)", + ) + parser.add_argument( + "--seed", type=int, default=DEFAULT_SEED, + help="Base seed for input-vector sampling", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq44_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + poly_df = load_bits_lost_csv(args.input) + baseline_df = load_baseline_csv(args.input) + points = collect_points(poly_df, n=args.n, samples=args.samples, seed=args.seed) + fig = plot_rq44(points, baseline_df) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() From a4fc1a909ba286054d291f84ce7513d63d21888e Mon Sep 17 00:00:00 2001 From: Mia Sophie Zerdick Date: Mon, 1 Jun 2026 14:52:37 +0100 Subject: [PATCH 27/33] ran experiments --- results/kernels.softmax_polynomial.csv | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) diff --git a/results/kernels.softmax_polynomial.csv b/results/kernels.softmax_polynomial.csv index a761f9e8..fb578577 100644 --- a/results/kernels.softmax_polynomial.csv +++ b/results/kernels.softmax_polynomial.csv @@ -1,4 +1,5 @@ test,params,impl,cycles,end,end_fpss,fpss_avg_fpu_latency,fpss_avg_load_latency,fpss_fpu_fmadd_issues,fpss_fpu_issues,fpss_fpu_latency,fpss_fpu_occupancy,fpss_fpu_rel_occupancy,fpss_issues,fpss_load_latency,fpss_loads,fpss_occupancy,fpss_section_latency,fpss_stores,fseq_fpu_yield,fseq_yield,section,snitch_avg_load_latency,snitch_fseq_offloads,snitch_fseq_rel_offloads,snitch_issues,snitch_load_latency,snitch_loads,snitch_occupancy,snitch_stores,start,tend,total_ipc,tstart +softmax_polynomial,112xf16,baseline,14690,17257,17254,0.0,0,336,2020,0,0.13750850918992513,0.5253576072821846,3845,0,0,0.2617426820966644,0,0,1.0,1.0,1,6.91358024691358,3845,0.45283241078789305,4646,2800,405,0.3162695711368278,274,2568,17261,0.5780122532334921,2570 softmax_polynomial,112xf16,linalg_xdsl_b-1,6939,9060,9057,0.0,0,0,1124,0,0.16198299466781957,0.5186894323950162,2167,0,0,0.31229283758466636,0,0,1.0,1.0,1,3.03125,2167,0.3809105290912287,3522,194,64,0.5075659316904453,717,2122,9064,0.8198587692751116,2124 softmax_polynomial,112xf16,linalg_xdsl_b0,6603,8700,8697,0.0,0,0,1040,0,0.15750416477358775,0.5060827250608273,2055,0,0,0.3112221717401181,0,0,1.0,1.0,1,3.03125,2055,0.37992235163616195,3354,194,64,0.5079509313948205,661,2098,8704,0.8191731031349386,2100 softmax_polynomial,112xf16,linalg_xdsl_b1,6603,8700,8697,0.0,0,0,1040,0,0.15750416477358775,0.5060827250608273,2055,0,0,0.3112221717401181,0,0,1.0,1.0,1,3.03125,2055,0.37992235163616195,3354,194,64,0.5079509313948205,661,2098,8704,0.8191731031349386,2100 @@ -11,6 +12,7 @@ softmax_polynomial,112xf16,linalg_xdsl_b6,6256,8399,8396,0.0,0,0,956,0,0.1528132 softmax_polynomial,112xf16,linalg_xdsl_b7,5938,8059,8056,0.0,0,0,872,0,0.1468507915122937,0.4762424904423812,1831,0,0,0.3083529808016167,0,0,1.0,1.0,1,3.03125,1831,0.37760362961435345,3018,194,64,0.5082519366790165,549,2122,8063,0.8166049174806331,2124 softmax_polynomial,112xf16,linalg_xdsl_b8,5938,8059,8056,0.0,0,0,872,0,0.1468507915122937,0.4762424904423812,1831,0,0,0.3083529808016167,0,0,1.0,1.0,1,3.03125,1831,0.37760362961435345,3018,194,64,0.5082519366790165,549,2122,8063,0.8166049174806331,2124 softmax_polynomial,112xf16,linalg_xdsl_b9,5938,8059,8056,0.0,0,0,872,0,0.1468507915122937,0.4762424904423812,1831,0,0,0.3083529808016167,0,0,1.0,1.0,1,3.03125,1831,0.37760362961435345,3018,194,64,0.5082519366790165,549,2122,8063,0.8166049174806331,2124 +softmax_polynomial,112xf32,baseline,14011,16605,16602,0.0,0,336,1794,0,0.1280422525158804,0.4957170489085383,3619,0,0,0.2582970523160374,0,0,1.0,1.0,1,6.920987654320988,3619,0.437870538415003,4646,2803,405,0.3315966026693312,274,2595,16609,0.5898936549853686,2597 softmax_polynomial,112xf32,linalg_xdsl_b-1,12319,14419,14416,0.0,0,0,2298,0,0.18654111535027193,0.5976592977893368,3845,0,0,0.3121194902183619,0,0,1.0,1.0,1,3.03125,3845,0.3867042140199135,6098,194,64,0.49500771166490787,1725,2101,14423,0.8071272018832698,2103 softmax_polynomial,112xf32,linalg_xdsl_b0,12319,14419,14416,0.0,0,0,2298,0,0.18654111535027193,0.5976592977893368,3845,0,0,0.3121194902183619,0,0,1.0,1.0,1,3.03125,3845,0.3867042140199135,6098,194,64,0.49500771166490787,1725,2101,14423,0.8071272018832698,2103 softmax_polynomial,112xf32,linalg_xdsl_b1,11671,13792,13789,0.0,0,0,2130,0,0.182503641504584,0.5882352941176471,3621,0,0,0.3102561905577928,0,0,1.0,1.0,1,3.03125,3621,0.3859106895449217,5762,194,64,0.49370233913117983,1613,2122,13796,0.8039585296889726,2124 @@ -29,6 +31,7 @@ softmax_polynomial,112xf32,linalg_xdsl_b6,10991,13088,13085,0.0,0,0,1962,0,0.178 softmax_polynomial,112xf32,linalg_xdsl_b7,10991,13088,13085,0.0,0,0,1962,0,0.17850968974615594,0.5775684427435973,3397,0,0,0.30907105813847696,0,0,1.0,1.0,1,3.03125,3397,0.3850164343193925,5426,194,64,0.49367664452734056,1501,2098,13092,0.8027477026658175,2100 softmax_polynomial,112xf32,linalg_xdsl_b8,10991,13088,13085,0.0,0,0,1962,0,0.17850968974615594,0.5775684427435973,3397,0,0,0.30907105813847696,0,0,1.0,1.0,1,3.03125,3397,0.3850164343193925,5426,194,64,0.49367664452734056,1501,2098,13092,0.8027477026658175,2100 softmax_polynomial,112xf32,linalg_xdsl_b9,10305,12448,12445,0.0,0,0,1794,0,0.17409024745269286,0.5653955247399937,3173,0,0,0.30790878214459,0,0,1.0,1.0,1,3.046875,3173,0.3840009681713663,5090,195,64,0.49393498301795247,1389,2144,12452,0.8018437651625425,2146 +softmax_polynomial,112xf64,baseline,15731,18365,18362,0.0,0,777,1894,0,0.12039921174750493,0.4556170315131104,4157,0,0,0.2642552920984044,0,0,1.0,1.0,1,10.505190311418685,4157,0.44984309057461314,5084,6072,578,0.323183522980103,324,2635,18369,0.5874388150785075,2637 softmax_polynomial,112xf64,linalg_xdsl_b-1,27343,29409,29406,0.0,0,0,6722,0,0.2458398858940131,0.7289881791562737,9221,0,0,0.3372343927147716,0,0,1.0,1.0,1,3.0,9221,0.41005914528394183,13266,384,128,0.48516987894525104,3681,2067,29413,0.8224042716600226,2069 softmax_polynomial,112xf64,linalg_xdsl_b0,27343,29409,29406,0.0,0,0,6722,0,0.2458398858940131,0.7289881791562737,9221,0,0,0.3372343927147716,0,0,1.0,1.0,1,3.0,9221,0.41005914528394183,13266,384,128,0.48516987894525104,3681,2067,29413,0.8224042716600226,2069 softmax_polynomial,112xf64,linalg_xdsl_b1,27343,29409,29406,0.0,0,0,6722,0,0.2458398858940131,0.7289881791562737,9221,0,0,0.3372343927147716,0,0,1.0,1.0,1,3.0,9221,0.41005914528394183,13266,384,128,0.48516987894525104,3681,2067,29413,0.8224042716600226,2069 @@ -47,6 +50,7 @@ softmax_polynomial,112xf64,linalg_xdsl_b6,25989,28056,28053,0.0,0,0,6386,0,0.245 softmax_polynomial,112xf64,linalg_xdsl_b7,24657,26697,26694,0.0,0,0,6050,0,0.24536642738370443,0.7267267267267268,8325,0,0,0.33763231536683297,0,0,1.0,1.0,1,3.0,8325,0.41117202548525705,11922,384,128,0.48351380946587175,3233,2041,26701,0.8211461248327048,2043 softmax_polynomial,112xf64,linalg_xdsl_b8,24657,26697,26694,0.0,0,0,6050,0,0.24536642738370443,0.7267267267267268,8325,0,0,0.33763231536683297,0,0,1.0,1.0,1,3.0,8325,0.41117202548525705,11922,384,128,0.48351380946587175,3233,2041,26701,0.8211461248327048,2043 softmax_polynomial,112xf64,linalg_xdsl_b9,24657,26697,26694,0.0,0,0,6050,0,0.24536642738370443,0.7267267267267268,8325,0,0,0.33763231536683297,0,0,1.0,1.0,1,3.0,8325,0.41117202548525705,11922,384,128,0.48351380946587175,3233,2041,26701,0.8211461248327048,2043 +softmax_polynomial,128xf16,baseline,16706,19273,19270,0.0,0,384,2308,0,0.13815395666227703,0.5258601048074732,4389,0,0,0.2627199808452053,0,0,1.0,1.0,1,6.993377483443709,4389,0.45439486489284603,5270,3168,453,0.3154555249610918,306,2568,19277,0.5781755058062972,2570 softmax_polynomial,128xf16,linalg_xdsl_b-1,7847,9968,9965,0.0,0,0,1284,0,0.1636294125143367,0.519627681100769,2471,0,0,0.31489741302408564,0,0,1.0,1.0,1,3.03125,2471,0.3826854576428682,3986,194,64,0.5079648273225437,813,2122,9972,0.8228622403466292,2124 softmax_polynomial,128xf16,linalg_xdsl_b0,7463,9560,9557,0.0,0,0,1188,0,0.1591853142168029,0.5070422535211268,2343,0,0,0.3139488141498057,0,0,1.0,1.0,1,3.03125,2343,0.3817826299494867,3794,194,64,0.5083746482647729,749,2098,9564,0.8223234624145785,2100 softmax_polynomial,128xf16,linalg_xdsl_b1,7463,9560,9557,0.0,0,0,1188,0,0.1591853142168029,0.5070422535211268,2343,0,0,0.3139488141498057,0,0,1.0,1.0,1,3.03125,2343,0.3817826299494867,3794,194,64,0.5083746482647729,749,2098,9564,0.8223234624145785,2100 @@ -59,6 +63,7 @@ softmax_polynomial,128xf16,linalg_xdsl_b6,7068,9211,9208,0.0,0,0,1092,0,0.154499 softmax_polynomial,128xf16,linalg_xdsl_b7,6702,8823,8820,0.0,0,0,996,0,0.1486123545210385,0.4772400574988021,2087,0,0,0.3113995822142644,0,0,1.0,1.0,1,3.03125,2087,0.37966163361833727,3410,194,64,0.5088033422858849,621,2122,8827,0.8202029245001492,2124 softmax_polynomial,128xf16,linalg_xdsl_b8,6702,8823,8820,0.0,0,0,996,0,0.1486123545210385,0.4772400574988021,2087,0,0,0.3113995822142644,0,0,1.0,1.0,1,3.03125,2087,0.37966163361833727,3410,194,64,0.5088033422858849,621,2122,8827,0.8202029245001492,2124 softmax_polynomial,128xf16,linalg_xdsl_b9,6702,8823,8820,0.0,0,0,996,0,0.1486123545210385,0.4772400574988021,2087,0,0,0.3113995822142644,0,0,1.0,1.0,1,3.03125,2087,0.37966163361833727,3410,194,64,0.5088033422858849,621,2122,8827,0.8202029245001492,2124 +softmax_polynomial,128xf32,baseline,15931,18530,18527,0.0,0,384,2050,0,0.12867993220764548,0.4962478818687969,4131,0,0,0.2593057560730651,0,0,1.0,1.0,1,7.0,4131,0.4394213381555154,5270,3171,453,0.3308015818216057,306,2600,18534,0.5901073378946708,2602 softmax_polynomial,128xf32,linalg_xdsl_b-1,13999,16099,16096,0.0,0,0,2626,0,0.18758482748767769,0.5983139667350194,4389,0,0,0.3135223944567469,0,0,1.0,1.0,1,3.03125,4389,0.3877551020408163,6930,194,64,0.4950353596685478,1965,2101,16103,0.8085577541252946,2103 softmax_polynomial,128xf32,linalg_xdsl_b0,13999,16099,16096,0.0,0,0,2626,0,0.18758482748767769,0.5983139667350194,4389,0,0,0.3135223944567469,0,0,1.0,1.0,1,3.03125,4389,0.3877551020408163,6930,194,64,0.4950353596685478,1965,2101,16103,0.8085577541252946,2103 softmax_polynomial,128xf32,linalg_xdsl_b1,13255,15381,15378,0.0,0,0,2434,0,0.1836288193134666,0.588918461166223,4133,0,0,0.3118068653338363,0,0,1.0,1.0,1,3.03125,4133,0.387021256671973,6546,194,64,0.4938513768389287,1837,2127,15385,0.8056582421727649,2129 @@ -77,6 +82,7 @@ softmax_polynomial,128xf32,linalg_xdsl_b6,12479,14581,14578,0.0,0,0,2242,0,0.179 softmax_polynomial,128xf32,linalg_xdsl_b7,12479,14581,14578,0.0,0,0,2242,0,0.1796618318775543,0.5782821769409338,3877,0,0,0.3106819456687235,0,0,1.0,1.0,1,3.03125,3877,0.38619384400836737,6162,194,64,0.49378956647167244,1709,2103,14585,0.8044715121403959,2105 softmax_polynomial,128xf32,linalg_xdsl_b8,12479,14581,14578,0.0,0,0,2242,0,0.1796618318775543,0.5782821769409338,3877,0,0,0.3106819456687235,0,0,1.0,1.0,1,3.03125,3877,0.38619384400836737,6162,194,64,0.49378956647167244,1709,2103,14585,0.8044715121403959,2105 softmax_polynomial,128xf32,linalg_xdsl_b9,11697,13845,13842,0.0,0,0,2050,0,0.17525861331965462,0.5661419497376415,3621,0,0,0.3095665555270582,0,0,1.0,1.0,1,3.046875,3621,0.38525375039897863,5778,195,64,0.49397281354193384,1581,2149,13849,0.803539369068992,2151 +softmax_polynomial,128xf64,baseline,17859,20493,20490,0.0,0,889,2166,0,0.12128338652780112,0.45609602021478207,4749,0,0,0.2659163447001512,0,0,1.0,1.0,1,10.728971962616823,4749,0.45276003432167033,5740,6888,642,0.3214065737163335,356,2635,20497,0.5873229184164848,2637 softmax_polynomial,128xf64,linalg_xdsl_b-1,31119,33185,33182,0.0,0,0,7682,0,0.24685883222468588,0.7293268774328302,10533,0,0,0.33847488672515186,0,0,1.0,1.0,1,3.0,10533,0.41107598641845217,15090,384,128,0.4849127542658826,4193,2067,33189,0.8233876409910345,2069 softmax_polynomial,128xf64,linalg_xdsl_b0,31119,33185,33182,0.0,0,0,7682,0,0.24685883222468588,0.7293268774328302,10533,0,0,0.33847488672515186,0,0,1.0,1.0,1,3.0,10533,0.41107598641845217,15090,384,128,0.4849127542658826,4193,2067,33189,0.8233876409910345,2069 softmax_polynomial,128xf64,linalg_xdsl_b1,31119,33185,33182,0.0,0,0,7682,0,0.24685883222468588,0.7293268774328302,10533,0,0,0.33847488672515186,0,0,1.0,1.0,1,3.0,10533,0.41107598641845217,15090,384,128,0.4849127542658826,4193,2067,33189,0.8233876409910345,2069 @@ -95,6 +101,7 @@ softmax_polynomial,128xf64,linalg_xdsl_b6,29573,31640,31637,0.0,0,0,7298,0,0.246 softmax_polynomial,128xf64,linalg_xdsl_b7,28049,30089,30086,0.0,0,0,6914,0,0.2464972013262505,0.7271006414975286,9509,0,0,0.3390138685871154,0,0,1.0,1.0,1,3.0,9509,0.4123054242726445,13554,384,128,0.4832257834503904,3681,2041,30093,0.8222396520375058,2043 softmax_polynomial,128xf64,linalg_xdsl_b8,28049,30089,30086,0.0,0,0,6914,0,0.2464972013262505,0.7271006414975286,9509,0,0,0.3390138685871154,0,0,1.0,1.0,1,3.0,9509,0.4123054242726445,13554,384,128,0.4832257834503904,3681,2041,30093,0.8222396520375058,2043 softmax_polynomial,128xf64,linalg_xdsl_b9,28049,30089,30086,0.0,0,0,6914,0,0.2464972013262505,0.7271006414975286,9509,0,0,0.3390138685871154,0,0,1.0,1.0,1,3.0,9509,0.4123054242726445,13554,384,128,0.4832257834503904,3681,2041,30093,0.8222396520375058,2043 +softmax_polynomial,16xf16,baseline,2461,5012,5009,0.0,0,48,289,0,0.11743193823648923,0.5,578,0,0,0.23486387647297846,0,0,1.0,1.0,1,5.095652173913043,578,0.48206839032527105,621,586,115,0.2523364485981308,80,2552,5016,0.4872003250711093,2554 softmax_polynomial,16xf16,linalg_xdsl_b-1,1353,3475,3472,0.0,0,0,161,0,0.11899482631189948,0.47352941176470587,340,0,0,0.25129342202512933,0,0,1.0,1.0,1,3.03125,340,0.39215686274509803,527,194,64,0.3895048041389505,141,2123,3479,0.6407982261640799,2125 softmax_polynomial,16xf16,linalg_xdsl_b0,1315,3432,3429,0.0,0,0,149,0,0.11330798479087452,0.45987654320987653,324,0,0,0.24638783269961978,0,0,1.0,1.0,1,3.046875,324,0.39177750906892383,503,195,64,0.38250950570342207,133,2118,3436,0.6288973384030419,2120 softmax_polynomial,16xf16,linalg_xdsl_b1,1315,3432,3429,0.0,0,0,149,0,0.11330798479087452,0.45987654320987653,324,0,0,0.24638783269961978,0,0,1.0,1.0,1,3.046875,324,0.39177750906892383,503,195,64,0.38250950570342207,133,2118,3436,0.6288973384030419,2120 @@ -107,6 +114,7 @@ softmax_polynomial,16xf16,linalg_xdsl_b6,1298,3415,3412,0.0,0,0,137,0,0.10554699 softmax_polynomial,16xf16,linalg_xdsl_b7,1214,3350,3347,0.0,0,0,125,0,0.10296540362438221,0.4280821917808219,292,0,0,0.24052718286655683,0,0,1.0,1.0,1,3.03125,292,0.3908969210174029,455,194,64,0.3747940691927512,117,2137,3354,0.6153212520593081,2139 softmax_polynomial,16xf16,linalg_xdsl_b8,1214,3350,3347,0.0,0,0,125,0,0.10296540362438221,0.4280821917808219,292,0,0,0.24052718286655683,0,0,1.0,1.0,1,3.03125,292,0.3908969210174029,455,194,64,0.3747940691927512,117,2137,3354,0.6153212520593081,2139 softmax_polynomial,16xf16,linalg_xdsl_b9,1214,3350,3347,0.0,0,0,125,0,0.10296540362438221,0.4280821917808219,292,0,0,0.24052718286655683,0,0,1.0,1.0,1,3.03125,292,0.3908969210174029,455,194,64,0.3747940691927512,117,2137,3354,0.6153212520593081,2139 +softmax_polynomial,16xf32,baseline,2408,4959,4956,0.0,0,48,255,0,0.10589700996677741,0.45535714285714285,560,0,0,0.23255813953488372,0,0,1.0,1.0,1,5.121739130434783,560,0.4741744284504657,621,589,115,0.25789036544850497,80,2552,4963,0.49044850498338866,2554 softmax_polynomial,16xf32,linalg_xdsl_b-1,2153,4257,4254,0.0,0,0,327,0,0.15188109614491407,0.5505050505050505,594,0,0,0.2758941012540641,0,0,1.0,1.0,1,3.03125,594,0.3989254533243788,895,194,64,0.41569902461681374,285,2105,4261,0.6915931258708778,2107 softmax_polynomial,16xf32,linalg_xdsl_b0,2153,4257,4254,0.0,0,0,327,0,0.15188109614491407,0.5505050505050505,594,0,0,0.2758941012540641,0,0,1.0,1.0,1,3.03125,594,0.3989254533243788,895,194,64,0.41569902461681374,285,2105,4261,0.6915931258708778,2107 softmax_polynomial,16xf32,linalg_xdsl_b1,2075,4197,4194,0.0,0,0,303,0,0.14602409638554217,0.5391459074733096,562,0,0,0.2708433734939759,0,0,1.0,1.0,1,3.03125,562,0.3988644428672818,847,194,64,0.4081927710843373,269,2123,4201,0.6790361445783133,2125 @@ -125,6 +133,7 @@ softmax_polynomial,16xf32,linalg_xdsl_b6,1973,4090,4087,0.0,0,0,279,0,0.14140902 softmax_polynomial,16xf32,linalg_xdsl_b7,1973,4090,4087,0.0,0,0,279,0,0.141409021794222,0.5264150943396226,530,0,0,0.26862645717181954,0,0,1.0,1.0,1,3.03125,530,0.39879608728367194,799,194,64,0.40496705524581855,253,2118,4094,0.6735935124176381,2120 softmax_polynomial,16xf32,linalg_xdsl_b8,1973,4090,4087,0.0,0,0,279,0,0.141409021794222,0.5264150943396226,530,0,0,0.26862645717181954,0,0,1.0,1.0,1,3.03125,530,0.39879608728367194,799,194,64,0.40496705524581855,253,2118,4094,0.6735935124176381,2120 softmax_polynomial,16xf32,linalg_xdsl_b9,1894,4011,4008,0.0,0,0,255,0,0.13463569165786696,0.5120481927710844,498,0,0,0.26293558606124606,0,0,1.0,1.0,1,3.03125,498,0.3987189751801441,751,194,64,0.39651531151003166,237,2118,4015,0.6594508975712777,2120 +softmax_polynomial,16xf64,baseline,2867,5450,5447,0.0,0,105,259,0,0.09033833275200558,0.4190938511326861,618,0,0,0.21555633065922566,0,0,1.0,1.0,1,6.0625,618,0.4161616161616162,867,1164,192,0.3024066968957098,130,2584,5454,0.5179630275549355,2586 softmax_polynomial,16xf64,linalg_xdsl_b-1,4595,6633,6630,0.0,0,0,959,0,0.2087051142546246,0.7041116005873715,1362,0,0,0.29640914036996735,0,0,1.0,1.0,1,3.0,1362,0.39216815433342933,2111,384,128,0.45941240478781287,609,2039,6637,0.7558215451577802,2041 softmax_polynomial,16xf64,linalg_xdsl_b0,4595,6633,6630,0.0,0,0,959,0,0.2087051142546246,0.7041116005873715,1362,0,0,0.29640914036996735,0,0,1.0,1.0,1,3.0,1362,0.39216815433342933,2111,384,128,0.45941240478781287,609,2039,6637,0.7558215451577802,2041 softmax_polynomial,16xf64,linalg_xdsl_b1,4595,6633,6630,0.0,0,0,959,0,0.2087051142546246,0.7041116005873715,1362,0,0,0.29640914036996735,0,0,1.0,1.0,1,3.0,1362,0.39216815433342933,2111,384,128,0.45941240478781287,609,2039,6637,0.7558215451577802,2041 @@ -143,6 +152,7 @@ softmax_polynomial,16xf64,linalg_xdsl_b6,4379,6433,6430,0.0,0,0,911,0,0.20803836 softmax_polynomial,16xf64,linalg_xdsl_b7,4198,6246,6243,0.0,0,0,863,0,0.20557408289661744,0.6993517017828201,1234,0,0,0.29394949976179136,0,0,1.0,1.0,1,3.0,1234,0.3913732952743419,1919,384,128,0.45712243925678897,545,2049,6250,0.7510719390185803,2051 softmax_polynomial,16xf64,linalg_xdsl_b8,4198,6246,6243,0.0,0,0,863,0,0.20557408289661744,0.6993517017828201,1234,0,0,0.29394949976179136,0,0,1.0,1.0,1,3.0,1234,0.3913732952743419,1919,384,128,0.45712243925678897,545,2049,6250,0.7510719390185803,2051 softmax_polynomial,16xf64,linalg_xdsl_b9,4198,6246,6243,0.0,0,0,863,0,0.20557408289661744,0.6993517017828201,1234,0,0,0.29394949976179136,0,0,1.0,1.0,1,3.0,1234,0.3913732952743419,1919,384,128,0.45712243925678897,545,2049,6250,0.7510719390185803,2051 +softmax_polynomial,32xf16,baseline,4419,6981,6978,0.0,0,96,577,0,0.1305725277212039,0.5142602495543672,1122,0,0,0.25390359809911744,0,0,1.0,1.0,1,5.852760736196319,1122,0.5353053435114504,974,954,163,0.22041185788639964,112,2563,6985,0.47431545598551705,2565 softmax_polynomial,32xf16,linalg_xdsl_b-1,2174,4290,4287,0.0,0,0,321,0,0.14765409383624656,0.4984472049689441,644,0,0,0.29622815087396503,0,0,1.0,1.0,1,3.03125,644,0.45098039215686275,784,194,64,0.36062557497700093,237,2117,4294,0.6568537258509659,2119 softmax_polynomial,32xf16,linalg_xdsl_b0,2123,4215,4212,0.0,0,0,297,0,0.13989637305699482,0.4852941176470588,612,0,0,0.2882713141780499,0,0,1.0,1.0,1,3.03125,612,0.4540059347181009,736,194,64,0.34667922750824304,221,2093,4219,0.634950541686293,2095 softmax_polynomial,32xf16,linalg_xdsl_b1,2123,4215,4212,0.0,0,0,297,0,0.13989637305699482,0.4852941176470588,612,0,0,0.2882713141780499,0,0,1.0,1.0,1,3.03125,612,0.4540059347181009,736,194,64,0.34667922750824304,221,2093,4219,0.634950541686293,2095 @@ -155,6 +165,7 @@ softmax_polynomial,32xf16,linalg_xdsl_b6,1987,4125,4122,0.0,0,0,273,0,0.13739305 softmax_polynomial,32xf16,linalg_xdsl_b7,1909,4025,4022,0.0,0,0,249,0,0.13043478260869565,0.4543795620437956,548,0,0,0.287061288632792,0,0,1.0,1.0,1,3.046875,548,0.4612794612794613,640,195,64,0.3352540597171294,189,2117,4029,0.6223153483499214,2119 softmax_polynomial,32xf16,linalg_xdsl_b8,1909,4025,4022,0.0,0,0,249,0,0.13043478260869565,0.4543795620437956,548,0,0,0.287061288632792,0,0,1.0,1.0,1,3.046875,548,0.4612794612794613,640,195,64,0.3352540597171294,189,2117,4029,0.6223153483499214,2119 softmax_polynomial,32xf16,linalg_xdsl_b9,1909,4025,4022,0.0,0,0,249,0,0.13043478260869565,0.4543795620437956,548,0,0,0.287061288632792,0,0,1.0,1.0,1,3.046875,548,0.4612794612794613,640,195,64,0.3352540597171294,189,2117,4029,0.6223153483499214,2119 +softmax_polynomial,32xf32,baseline,4334,6896,6893,0.0,0,96,511,0,0.11790493770189202,0.4696691176470588,1088,0,0,0.25103830179972314,0,0,1.0,1.0,1,5.871165644171779,1088,0.527643064985451,974,957,163,0.22473465620673744,112,2563,6900,0.4757729580064606,2565 softmax_polynomial,32xf32,linalg_xdsl_b-1,3862,5957,5954,0.0,0,0,655,0,0.16960124287933714,0.5675909878682842,1154,0,0,0.2988089073019161,0,0,1.0,1.0,1,3.03125,1154,0.43156320119670905,1520,194,64,0.3935784567581564,525,2096,5961,0.6923873640600725,2098 softmax_polynomial,32xf32,linalg_xdsl_b0,3862,5957,5954,0.0,0,0,655,0,0.16960124287933714,0.5675909878682842,1154,0,0,0.2988089073019161,0,0,1.0,1.0,1,3.03125,1154,0.43156320119670905,1520,194,64,0.3935784567581564,525,2096,5961,0.6923873640600725,2098 softmax_polynomial,32xf32,linalg_xdsl_b1,3641,5757,5754,0.0,0,0,607,0,0.16671244163691293,0.5568807339449541,1090,0,0,0.2993683054106015,0,0,1.0,1.0,1,3.03125,1090,0.4335719968178202,1424,194,64,0.39110134578412525,493,2117,5761,0.6904696511947268,2119 @@ -173,6 +184,7 @@ softmax_polynomial,32xf32,linalg_xdsl_b6,3467,5559,5556,0.0,0,0,559,0,0.16123449 softmax_polynomial,32xf32,linalg_xdsl_b7,3467,5559,5556,0.0,0,0,559,0,0.16123449668301124,0.5448343079922028,1026,0,0,0.2959330833573695,0,0,1.0,1.0,1,3.03125,1026,0.4358538657604078,1328,194,64,0.3830400922988174,461,2093,5563,0.678973175656187,2095 softmax_polynomial,32xf32,linalg_xdsl_b8,3467,5559,5556,0.0,0,0,559,0,0.16123449668301124,0.5448343079922028,1026,0,0,0.2959330833573695,0,0,1.0,1.0,1,3.03125,1026,0.4358538657604078,1328,194,64,0.3830400922988174,461,2093,5563,0.678973175656187,2095 softmax_polynomial,32xf32,linalg_xdsl_b9,3283,5421,5418,0.0,0,0,511,0,0.15565031982942432,0.5311850311850311,962,0,0,0.2930246725555894,0,0,1.0,1.0,1,3.03125,962,0.43846855059252504,1232,194,64,0.3752665245202559,429,2139,5425,0.6682911970758453,2141 +softmax_polynomial,32xf64,baseline,5021,7630,7627,0.0,0,217,531,0,0.1057558255327624,0.433115823817292,1226,0,0,0.24417446723760208,0,0,1.0,1.0,1,7.734375,1226,0.4947538337368846,1252,1980,256,0.2493527185819558,162,2610,7634,0.4935271858195579,2612 softmax_polynomial,32xf64,linalg_xdsl_b-1,8377,10433,10430,0.0,0,0,1919,0,0.22907962277665037,0.7133828996282527,2690,0,0,0.32111734511161516,0,0,1.0,1.0,1,3.0,2690,0.4191336865066999,3728,384,128,0.4450280530022681,1121,2057,10437,0.7661453981138833,2059 softmax_polynomial,32xf64,linalg_xdsl_b0,8377,10433,10430,0.0,0,0,1919,0,0.22907962277665037,0.7133828996282527,2690,0,0,0.32111734511161516,0,0,1.0,1.0,1,3.0,2690,0.4191336865066999,3728,384,128,0.4450280530022681,1121,2057,10437,0.7661453981138833,2059 softmax_polynomial,32xf64,linalg_xdsl_b1,8377,10433,10430,0.0,0,0,1919,0,0.22907962277665037,0.7133828996282527,2690,0,0,0.32111734511161516,0,0,1.0,1.0,1,3.0,2690,0.4191336865066999,3728,384,128,0.4450280530022681,1121,2057,10437,0.7661453981138833,2059 @@ -191,6 +203,7 @@ softmax_polynomial,32xf64,linalg_xdsl_b6,7985,10042,10039,0.0,0,0,1823,0,0.22830 softmax_polynomial,32xf64,linalg_xdsl_b7,7612,9642,9639,0.0,0,0,1727,0,0.22687861271676302,0.709531635168447,2434,0,0,0.3197582764056752,0,0,1.0,1.0,1,3.0,2434,0.42125302872966425,3344,384,128,0.4393063583815029,993,2031,9646,0.7590646347871781,2033 softmax_polynomial,32xf64,linalg_xdsl_b8,7612,9642,9639,0.0,0,0,1727,0,0.22687861271676302,0.709531635168447,2434,0,0,0.3197582764056752,0,0,1.0,1.0,1,3.0,2434,0.42125302872966425,3344,384,128,0.4393063583815029,993,2031,9646,0.7590646347871781,2033 softmax_polynomial,32xf64,linalg_xdsl_b9,7612,9642,9639,0.0,0,0,1727,0,0.22687861271676302,0.709531635168447,2434,0,0,0.3197582764056752,0,0,1.0,1.0,1,3.0,2434,0.42125302872966425,3344,384,128,0.4393063583815029,993,2031,9646,0.7590646347871781,2033 +softmax_polynomial,48xf16,baseline,6344,8906,8903,0.0,0,144,865,0,0.13634930643127363,0.5192076830732293,1666,0,0,0.26261034047919296,0,0,1.0,1.0,1,6.215962441314554,1666,0.522257053291536,1524,1324,213,0.24022698612862547,146,2563,8910,0.5028373266078184,2565 softmax_polynomial,48xf16,linalg_xdsl_b-1,3002,5118,5115,0.0,0,0,481,0,0.16022651565622917,0.5073839662447257,948,0,0,0.3157894736842105,0,0,1.0,1.0,1,3.03125,948,0.4768611670020121,1040,194,64,0.346435709526982,333,2117,5122,0.6622251832111925,2119 softmax_polynomial,48xf16,linalg_xdsl_b0,2903,4995,4992,0.0,0,0,445,0,0.15328970031002412,0.49444444444444446,900,0,0,0.3100241129865656,0,0,1.0,1.0,1,3.03125,900,0.4817987152034261,968,194,64,0.3334481570788839,309,2093,4999,0.6434722700654496,2095 softmax_polynomial,48xf16,linalg_xdsl_b1,2903,4995,4992,0.0,0,0,445,0,0.15328970031002412,0.49444444444444446,900,0,0,0.3100241129865656,0,0,1.0,1.0,1,3.03125,900,0.4817987152034261,968,194,64,0.3334481570788839,309,2093,4999,0.6434722700654496,2095 @@ -203,6 +216,7 @@ softmax_polynomial,48xf16,linalg_xdsl_b6,2719,4857,4854,0.0,0,0,409,0,0.15042294 softmax_polynomial,48xf16,linalg_xdsl_b7,2593,4709,4706,0.0,0,0,373,0,0.14384882375626687,0.4639303482587065,804,0,0,0.3100655611261088,0,0,1.0,1.0,1,3.046875,804,0.49385749385749383,824,195,64,0.3177786347859622,261,2117,4713,0.627844195912071,2119 softmax_polynomial,48xf16,linalg_xdsl_b8,2593,4709,4706,0.0,0,0,373,0,0.14384882375626687,0.4639303482587065,804,0,0,0.3100655611261088,0,0,1.0,1.0,1,3.046875,804,0.49385749385749383,824,195,64,0.3177786347859622,261,2117,4713,0.627844195912071,2119 softmax_polynomial,48xf16,linalg_xdsl_b9,2593,4709,4706,0.0,0,0,373,0,0.14384882375626687,0.4639303482587065,804,0,0,0.3100655611261088,0,0,1.0,1.0,1,3.046875,804,0.49385749385749383,824,195,64,0.3177786347859622,261,2117,4713,0.627844195912071,2119 +softmax_polynomial,48xf32,baseline,6259,8826,8823,0.0,0,144,767,0,0.12254353730627895,0.4746287128712871,1616,0,0,0.25818820897907013,0,0,1.0,1.0,1,6.279620853080568,1616,0.549286199864038,1326,1325,211,0.21185492890238058,144,2568,8830,0.4700431378814507,2570 softmax_polynomial,48xf32,linalg_xdsl_b-1,5547,7647,7644,0.0,0,0,983,0,0.17721290787813232,0.573512252042007,1714,0,0,0.30899585361456644,0,0,1.0,1.0,1,3.03125,1714,0.4442716433385174,2144,194,64,0.38651523345952765,765,2101,7651,0.6955110870740941,2103 softmax_polynomial,48xf32,linalg_xdsl_b0,5547,7647,7644,0.0,0,0,983,0,0.17721290787813232,0.573512252042007,1714,0,0,0.30899585361456644,0,0,1.0,1.0,1,3.03125,1714,0.4442716433385174,2144,194,64,0.38651523345952765,765,2101,7651,0.6955110870740941,2103 softmax_polynomial,48xf32,linalg_xdsl_b1,5230,7351,7348,0.0,0,0,911,0,0.17418738049713192,0.5630407911001236,1618,0,0,0.30936902485659656,0,0,1.0,1.0,1,3.03125,1618,0.44720840243228305,2000,194,64,0.3824091778202677,717,2122,7355,0.6917782026768642,2124 @@ -221,6 +235,7 @@ softmax_polynomial,48xf32,linalg_xdsl_b6,4960,7057,7054,0.0,0,0,839,0,0.16915322 softmax_polynomial,48xf32,linalg_xdsl_b7,4960,7057,7054,0.0,0,0,839,0,0.16915322580645162,0.5512483574244416,1522,0,0,0.30685483870967745,0,0,1.0,1.0,1,3.03125,1522,0.45056246299585556,1856,194,64,0.3741935483870968,669,2098,7061,0.6810483870967743,2100 softmax_polynomial,48xf32,linalg_xdsl_b8,4960,7057,7054,0.0,0,0,839,0,0.16915322580645162,0.5512483574244416,1522,0,0,0.30685483870967745,0,0,1.0,1.0,1,3.03125,1522,0.45056246299585556,1856,194,64,0.3741935483870968,669,2098,7061,0.6810483870967743,2100 softmax_polynomial,48xf32,linalg_xdsl_b9,4680,6823,6820,0.0,0,0,767,0,0.1638888888888889,0.5378681626928471,1426,0,0,0.30470085470085473,0,0,1.0,1.0,1,3.03125,1426,0.4544295729764181,1712,194,64,0.3658119658119658,621,2144,6827,0.6705128205128206,2146 +softmax_polynomial,48xf64,baseline,7143,9749,9746,0.0,0,329,803,0,0.1124177516449671,0.43784078516902947,1834,0,0,0.25675486490270194,0,0,1.0,1.0,1,8.7375,1834,0.5285302593659942,1636,2796,320,0.22903541929161417,194,2607,9753,0.48579028419431614,2609 softmax_polynomial,48xf64,linalg_xdsl_b-1,12166,14222,14219,0.0,0,0,2879,0,0.23664310373171132,0.7165256346441016,4018,0,0,0.3302646720368239,0,0,1.0,1.0,1,3.0,4018,0.42918179876094853,5344,384,128,0.4392569455860595,1633,2057,14226,0.7695216176228834,2059 softmax_polynomial,48xf64,linalg_xdsl_b0,12166,14222,14219,0.0,0,0,2879,0,0.23664310373171132,0.7165256346441016,4018,0,0,0.3302646720368239,0,0,1.0,1.0,1,3.0,4018,0.42918179876094853,5344,384,128,0.4392569455860595,1633,2057,14226,0.7695216176228834,2059 softmax_polynomial,48xf64,linalg_xdsl_b1,12166,14222,14219,0.0,0,0,2879,0,0.23664310373171132,0.7165256346441016,4018,0,0,0.3302646720368239,0,0,1.0,1.0,1,3.0,4018,0.42918179876094853,5344,384,128,0.4392569455860595,1633,2057,14226,0.7695216176228834,2059 @@ -239,6 +254,7 @@ softmax_polynomial,48xf64,linalg_xdsl_b6,11574,13631,13628,0.0,0,0,2735,0,0.2363 softmax_polynomial,48xf64,linalg_xdsl_b7,11017,13047,13044,0.0,0,0,2591,0,0.2351819914677317,0.712988442487617,3634,0,0,0.3298538622129436,0,0,1.0,1.0,1,3.0,3634,0.4325160676029517,4768,384,128,0.4327856948352546,1441,2031,13051,0.7626395570481982,2033 softmax_polynomial,48xf64,linalg_xdsl_b8,11017,13047,13044,0.0,0,0,2591,0,0.2351819914677317,0.712988442487617,3634,0,0,0.3298538622129436,0,0,1.0,1.0,1,3.0,3634,0.4325160676029517,4768,384,128,0.4327856948352546,1441,2031,13051,0.7626395570481982,2033 softmax_polynomial,48xf64,linalg_xdsl_b9,11017,13047,13044,0.0,0,0,2591,0,0.2351819914677317,0.712988442487617,3634,0,0,0.3298538622129436,0,0,1.0,1.0,1,3.0,3634,0.4325160676029517,4768,384,128,0.4327856948352546,1441,2031,13051,0.7626395570481982,2033 +softmax_polynomial,64xf16,baseline,8563,11125,11122,0.0,0,192,1154,0,0.13476585308887074,0.5219357756671189,2211,0,0,0.25820390050216047,0,0,1.0,1.0,1,6.482758620689655,2211,0.46149029430181593,2580,1692,261,0.30129627467009223,178,2563,11129,0.5595001751722527,2565 softmax_polynomial,64xf16,linalg_xdsl_b-1,4127,6243,6240,0.0,0,0,642,0,0.1555609401502302,0.5123703112529928,1253,0,0,0.3036103707293433,0,0,1.0,1.0,1,3.03125,1253,0.3929131389150204,1936,194,64,0.4691058880542767,429,2117,6247,0.77271625878362,2119 softmax_polynomial,64xf16,linalg_xdsl_b0,3950,6042,6039,0.0,0,0,594,0,0.15037974683544303,0.49957947855340623,1189,0,0,0.3010126582278481,0,0,1.0,1.0,1,3.03125,1189,0.3925387916804226,1840,194,64,0.46582278481012657,397,2093,6046,0.7668354430379747,2095 softmax_polynomial,64xf16,linalg_xdsl_b1,3950,6042,6039,0.0,0,0,594,0,0.15037974683544303,0.49957947855340623,1189,0,0,0.3010126582278481,0,0,1.0,1.0,1,3.03125,1189,0.3925387916804226,1840,194,64,0.46582278481012657,397,2093,6046,0.7668354430379747,2095 @@ -251,6 +267,7 @@ softmax_polynomial,64xf16,linalg_xdsl_b6,3751,5889,5886,0.0,0,0,546,0,0.14556118 softmax_polynomial,64xf16,linalg_xdsl_b7,3560,5676,5673,0.0,0,0,498,0,0.1398876404494382,0.46936852026390197,1061,0,0,0.29803370786516853,0,0,1.0,1.0,1,3.03125,1061,0.39165743816906606,1648,194,64,0.46292134831460674,333,2117,5680,0.7609550561797753,2119 softmax_polynomial,64xf16,linalg_xdsl_b8,3560,5676,5673,0.0,0,0,498,0,0.1398876404494382,0.46936852026390197,1061,0,0,0.29803370786516853,0,0,1.0,1.0,1,3.03125,1061,0.39165743816906606,1648,194,64,0.46292134831460674,333,2117,5680,0.7609550561797753,2119 softmax_polynomial,64xf16,linalg_xdsl_b9,3560,5676,5673,0.0,0,0,498,0,0.1398876404494382,0.46936852026390197,1061,0,0,0.29803370786516853,0,0,1.0,1.0,1,3.03125,1061,0.39165743816906606,1648,194,64,0.46292134831460674,333,2117,5680,0.7609550561797753,2119 +softmax_polynomial,64xf32,baseline,8163,10757,10754,0.0,0,192,1024,0,0.12544407693250031,0.4920711196540125,2081,0,0,0.25493078525052065,0,0,1.0,1.0,1,6.494252873563219,2081,0.4464707144389616,2580,1695,261,0.3160602719588387,178,2595,10761,0.5709910572093593,2597 softmax_polynomial,64xf32,linalg_xdsl_b-1,7223,9323,9320,0.0,0,0,1312,0,0.1816419770178596,0.5933966530981456,2211,0,0,0.30610549633116435,0,0,1.0,1.0,1,3.03125,2211,0.39348638547784304,3408,194,64,0.4718261110341963,1005,2101,9327,0.7779316073653606,2103 softmax_polynomial,64xf32,linalg_xdsl_b0,7223,9323,9320,0.0,0,0,1312,0,0.1816419770178596,0.5933966530981456,2211,0,0,0.30610549633116435,0,0,1.0,1.0,1,3.03125,2211,0.39348638547784304,3408,194,64,0.4718261110341963,1005,2101,9327,0.7779316073653606,2103 softmax_polynomial,64xf32,linalg_xdsl_b1,6824,8945,8942,0.0,0,0,1216,0,0.17819460726846426,0.5837734037445992,2083,0,0,0.30524618991793667,0,0,1.0,1.0,1,3.03125,2083,0.3930930364219664,3216,194,64,0.4712778429073857,941,2122,8949,0.7765240328253225,2124 @@ -269,6 +286,7 @@ softmax_polynomial,64xf32,linalg_xdsl_b6,6442,8539,8536,0.0,0,0,1120,0,0.1738590 softmax_polynomial,64xf32,linalg_xdsl_b7,6442,8539,8536,0.0,0,0,1120,0,0.17385904998447688,0.5728900255754475,1955,0,0,0.3034771809996895,0,0,1.0,1.0,1,3.03125,1955,0.39264912633058846,3024,194,64,0.4694194349580876,877,2098,8543,0.772896615957777,2100 softmax_polynomial,64xf32,linalg_xdsl_b8,6442,8539,8536,0.0,0,0,1120,0,0.17385904998447688,0.5728900255754475,1955,0,0,0.3034771809996895,0,0,1.0,1.0,1,3.03125,1955,0.39264912633058846,3024,194,64,0.4694194349580876,877,2098,8543,0.772896615957777,2100 softmax_polynomial,64xf32,linalg_xdsl_b9,6067,8210,8207,0.0,0,0,1024,0,0.16878193505851327,0.5604816639299398,1827,0,0,0.3011373001483435,0,0,1.0,1.0,1,3.03125,1827,0.3921442369607212,2832,194,64,0.46678753914620075,813,2144,8214,0.7679248392945442,2146 +softmax_polynomial,64xf64,baseline,9272,11901,11891,0.0,0,441,1076,0,0.11604831751509923,0.45229087852038674,2379,0,0,0.2565789473684211,0,0,1.0,1.0,1,9.378238341968911,2379,0.4487832484436899,2922,3620,386,0.31514236410698876,228,2630,11905,0.5717213114754098,2632 softmax_polynomial,64xf64,linalg_xdsl_b-1,15932,17988,17985,0.0,0,0,3840,0,0.24102435350238513,0.7268597387847814,5283,0,0,0.3315967863419533,0,0,1.0,1.0,1,3.0,5283,0.41007529302181167,7600,384,128,0.4770273663068039,2145,2057,17992,0.8086241526487572,2059 softmax_polynomial,64xf64,linalg_xdsl_b0,15932,17988,17985,0.0,0,0,3840,0,0.24102435350238513,0.7268597387847814,5283,0,0,0.3315967863419533,0,0,1.0,1.0,1,3.0,5283,0.41007529302181167,7600,384,128,0.4770273663068039,2145,2057,17992,0.8086241526487572,2059 softmax_polynomial,64xf64,linalg_xdsl_b1,15932,17988,17985,0.0,0,0,3840,0,0.24102435350238513,0.7268597387847814,5283,0,0,0.3315967863419533,0,0,1.0,1.0,1,3.0,5283,0.41007529302181167,7600,384,128,0.4770273663068039,2145,2057,17992,0.8086241526487572,2059 @@ -287,6 +305,7 @@ softmax_polynomial,64xf64,linalg_xdsl_b6,15149,17211,17208,0.0,0,0,3648,0,0.2408 softmax_polynomial,64xf64,linalg_xdsl_b7,14389,16424,16421,0.0,0,0,3456,0,0.24018347348669122,0.7243764409976944,4771,0,0,0.33157272916811453,0,0,1.0,1.0,1,3.0,4771,0.4111867620442989,6832,384,128,0.4748071443463757,1889,2036,16428,0.8063798735144903,2038 softmax_polynomial,64xf64,linalg_xdsl_b8,14389,16424,16421,0.0,0,0,3456,0,0.24018347348669122,0.7243764409976944,4771,0,0,0.33157272916811453,0,0,1.0,1.0,1,3.0,4771,0.4111867620442989,6832,384,128,0.4748071443463757,1889,2036,16428,0.8063798735144903,2038 softmax_polynomial,64xf64,linalg_xdsl_b9,14389,16424,16421,0.0,0,0,3456,0,0.24018347348669122,0.7243764409976944,4771,0,0,0.33157272916811453,0,0,1.0,1.0,1,3.0,4771,0.4111867620442989,6832,384,128,0.4748071443463757,1889,2036,16428,0.8063798735144903,2038 +softmax_polynomial,80xf16,baseline,10658,13225,13222,0.0,0,240,1444,0,0.13548508162882342,0.5237577076532463,2757,0,0,0.25867892662788516,0,0,1.0,1.0,1,6.679611650485437,2757,0.4479285134037368,3398,2064,309,0.31882154250328393,210,2568,13229,0.5775004691311691,2570 softmax_polynomial,80xf16,linalg_xdsl_b-1,5123,7244,7241,0.0,0,0,804,0,0.15693929338278353,0.5157152020525978,1559,0,0,0.30431387858676556,0,0,1.0,1.0,1,3.03125,1559,0.37539128340958344,2594,194,64,0.5063439390981846,525,2122,7248,0.8106578176849502,2124 softmax_polynomial,80xf16,linalg_xdsl_b0,4883,6980,6977,0.0,0,0,744,0,0.15236534917059186,0.5030425963488844,1479,0,0,0.3028875691173459,0,0,1.0,1.0,1,3.03125,1479,0.3741462180622312,2474,194,64,0.5066557444194143,485,2098,6984,0.8095433135367602,2100 softmax_polynomial,80xf16,linalg_xdsl_b1,4883,6980,6977,0.0,0,0,744,0,0.15236534917059186,0.5030425963488844,1479,0,0,0.3028875691173459,0,0,1.0,1.0,1,3.03125,1479,0.3741462180622312,2474,194,64,0.5066557444194143,485,2098,6984,0.8095433135367602,2100 @@ -299,6 +318,7 @@ softmax_polynomial,80xf16,linalg_xdsl_b6,4632,6775,6772,0.0,0,0,684,0,0.14766839 softmax_polynomial,80xf16,linalg_xdsl_b7,4410,6531,6528,0.0,0,0,624,0,0.1414965986394558,0.47308567096285065,1319,0,0,0.29909297052154193,0,0,1.0,1.0,1,3.03125,1319,0.3712355755699409,2234,194,64,0.5065759637188209,405,2122,6535,0.8056689342403628,2124 softmax_polynomial,80xf16,linalg_xdsl_b8,4410,6531,6528,0.0,0,0,624,0,0.1414965986394558,0.47308567096285065,1319,0,0,0.29909297052154193,0,0,1.0,1.0,1,3.03125,1319,0.3712355755699409,2234,194,64,0.5065759637188209,405,2122,6535,0.8056689342403628,2124 softmax_polynomial,80xf16,linalg_xdsl_b9,4410,6531,6528,0.0,0,0,624,0,0.1414965986394558,0.47308567096285065,1319,0,0,0.29909297052154193,0,0,1.0,1.0,1,3.03125,1319,0.3712355755699409,2234,194,64,0.5065759637188209,405,2122,6535,0.8056689342403628,2124 +softmax_polynomial,80xf32,baseline,10171,12765,12762,0.0,0,240,1282,0,0.12604463671222102,0.49402697495183046,2595,0,0,0.2551371546553928,0,0,1.0,1.0,1,6.689320388349515,2595,0.4330051727014851,3398,2067,309,0.33408711041195555,210,2595,12769,0.5892242650673483,2597 softmax_polynomial,80xf32,linalg_xdsl_b-1,8959,11059,11056,0.0,0,0,1642,0,0.18327938385980577,0.5955749002538991,2757,0,0,0.3077352383078469,0,0,1.0,1.0,1,3.03125,2757,0.3833959115561118,4434,194,64,0.4949213081817167,1245,2101,11063,0.8026565464895636,2103 softmax_polynomial,80xf32,linalg_xdsl_b0,8959,11059,11056,0.0,0,0,1642,0,0.18327938385980577,0.5955749002538991,2757,0,0,0.3077352383078469,0,0,1.0,1.0,1,3.03125,2757,0.3833959115561118,4434,194,64,0.4949213081817167,1245,2101,11063,0.8026565464895636,2103 softmax_polynomial,80xf32,linalg_xdsl_b1,8503,10624,10621,0.0,0,0,1522,0,0.17899564859461367,0.5860608394301117,2597,0,0,0.3054216159002705,0,0,1.0,1.0,1,3.03125,2597,0.38241790605212783,4194,194,64,0.49323768081853464,1165,2122,10628,0.7986592967188051,2124 @@ -317,6 +337,7 @@ softmax_polynomial,80xf32,linalg_xdsl_b6,8015,10112,10109,0.0,0,0,1402,0,0.17492 softmax_polynomial,80xf32,linalg_xdsl_b7,8015,10112,10109,0.0,0,0,1402,0,0.17492202121023082,0.5752974969224456,2437,0,0,0.3040548970679975,0,0,1.0,1.0,1,3.03125,2437,0.3813174777030199,3954,194,64,0.493325015595758,1085,2098,10116,0.7973799126637555,2100 softmax_polynomial,80xf32,linalg_xdsl_b8,8015,10112,10109,0.0,0,0,1402,0,0.17492202121023082,0.5752974969224456,2437,0,0,0.3040548970679975,0,0,1.0,1.0,1,3.03125,2437,0.3813174777030199,3954,194,64,0.493325015595758,1085,2098,10116,0.7973799126637555,2100 softmax_polynomial,80xf32,linalg_xdsl_b9,7521,9664,9661,0.0,0,0,1282,0,0.17045605637548197,0.5630215195432586,2277,0,0,0.30275229357798167,0,0,1.0,1.0,1,3.046875,2277,0.3800701051577366,3714,195,64,0.4938173115277224,1005,2144,9668,0.7965696051057041,2146 +softmax_polynomial,80xf64,baseline,11475,14104,14101,0.0,0,553,1350,0,0.11764705882352941,0.45408678102926336,2973,0,0,0.25908496732026143,0,0,1.0,1.0,1,9.866666666666667,2973,0.4407709414381023,3772,4440,450,0.3287145969498911,260,2630,14108,0.5877995642701526,2632 softmax_polynomial,80xf64,linalg_xdsl_b-1,19791,21852,21849,0.0,0,0,4802,0,0.24263554140771057,0.7279066242231317,6597,0,0,0.3333333333333333,0,0,1.0,1.0,1,3.0,6597,0.406845513413506,9618,384,128,0.4859784750644232,2657,2062,21856,0.8193118083977565,2064 softmax_polynomial,80xf64,linalg_xdsl_b0,19791,21852,21849,0.0,0,0,4802,0,0.24263554140771057,0.7279066242231317,6597,0,0,0.3333333333333333,0,0,1.0,1.0,1,3.0,6597,0.406845513413506,9618,384,128,0.4859784750644232,2657,2062,21856,0.8193118083977565,2064 softmax_polynomial,80xf64,linalg_xdsl_b1,19791,21852,21849,0.0,0,0,4802,0,0.24263554140771057,0.7279066242231317,6597,0,0,0.3333333333333333,0,0,1.0,1.0,1,3.0,6597,0.406845513413506,9618,384,128,0.4859784750644232,2657,2062,21856,0.8193118083977565,2064 @@ -335,6 +356,7 @@ softmax_polynomial,80xf64,linalg_xdsl_b6,18821,20883,20880,0.0,0,0,4562,0,0.2423 softmax_polynomial,80xf64,linalg_xdsl_b7,17873,19908,19905,0.0,0,0,4322,0,0.2418172662675544,0.7255329864025516,5957,0,0,0.33329603312258715,0,0,1.0,1.0,1,3.0,5957,0.40759493670886077,8658,384,128,0.48441783696077884,2337,2036,19912,0.8177138700833659,2038 softmax_polynomial,80xf64,linalg_xdsl_b8,17873,19908,19905,0.0,0,0,4322,0,0.2418172662675544,0.7255329864025516,5957,0,0,0.33329603312258715,0,0,1.0,1.0,1,3.0,5957,0.40759493670886077,8658,384,128,0.48441783696077884,2337,2036,19912,0.8177138700833659,2038 softmax_polynomial,80xf64,linalg_xdsl_b9,17873,19908,19905,0.0,0,0,4322,0,0.2418172662675544,0.7255329864025516,5957,0,0,0.33329603312258715,0,0,1.0,1.0,1,3.0,5957,0.40759493670886077,8658,384,128,0.48441783696077884,2337,2036,19912,0.8177138700833659,2038 +softmax_polynomial,96xf16,baseline,12674,15241,15238,0.0,0,288,1732,0,0.13665772447530378,0.5246894880339291,3301,0,0,0.2604544737257377,0,0,1.0,1.0,1,6.812324929971989,3301,0.4507715417178752,4022,2432,357,0.3173425911314502,242,2568,15245,0.577797064857188,2570 softmax_polynomial,96xf16,linalg_xdsl_b-1,6031,8152,8149,0.0,0,0,964,0,0.15984082241750952,0.5174449812130971,1863,0,0,0.30890399602056046,0,0,1.0,1.0,1,3.03125,1863,0.3785815891079049,3058,194,64,0.5070469242248383,621,2122,8156,0.8159509202453987,2124 softmax_polynomial,96xf16,linalg_xdsl_b0,5743,7840,7837,0.0,0,0,892,0,0.15531951941493993,0.5048104131295982,1767,0,0,0.3076789134598642,0,0,1.0,1.0,1,3.03125,1767,0.37748344370860926,2914,194,64,0.5074003134250392,573,2098,7844,0.8150792268849034,2100 softmax_polynomial,96xf16,linalg_xdsl_b1,5743,7840,7837,0.0,0,0,892,0,0.15531951941493993,0.5048104131295982,1767,0,0,0.3076789134598642,0,0,1.0,1.0,1,3.03125,1767,0.37748344370860926,2914,194,64,0.5074003134250392,573,2098,7844,0.8150792268849034,2100 @@ -347,6 +369,7 @@ softmax_polynomial,96xf16,linalg_xdsl_b6,5444,7587,7584,0.0,0,0,820,0,0.15062454 softmax_polynomial,96xf16,linalg_xdsl_b7,5174,7295,7292,0.0,0,0,748,0,0.14456899884035562,0.4749206349206349,1575,0,0,0.30440664862775413,0,0,1.0,1.0,1,3.03125,1575,0.3749107355391573,2626,194,64,0.507537688442211,477,2122,7299,0.8119443370699652,2124 softmax_polynomial,96xf16,linalg_xdsl_b8,5174,7295,7292,0.0,0,0,748,0,0.14456899884035562,0.4749206349206349,1575,0,0,0.30440664862775413,0,0,1.0,1.0,1,3.03125,1575,0.3749107355391573,2626,194,64,0.507537688442211,477,2122,7299,0.8119443370699652,2124 softmax_polynomial,96xf16,linalg_xdsl_b9,5174,7295,7292,0.0,0,0,748,0,0.14456899884035562,0.4749206349206349,1575,0,0,0.30440664862775413,0,0,1.0,1.0,1,3.03125,1575,0.3749107355391573,2626,194,64,0.507537688442211,477,2122,7299,0.8119443370699652,2124 +softmax_polynomial,96xf32,baseline,12091,14685,14682,0.0,0,288,1538,0,0.12720205111239766,0.4950112648857419,3107,0,0,0.2569679927218592,0,0,1.0,1.0,1,6.820728291316526,3107,0.43582550147285737,4022,2435,357,0.3326441154577785,242,2595,14689,0.5896121081796377,2597 softmax_polynomial,96xf32,linalg_xdsl_b-1,10639,12739,12736,0.0,0,0,1970,0,0.18516777892659084,0.5967888518630718,3301,0,0,0.3102735219475515,0,0,1.0,1.0,1,3.03125,3301,0.385315746469009,5266,194,64,0.49497133189209513,1485,2101,12743,0.8052448538396466,2103 softmax_polynomial,96xf32,linalg_xdsl_b0,10639,12739,12736,0.0,0,0,1970,0,0.18516777892659084,0.5967888518630718,3301,0,0,0.3102735219475515,0,0,1.0,1.0,1,3.03125,3301,0.385315746469009,5266,194,64,0.49497133189209513,1485,2101,12743,0.8052448538396466,2103 softmax_polynomial,96xf32,linalg_xdsl_b1,10087,12208,12205,0.0,0,0,1826,0,0.18102508178844057,0.587327114827919,3109,0,0,0.3082184990581937,0,0,1.0,1.0,1,3.03125,3109,0.38444416965500183,4978,194,64,0.4935064935064935,1389,2122,12212,0.8017249925646872,2124 @@ -365,6 +388,7 @@ softmax_polynomial,96xf32,linalg_xdsl_b6,9503,11600,11597,0.0,0,0,1682,0,0.17699 softmax_polynomial,96xf32,linalg_xdsl_b7,9503,11600,11597,0.0,0,0,1682,0,0.17699673787225087,0.5766198148782996,2917,0,0,0.3069556982005682,0,0,1.0,1.0,1,3.03125,2917,0.38346260023662415,4690,194,64,0.49352835946543194,1293,2098,11604,0.8004840576660002,2100 softmax_polynomial,96xf32,linalg_xdsl_b8,9503,11600,11597,0.0,0,0,1682,0,0.17699673787225087,0.5766198148782996,2917,0,0,0.3069556982005682,0,0,1.0,1.0,1,3.03125,2917,0.38346260023662415,4690,194,64,0.49352835946543194,1293,2098,11604,0.8004840576660002,2100 softmax_polynomial,96xf32,linalg_xdsl_b9,8913,11056,11053,0.0,0,0,1538,0,0.17255693930214294,0.5644036697247706,2725,0,0,0.3057331986985302,0,0,1.0,1.0,1,3.046875,2725,0.38234881436789675,4402,195,64,0.4938853360260294,1197,2144,11060,0.7996185347245597,2146 +softmax_polynomial,96xf64,baseline,13603,16232,16229,0.0,0,665,1622,0,0.11923840329339117,0.4549789621318373,3565,0,0,0.26207454238035727,0,0,1.0,1.0,1,10.22568093385214,3565,0.446015263355436,4428,5256,514,0.3255164301992208,292,2630,16236,0.587590972579578,2632 softmax_polynomial,96xf64,linalg_xdsl_b-1,23567,25628,25625,0.0,0,0,5762,0,0.24449442016378836,0.7285371096219497,7909,0,0,0.33559638477532144,0,0,1.0,1.0,1,3.0,7909,0.4087127280243915,11442,384,128,0.48550939873552,3169,2062,25632,0.8211057835108415,2064 softmax_polynomial,96xf64,linalg_xdsl_b0,23567,25628,25625,0.0,0,0,5762,0,0.24449442016378836,0.7285371096219497,7909,0,0,0.33559638477532144,0,0,1.0,1.0,1,3.0,7909,0.4087127280243915,11442,384,128,0.48550939873552,3169,2062,25632,0.8211057835108415,2064 softmax_polynomial,96xf64,linalg_xdsl_b1,23567,25628,25625,0.0,0,0,5762,0,0.24449442016378836,0.7285371096219497,7909,0,0,0.33559638477532144,0,0,1.0,1.0,1,3.0,7909,0.4087127280243915,11442,384,128,0.48550939873552,3169,2062,25632,0.8211057835108415,2064 From e1512e29fc14c81ccb1b119d24b1713a3ae1b0bb Mon Sep 17 00:00:00 2001 From: szerdick Date: Mon, 1 Jun 2026 14:54:20 +0100 Subject: [PATCH 28/33] a lot of renaming of plots --- Snakefile | 39 ++--- plots-mia-thesis/output/rq2_plots.pdf | Bin 20149 -> 23699 bytes .../output/{rq34_plots.pdf => rq31_plots.pdf} | Bin 21285 -> 21304 bytes .../output/{rq1_plots.pdf => rq32_plots.pdf} | Bin 23699 -> 20149 bytes plots-mia-thesis/output/rq33_plots.pdf | Bin 48076 -> 0 bytes plots-mia-thesis/output/rq40_plots.pdf | Bin 20898 -> 20924 bytes plots-mia-thesis/output/rq42_plots.pdf | Bin 23402 -> 24056 bytes plots-mia-thesis/output/rq44_plots.pdf | Bin 22284 -> 22167 bytes plots-mia-thesis/plot_rq1.py | 131 --------------- plots-mia-thesis/plot_rq2.py | 152 +++++++++--------- .../{plot_rq34.py => plot_rq31.py} | 12 +- plots-mia-thesis/plot_rq32.py | 125 ++++++++++++++ plots-mia-thesis/plot_rq33.py | 75 --------- plots-mia-thesis/plot_rq40.py | 4 +- plots-mia-thesis/plot_rq42.py | 10 +- plots-mia-thesis/plot_rq43.py | 6 +- plots-mia-thesis/plot_rq44.py | 2 +- 17 files changed, 236 insertions(+), 320 deletions(-) rename plots-mia-thesis/output/{rq34_plots.pdf => rq31_plots.pdf} (85%) rename plots-mia-thesis/output/{rq1_plots.pdf => rq32_plots.pdf} (55%) delete mode 100644 plots-mia-thesis/output/rq33_plots.pdf delete mode 100644 plots-mia-thesis/plot_rq1.py rename plots-mia-thesis/{plot_rq34.py => plot_rq31.py} (93%) create mode 100644 plots-mia-thesis/plot_rq32.py delete mode 100644 plots-mia-thesis/plot_rq33.py diff --git a/Snakefile b/Snakefile index 1c676c13..096672dd 100644 --- a/Snakefile +++ b/Snakefile @@ -456,7 +456,7 @@ rule exp_macro: rule exp_polynomial: input: "results/kernels.exp_polynomial.csv", - "plots-mia-thesis/output/rq1_plots.pdf", + "plots-mia-thesis/output/rq2_plots.pdf", rule softmax_polynomial: @@ -1008,15 +1008,15 @@ rule xdsl_kernel_generate_source_chebyshev: PLOTS_DIR = "plots-mia-thesis" PLOTS_OUTPUT = PLOTS_DIR + "/output" -rule plot_rq1: +rule plot_rq2: input: - script = PLOTS_DIR + "/plot_rq1.py", + script = PLOTS_DIR + "/plot_rq2.py", utils = PLOTS_DIR + "/plot_utils.py", micro = "results/kernels.exp_micro.csv", poly = "results/kernels.exp_polynomial.csv", macro = "results/kernels.exp_macro.csv", output: - PLOTS_OUTPUT + "/rq1_plots.pdf", + PLOTS_OUTPUT + "/rq2_plots.pdf", shell: "python {input.script} --exp-micro {input.micro} --exp-polynomial {input.poly} --exp-macro {input.macro} -o {output}" @@ -1047,30 +1047,21 @@ rule plot_rq13: shell: "python {input.script} -o {output}" -rule plot_rq33: +rule plot_rq31: input: - script = PLOTS_DIR + "/plot_rq33.py", + script = PLOTS_DIR + "/plot_rq31.py", utils = PLOTS_DIR + "/plot_utils.py", output: - PLOTS_OUTPUT + "/rq33_plots.pdf", + PLOTS_OUTPUT + "/rq31_plots.pdf", shell: "python {input.script} -o {output}" -rule plot_rq34: +rule plot_rq32: input: - script = PLOTS_DIR + "/plot_rq34.py", + script = PLOTS_DIR + "/plot_rq32.py", utils = PLOTS_DIR + "/plot_utils.py", output: - PLOTS_OUTPUT + "/rq34_plots.pdf", - shell: - "python {input.script} -o {output}" - -rule plot_rq2: - input: - script = PLOTS_DIR + "/plot_rq2.py", - utils = PLOTS_DIR + "/plot_utils.py", - output: - PLOTS_OUTPUT + "/rq2_plots.pdf", + PLOTS_OUTPUT + "/rq32_plots.pdf", shell: "python {input.script} -o {output}" @@ -1087,7 +1078,7 @@ rule plot_rq42: input: script = PLOTS_DIR + "/plot_rq42.py", utils = PLOTS_DIR + "/plot_utils.py", - rq34 = PLOTS_DIR + "/plot_rq34.py", + rq31 = PLOTS_DIR + "/plot_rq31.py", softmax = "results/kernels.softmax_polynomial.csv", output: PLOTS_OUTPUT + "/rq42_plots.pdf", @@ -1108,7 +1099,7 @@ rule plot_rq44: input: script = PLOTS_DIR + "/plot_rq44.py", utils = PLOTS_DIR + "/plot_utils.py", - rq34 = PLOTS_DIR + "/plot_rq34.py", + rq31 = PLOTS_DIR + "/plot_rq31.py", rq40 = PLOTS_DIR + "/plot_rq40.py", rq43 = PLOTS_DIR + "/plot_rq43.py", softmax = "results/kernels.softmax_polynomial.csv", @@ -1120,12 +1111,12 @@ rule plot_rq44: rule plots_mia_thesis: input: - PLOTS_OUTPUT + "/rq1_plots.pdf", + PLOTS_OUTPUT + "/rq2_plots.pdf", PLOTS_OUTPUT + "/rq11_plots.pdf", PLOTS_OUTPUT + "/rq12_plots.pdf", PLOTS_OUTPUT + "/rq13_plots.pdf", - 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z848ul!cGX1hBmaa#7YqX06-{8!%)vz3M9z|`1#}V;v)a`0E9sSQWy8YunT+A(2H@> z($W{=U;r5En<0!)3J5|;8Sx>ZFyO@)DEO~E5C8=HJ3j~jk-BhJ8UVgfQ%V|qAx;V; z{fjH|f5-wZfB`_Iz@Wdt0HgpAz=b`a)Zd^1QV<~YLL3zGUy*V3aX)Fm1?2(KV915S z(oo3XDgdNml7F)Uz(5zlz;I~(1_Og3CI4mu1c0ReE(`=fF3Jj!mb?%L#KHNi2oMMY z{+IDjzCa*Y@^>8aKX(lXk-E@3pfun@LR{l7Bm_Y&v;>F~;cv!3khJvwwB)D$Krj$? zp)gMU3x~n~+q+*(z*5i)XCb(pf2)AQcQH;<6372%n*XQ(fkFPhNI*#d^nwbKz&{fH z=d2_cdO;aUsf(&YaZUbR7y17`bto8ep$P82T}TLpf-dwOiu=a?CIW@Q{=TdrfYk5L Z?l)mSAA6LE8H^kTfspg@sq1Ty{~w`4BE pd.Series: - return ( - df[df["precision"] == precision] - .groupby("degree")[metric] - .mean() - .sort_index() - ) - - -def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: - return df.loc[df["precision"] == precision, metric].mean() - - -def plot_rq1( - poly_df: pd.DataFrame, - baseline_df: pd.DataFrame, - vendor_df: pd.DataFrame, -) -> plt.Figure: - fig, axes = plt.subplots(2, len(PRECISIONS), figsize=(len(PRECISIONS) * 5, 8)) - - metrics = [ - ("cycles_per_byte", "Avg cycles / byte"), - ("fpss_fpu_occupancy", "Avg FPU utilization"), - ] - - for row_idx, (metric, ylabel) in enumerate(metrics): - for col_idx, precision in enumerate(PRECISIONS): - ax = axes[row_idx, col_idx] - series = avg_per_degree(poly_df, precision, metric) - baseline = avg_baseline(baseline_df, precision, metric) - vendor = avg_baseline(vendor_df, precision, metric) - - if not series.empty: - ax.plot( - series.index, series.values, - marker="o", linestyle="none", color="#33a02c", - label="Chebyshev polynomial", - ) - if not np.isnan(baseline): - ax.axhline( - baseline, color="#1f78b4", linestyle="--", - label=f"libm baseline ({baseline:.3g})", - ) - # vendor kernel (snrt) is only measured in f64 -> NaN elsewhere - if not np.isnan(vendor): - ax.axhline( - vendor, color="#e31a1c", linestyle="-.", - label=f"vendor kernel ({vendor:.3g})", - ) - - ax.set_title(f"{precision}") - ax.set_xlabel("Chebyshev degree") - ax.set_ylabel(ylabel) - if not series.empty: - ax.set_xticks(series.index) - ax.grid(True, alpha=0.3) - ax.legend(loc="best", fontsize=8) - - fig.tight_layout() - return fig - - -def main() -> None: - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument( - "--exp-micro", default="results/kernels.exp_micro.csv", - help="Input CSV with libm baseline measurements", - ) - parser.add_argument( - "--exp-polynomial", default="results/kernels.exp_polynomial.csv", - help="Input CSV with Chebyshev polynomial degree-variant measurements", - ) - parser.add_argument( - "--exp-macro", default="results/kernels.exp_macro.csv", - help="Input CSV with vendor kernel (snrt) measurements", - ) - parser.add_argument( - "--output", "-o", default="plots-mia-thesis/output/rq1_plots.pdf", - help="Output plot file", - ) - args = parser.parse_args() - - Path(args.output).parent.mkdir(parents=True, exist_ok=True) - - poly_df = load_chebyshev_csv(args.exp_polynomial) - baseline_df = load_baseline_csv(args.exp_micro) - vendor_df = load_vendor_csv(args.exp_macro) - - fig = plot_rq1(poly_df, baseline_df, vendor_df) - savefig(fig, args.output) - print(f"Saved plot to {args.output}") - - -if __name__ == "__main__": - main() diff --git a/plots-mia-thesis/plot_rq2.py b/plots-mia-thesis/plot_rq2.py index 5d5cacd2..592ab69f 100644 --- a/plots-mia-thesis/plot_rq2.py +++ b/plots-mia-thesis/plot_rq2.py @@ -1,60 +1,43 @@ #!/usr/bin/env python3 """ -RQ2 plot: accuracy vs performance Pareto, one panel per precision (f16/f32/f64). +RQ2 plot: how does the Chebyshev polynomial degree affect cycles/byte and FPU +utilization of the xDSL polynomial pipeline, compared to the libm baseline? - x = max_bits_lost (the accuracy bound passed to lower-exp-to-polynomial; - moving right = looser accuracy) - y = avg cycles / byte across input sizes N (lower = faster) - -The lower-left corner is "best" (more accurate AND faster). A reasonable -pipeline should produce a monotone-decreasing curve: relaxing the bound buys -performance. - -Source data is `kernels.exp_micro.csv`. The plot expects rows with -`impl = linalg_xdsl_b` where is the integer `max_bits_lost` (negative -allowed, e.g. `linalg_xdsl_b-1` for correctly-rounded). The Snakefile does -not yet emit these variants — once it does, the plot picks them up -automatically. Until then only the libm baseline reference line is drawn. +For each precision (f16, f32, f64) produce two plots: + - degree vs. avg cycles/byte (averaged across input sizes N) + - degree vs. avg FPU utilization (averaged across input sizes N) +The libm baseline (from exp_micro) is drawn as a horizontal reference line. +The vendor kernel (snrt, from exp_macro) is drawn as a second horizontal +reference line; it is only measured in f64, so it appears on the f64 plots. Usage: - python plot_rq2.py [-i results/kernels.exp_micro.csv] \\ - [-o plots-mia-thesis/output/rq2_plots.pdf] + python plot_rq2.py \ + [--exp-micro results/kernels.exp_micro.csv] \ + [--exp-polynomial results/kernels.exp_polynomial.csv] \ + [--exp-macro results/kernels.exp_macro.csv] \ + [--output plots-mia-thesis/output/rq2_plots.pdf] """ import argparse -import re from pathlib import Path -import matplotlib.pyplot as plt import numpy as np import pandas as pd +import matplotlib.pyplot as plt from plot_utils import ( PRECISIONS, - annotate_kernel_df, load_baseline_csv, + load_chebyshev_csv, + load_vendor_csv, savefig, ) -# Inferred naming: `linalg_xdsl_b` where is the integer max_bits_lost -# the pass was invoked with (e.g. `linalg_xdsl_b-1`, `linalg_xdsl_b0`, -# `linalg_xdsl_b4`). Negative values are correctly-rounded; 0 is libm-grade; -# higher values relax the bound. -BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") - - -def load_bits_lost_csv(csv_path: str) -> pd.DataFrame: - df = pd.read_csv(csv_path) - df = df[df["impl"].str.match(BITS_LOST_VARIANT_RE)].copy() - df["max_bits_lost"] = df["impl"].str.extract(BITS_LOST_VARIANT_RE).astype(int) - return annotate_kernel_df(df) - - -def avg_per_bits_lost(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: +def avg_per_degree(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: return ( df[df["precision"] == precision] - .groupby("max_bits_lost")[metric] + .groupby("degree")[metric] .mean() .sort_index() ) @@ -64,37 +47,51 @@ def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: return df.loc[df["precision"] == precision, metric].mean() -def plot_rq2(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: - fig, axes = plt.subplots( - 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False - ) +def plot_rq2( + poly_df: pd.DataFrame, + baseline_df: pd.DataFrame, + vendor_df: pd.DataFrame, +) -> plt.Figure: + fig, axes = plt.subplots(2, len(PRECISIONS), figsize=(len(PRECISIONS) * 5, 8)) + + metrics = [ + ("cycles_per_byte", "Avg cycles / byte"), + ("fpss_fpu_occupancy", "Avg FPU utilization"), + ] + + for row_idx, (metric, ylabel) in enumerate(metrics): + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[row_idx, col_idx] + series = avg_per_degree(poly_df, precision, metric) + baseline = avg_baseline(baseline_df, precision, metric) + vendor = avg_baseline(vendor_df, precision, metric) + + if not series.empty: + ax.plot( + series.index, series.values, + marker="o", linestyle="none", color="#33a02c", + label="Chebyshev polynomial", + ) + if not np.isnan(baseline): + ax.axhline( + baseline, color="#1f78b4", linestyle="--", + label=f"libm baseline ({baseline:.3g})", + ) + # vendor kernel (snrt) is only measured in f64 -> NaN elsewhere + if not np.isnan(vendor): + ax.axhline( + vendor, color="#e31a1c", linestyle="-.", + label=f"vendor kernel ({vendor:.3g})", + ) + + ax.set_title(f"{precision}") + ax.set_xlabel("Chebyshev degree") + ax.set_ylabel(ylabel) + if not series.empty: + ax.set_xticks(series.index) + ax.grid(True, alpha=0.3) + ax.legend(loc="best", fontsize=8) - for col_idx, precision in enumerate(PRECISIONS): - ax = axes[col_idx] - series = avg_per_bits_lost(poly_df, precision, "cycles_per_byte") - baseline = avg_baseline(baseline_df, precision, "cycles_per_byte") - - if not series.empty: - ax.plot( - series.index, series.values, - marker="o", linestyle="none", color="#33a02c", - label="Chebyshev polynomial", - ) - if not np.isnan(baseline): - ax.axhline( - baseline, color="#1f78b4", linestyle="--", - label=f"libm baseline ({baseline:.3g})", - ) - - ax.set_title(precision) - ax.set_xlabel(r"max_bits_lost (looser $\rightarrow$)") - ax.set_ylabel("avg cycles / byte") - if not series.empty: - ax.set_xticks(series.index) - ax.grid(True, alpha=0.3) - ax.legend(loc="best", fontsize=8) - - fig.suptitle("Accuracy vs performance Pareto for our polynomial approximation of exp(x)") fig.tight_layout() return fig @@ -102,21 +99,30 @@ def plot_rq2(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument( - "--input", "-i", - default="results/kernels.exp_micro.csv", - help="Input CSV with exp_micro measurements", + "--exp-micro", default="results/kernels.exp_micro.csv", + help="Input CSV with libm baseline measurements", + ) + parser.add_argument( + "--exp-polynomial", default="results/kernels.exp_polynomial.csv", + help="Input CSV with Chebyshev polynomial degree-variant measurements", ) parser.add_argument( - "--output", "-o", - default="plots-mia-thesis/output/rq2_plots.pdf", + "--exp-macro", default="results/kernels.exp_macro.csv", + help="Input CSV with vendor kernel (snrt) measurements", + ) + parser.add_argument( + "--output", "-o", default="plots-mia-thesis/output/rq2_plots.pdf", help="Output plot file", ) args = parser.parse_args() Path(args.output).parent.mkdir(parents=True, exist_ok=True) - poly_df = load_bits_lost_csv(args.input) - baseline_df = load_baseline_csv(args.input) - fig = plot_rq2(poly_df, baseline_df) + + poly_df = load_chebyshev_csv(args.exp_polynomial) + baseline_df = load_baseline_csv(args.exp_micro) + vendor_df = load_vendor_csv(args.exp_macro) + + fig = plot_rq2(poly_df, baseline_df, vendor_df) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq34.py b/plots-mia-thesis/plot_rq31.py similarity index 93% rename from plots-mia-thesis/plot_rq34.py rename to plots-mia-thesis/plot_rq31.py index 581edf54..58c7961f 100644 --- a/plots-mia-thesis/plot_rq34.py +++ b/plots-mia-thesis/plot_rq31.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """ -RQ34 plot: table of Chebyshev polynomial degrees picked by the +RQ31 plot: table of Chebyshev polynomial degrees picked by the xdsl `lower-exp-to-polynomial` pass for every (precision, max_bits_lost) pair. Rows are precision formats (f16/f32/f64). Columns are values of the @@ -19,9 +19,9 @@ verbatim, so the numbers here are exactly what the pass picks at compile time. Usage: - python plot_rq34.py [--xmin -2.0] [--xmax 0.0] \\ + python plot_rq31.py [--xmin -2.0] [--xmax 0.0] \\ [--bits-lost -1 0 1 2 4 8 16] \\ - [-o plots-mia-thesis/output/rq34_plots.pdf] + [-o plots-mia-thesis/output/rq31_plots.pdf] """ import argparse @@ -69,7 +69,7 @@ def chosen_degree( return degree, capped -def plot_rq34( +def plot_rq31( xmin: float, xmax: float, bits_lost_values: list[int], ) -> plt.Figure: rows = PRECISIONS @@ -130,7 +130,7 @@ def plot_rq34( def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument( - "--output", "-o", default="plots-mia-thesis/output/rq34_plots.pdf", + "--output", "-o", default="plots-mia-thesis/output/rq31_plots.pdf", help="Output plot file", ) parser.add_argument( @@ -148,7 +148,7 @@ def main() -> None: args = parser.parse_args() Path(args.output).parent.mkdir(parents=True, exist_ok=True) - fig = plot_rq34(args.xmin, args.xmax, args.bits_lost) + fig = plot_rq31(args.xmin, args.xmax, args.bits_lost) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq32.py b/plots-mia-thesis/plot_rq32.py new file mode 100644 index 00000000..d48d9d80 --- /dev/null +++ b/plots-mia-thesis/plot_rq32.py @@ -0,0 +1,125 @@ +#!/usr/bin/env python3 +""" +RQ32 plot: accuracy vs performance Pareto, one panel per precision (f16/f32/f64). + + x = max_bits_lost (the accuracy bound passed to lower-exp-to-polynomial; + moving right = looser accuracy) + y = avg cycles / byte across input sizes N (lower = faster) + +The lower-left corner is "best" (more accurate AND faster). A reasonable +pipeline should produce a monotone-decreasing curve: relaxing the bound buys +performance. + +Source data is `kernels.exp_micro.csv`. The plot expects rows with +`impl = linalg_xdsl_b` where is the integer `max_bits_lost` (negative +allowed, e.g. `linalg_xdsl_b-1` for correctly-rounded). The Snakefile does +not yet emit these variants — once it does, the plot picks them up +automatically. Until then only the libm baseline reference line is drawn. + +Usage: + python plot_rq32.py [-i results/kernels.exp_micro.csv] \\ + [-o plots-mia-thesis/output/rq32_plots.pdf] +""" + +import argparse +import re +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd + +from plot_utils import ( + PRECISIONS, + annotate_kernel_df, + load_baseline_csv, + savefig, +) + + +# Inferred naming: `linalg_xdsl_b` where is the integer max_bits_lost +# the pass was invoked with (e.g. `linalg_xdsl_b-1`, `linalg_xdsl_b0`, +# `linalg_xdsl_b4`). Negative values are correctly-rounded; 0 is libm-grade; +# higher values relax the bound. +BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") + + +def load_bits_lost_csv(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"].str.match(BITS_LOST_VARIANT_RE)].copy() + df["max_bits_lost"] = df["impl"].str.extract(BITS_LOST_VARIANT_RE).astype(int) + return annotate_kernel_df(df) + + +def avg_per_bits_lost(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: + return ( + df[df["precision"] == precision] + .groupby("max_bits_lost")[metric] + .mean() + .sort_index() + ) + + +def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: + return df.loc[df["precision"] == precision, metric].mean() + + +def plot_rq32(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: + fig, axes = plt.subplots( + 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False + ) + + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[col_idx] + series = avg_per_bits_lost(poly_df, precision, "cycles_per_byte") + baseline = avg_baseline(baseline_df, precision, "cycles_per_byte") + + if not series.empty: + ax.plot( + series.index, series.values, + marker="o", linestyle="none", color="#33a02c", + label="Chebyshev polynomial", + ) + if not np.isnan(baseline): + ax.axhline( + baseline, color="#1f78b4", linestyle="--", + label=f"libm baseline ({baseline:.3g})", + ) + + ax.set_title(precision) + ax.set_xlabel(r"max_bits_lost (looser $\rightarrow$)") + ax.set_ylabel("avg cycles / byte") + if not series.empty: + ax.set_xticks(series.index) + ax.grid(True, alpha=0.3) + ax.legend(loc="best", fontsize=8) + + fig.suptitle("Accuracy vs performance Pareto for our polynomial approximation of exp(x)") + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--input", "-i", + default="results/kernels.exp_micro.csv", + help="Input CSV with exp_micro measurements", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/rq32_plots.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + poly_df = load_bits_lost_csv(args.input) + baseline_df = load_baseline_csv(args.input) + fig = plot_rq32(poly_df, baseline_df) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/plot_rq33.py b/plots-mia-thesis/plot_rq33.py deleted file mode 100644 index bc03365c..00000000 --- a/plots-mia-thesis/plot_rq33.py +++ /dev/null @@ -1,75 +0,0 @@ -#!/usr/bin/env python3 -""" -RQ33 plot: absolute approximation error |p_d(x) - exp(x)| on the interval -[CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER] for each Chebyshev degree d -in XDSL_LINALG_CHEBYSHEV_DEGREE_VARIANTS. - -The polynomial p_d is the degree-d Chebyshev-Lobatto interpolant of exp, -computed with the same DCT-I formula used by the Snakefile rule -xdsl_kernel_generate_source_chebyshev — so the curves here correspond exactly -to what the xDSL pipeline emits. - -Usage: - python plot_rq33.py [--output plots-mia-thesis/output/rq33_plots.pdf] -""" - -import argparse -from pathlib import Path - -import matplotlib.pyplot as plt -import numpy as np - -from plot_utils import ( - CHEBYSHEV_DEGREES, - CHEBYSHEV_DOMAIN_LOWER, - CHEBYSHEV_DOMAIN_UPPER, - DEGREE_COLORS, - DEGREE_LINESTYLES, - chebyshev_lobatto_coeffs, - eval_chebyshev, - savefig, -) - - -def plot_rq33() -> plt.Figure: - x = np.linspace(CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, 2001) - exp_x = np.exp(x) - - fig, ax = plt.subplots(figsize=(8, 5)) - for d in CHEBYSHEV_DEGREES: - approx = eval_chebyshev(chebyshev_lobatto_coeffs(d), x) - ax.plot( - x, np.abs(approx - exp_x), - color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], - label=f"d={d}", - ) - - ax.set_yscale("log") - ax.set_xlabel("x") - ax.set_ylabel(r"$|p_d(x) - \exp(x)|$") - ax.set_title( - f"Chebyshev-Lobatto approximation error on " - f"[{CHEBYSHEV_DOMAIN_LOWER}, {CHEBYSHEV_DOMAIN_UPPER}]" - ) - ax.grid(True, which="both", alpha=0.3) - ax.legend(ncol=2, fontsize=8, loc="best") - fig.tight_layout() - return fig - - -def main() -> None: - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument( - "--output", "-o", default="plots-mia-thesis/output/rq33_plots.pdf", - help="Output plot file", - ) - args = parser.parse_args() - - Path(args.output).parent.mkdir(parents=True, exist_ok=True) - fig = plot_rq33() - savefig(fig, args.output) - print(f"Saved plot to {args.output}") - - -if __name__ == "__main__": - main() diff --git a/plots-mia-thesis/plot_rq40.py b/plots-mia-thesis/plot_rq40.py index b5a1113b..a81bb639 100644 --- a/plots-mia-thesis/plot_rq40.py +++ b/plots-mia-thesis/plot_rq40.py @@ -24,7 +24,7 @@ eval_chebyshev_clenshaw_lowered (every coefficient rounded to DTYPE, every mul/add/sub rounded back to DTYPE). The degree d is the one the pass picks at - this (precision, max_bits_lost) — see plot_rq34's + this (precision, max_bits_lost) — see plot_rq31's chosen_degree. Per (precision, max_bits_lost) we draw `samples` input vectors of size @@ -59,7 +59,7 @@ import matplotlib.pyplot as plt import numpy as np -from plot_rq34 import chosen_degree +from plot_rq31 import chosen_degree from plot_utils import ( CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, diff --git a/plots-mia-thesis/plot_rq42.py b/plots-mia-thesis/plot_rq42.py index ef86d5e8..9dca4c79 100644 --- a/plots-mia-thesis/plot_rq42.py +++ b/plots-mia-thesis/plot_rq42.py @@ -1,14 +1,14 @@ #!/usr/bin/env python3 """ RQ42 plot: Does the kernel-level exp accuracy/perf trade-off translate to -the softmax operator? Mirrors rq2's layout so the two plots can be +the softmax operator? Mirrors rq32's layout so the two plots can be compared directly: same x-axis (`max_bits_lost`), same left y-axis (avg cycles/byte). Adds a twin right y-axis showing the end-to-end softmax output accuracy (avg bits lost in the softmax output across 100 sampled input vectors). Performance is loaded from `results/kernels.softmax_polynomial.csv` — same -processing as rq2. Accuracy is measured offline: +processing as rq32. Accuracy is measured offline: for each (precision, max_bits_lost): 1. recover the Chebyshev degree the pass picks (chosen_degree) 2. sample 100 input vectors of size DEFAULT_N from uniform(-1, 1) @@ -36,7 +36,7 @@ import numpy as np import pandas as pd -from plot_rq34 import chosen_degree +from plot_rq31 import chosen_degree from plot_utils import ( CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, @@ -57,7 +57,7 @@ DEFAULT_SAMPLES = 100 DEFAULT_SEED = 0 -PERF_COLOR = "#33a02c" # matches rq2 +PERF_COLOR = "#33a02c" # matches rq32 ACC_COLOR = "#e31a1c" @@ -166,7 +166,7 @@ def plot_rq42(agg: pd.DataFrame) -> plt.Figure: ax.grid(True, alpha=0.3) continue - # Left axis: avg cycles/byte (mirrors rq2). + # Left axis: avg cycles/byte (mirrors rq32). l_perf, = ax.plot( sub["max_bits_lost"], sub["cycles_per_byte_mean"], marker="o", linestyle="-", color=PERF_COLOR, diff --git a/plots-mia-thesis/plot_rq43.py b/plots-mia-thesis/plot_rq43.py index 7d3adbea..218cd4bb 100644 --- a/plots-mia-thesis/plot_rq43.py +++ b/plots-mia-thesis/plot_rq43.py @@ -2,7 +2,7 @@ """ RQ43 plot: per-precision performance of the softmax_polynomial kernel as a function of the `max_bits_lost` attribute attached to math.exp. Mirrors -plot_rq2's layout for the exp kernel — same x-axis (max_bits_lost), +plot_rq32's layout for the exp kernel — same x-axis (max_bits_lost), same y-axis (avg cycles / byte), one panel per precision (f16/f32/f64) — but draws softmax_polynomial measurements instead of exp_micro. @@ -40,8 +40,8 @@ BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") -POLY_COLOR = "#33a02c" # matches rq2 -BASELINE_COLOR = "#1f78b4" # matches rq2 +POLY_COLOR = "#33a02c" # matches rq32 +BASELINE_COLOR = "#1f78b4" # matches rq32 def load_bits_lost_csv(csv_path: str) -> pd.DataFrame: diff --git a/plots-mia-thesis/plot_rq44.py b/plots-mia-thesis/plot_rq44.py index dac36b25..65934ca9 100644 --- a/plots-mia-thesis/plot_rq44.py +++ b/plots-mia-thesis/plot_rq44.py @@ -42,7 +42,7 @@ import numpy as np import pandas as pd -from plot_rq34 import chosen_degree +from plot_rq31 import chosen_degree from plot_rq40 import ( F16_BITS_LOST_CAP, per_vector_mean_ulp_err, From 36bc2553e226d4e3570a1b659194cc7fbeef1aee Mon Sep 17 00:00:00 2001 From: root Date: Tue, 2 Jun 2026 03:43:30 +0000 Subject: [PATCH 29/33] a lot of renaming and rq4 plots --- Snakefile | 30 +- plots-mia-thesis/output/chebyshev_error.pdf | Bin 48113 -> 0 bytes plots-mia-thesis/output/exp_macro_plots.pdf | Bin 14102 -> 0 bytes plots-mia-thesis/output/exp_micro_plots.pdf | Bin 17312 -> 0 bytes plots-mia-thesis/output/rq40_plots.pdf | Bin 20924 -> 0 bytes plots-mia-thesis/output/rq41_plots.pdf | Bin 62903 -> 20898 bytes plots-mia-thesis/output/rq42_plots.pdf | Bin 24056 -> 25933 bytes plots-mia-thesis/output/rq43_plots.pdf | Bin 20412 -> 21125 bytes plots-mia-thesis/output/softmax_appendix.pdf | Bin 0 -> 45320 bytes plots-mia-thesis/plot_exp_macro.py | 151 ---------- plots-mia-thesis/plot_exp_micro.py | 149 ---------- plots-mia-thesis/plot_rq40.py | 256 ---------------- plots-mia-thesis/plot_rq41.py | 276 +++++++++++++----- plots-mia-thesis/plot_rq42.py | 274 ++++++----------- plots-mia-thesis/plot_rq43.py | 252 +++++++++++----- plots-mia-thesis/plot_rq44.py | 242 --------------- .../output/rq43_plots.pdf} | Bin 22167 -> 25902 bytes plots-mia-thesis/softmax_appendix.py | 147 ++++++++++ 18 files changed, 624 insertions(+), 1153 deletions(-) delete mode 100644 plots-mia-thesis/output/chebyshev_error.pdf delete mode 100644 plots-mia-thesis/output/exp_macro_plots.pdf delete mode 100644 plots-mia-thesis/output/exp_micro_plots.pdf delete mode 100644 plots-mia-thesis/output/rq40_plots.pdf create mode 100644 plots-mia-thesis/output/softmax_appendix.pdf delete mode 100644 plots-mia-thesis/plot_exp_macro.py delete mode 100644 plots-mia-thesis/plot_exp_micro.py delete mode 100644 plots-mia-thesis/plot_rq40.py delete mode 100644 plots-mia-thesis/plot_rq44.py rename plots-mia-thesis/{output/rq44_plots.pdf => plots-mia-thesis/output/rq43_plots.pdf} (52%) create mode 100644 plots-mia-thesis/softmax_appendix.py diff --git a/Snakefile b/Snakefile index 096672dd..65456f32 100644 --- a/Snakefile +++ b/Snakefile @@ -309,7 +309,7 @@ TESTSET_SOFTMAX_POLYNOMIAL = [ variant=XDSL_LINALG_MAX_BITS_LOST_VARIANTS, ), # libm reference (exp_kernel calls expf/exp directly) for the perf - # comparison in plot_rq43 / plot_rq44. + # comparison in plot_rq42 / plot_rq43. *expand( "softmax_polynomial/{N}xf{precision}/baseline", N=range(16, 129, 16), @@ -1065,12 +1065,12 @@ rule plot_rq32: shell: "python {input.script} -o {output}" -rule plot_rq41: +rule plot_softmax_appendix: input: - script = PLOTS_DIR + "/plot_rq41.py", + script = PLOTS_DIR + "/softmax_appendix.py", utils = PLOTS_DIR + "/plot_utils.py", output: - PLOTS_OUTPUT + "/rq41_plots.pdf", + PLOTS_OUTPUT + "/softmax_appendix.pdf", shell: "python {input.script} -o {output}" @@ -1078,7 +1078,6 @@ rule plot_rq42: input: script = PLOTS_DIR + "/plot_rq42.py", utils = PLOTS_DIR + "/plot_utils.py", - rq31 = PLOTS_DIR + "/plot_rq31.py", softmax = "results/kernels.softmax_polynomial.csv", output: PLOTS_OUTPUT + "/rq42_plots.pdf", @@ -1089,22 +1088,12 @@ rule plot_rq43: input: script = PLOTS_DIR + "/plot_rq43.py", utils = PLOTS_DIR + "/plot_utils.py", - softmax = "results/kernels.softmax_polynomial.csv", - output: - PLOTS_OUTPUT + "/rq43_plots.pdf", - shell: - "python {input.script} -i {input.softmax} -o {output}" - -rule plot_rq44: - input: - script = PLOTS_DIR + "/plot_rq44.py", - utils = PLOTS_DIR + "/plot_utils.py", rq31 = PLOTS_DIR + "/plot_rq31.py", - rq40 = PLOTS_DIR + "/plot_rq40.py", - rq43 = PLOTS_DIR + "/plot_rq43.py", + rq41 = PLOTS_DIR + "/plot_rq41.py", + rq42 = PLOTS_DIR + "/plot_rq42.py", softmax = "results/kernels.softmax_polynomial.csv", output: - PLOTS_OUTPUT + "/rq44_plots.pdf", + PLOTS_OUTPUT + "/rq43_plots.pdf", shell: "python {input.script} -i {input.softmax} -o {output}" @@ -1117,7 +1106,6 @@ rule plots_mia_thesis: PLOTS_OUTPUT + "/rq13_plots.pdf", PLOTS_OUTPUT + "/rq31_plots.pdf", PLOTS_OUTPUT + "/rq32_plots.pdf", - PLOTS_OUTPUT + "/rq41_plots.pdf", + PLOTS_OUTPUT + 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-#!/usr/bin/env python3 -""" -Plot exp kernel results from kernels.exp.csv. - -Usage: - python plot_exp.py [--input results/kernels.exp.csv] [--output output/exp_plots.pdf] -""" - -import argparse -from pathlib import Path -from typing import Sequence - -import numpy as np -import numpy.typing as npt -import pandas as pd -from matplotlib.axes import Axes - -from fpu import FPUGridPlotRow -from plot_utils import IMPL_COLORS, IMPL_MARKERS, GridPlotRow, plot_combined, savefig - - -PRECISION_BYTES = {"f16": 2, "f32": 4, "f64": 8} - - -def load_and_prepare(csv_path: str) -> pd.DataFrame: - df = pd.read_csv(csv_path) - - def get_total_elements(row): - parts = row["params"].split("x") - dims = [int(p) for p in parts[:-1]] - return int(np.prod(dims)) - - def get_precision(row): - parts = row["params"].split("x") - return parts[-1] - - df["total_elements"] = df.apply(get_total_elements, axis=1) - df["precision"] = df.apply(get_precision, axis=1) - df = df[df["test"] == "exp_macro"].copy() - df["test"] = "Exp" - - df["total_input_bytes"] = df.apply( - lambda row: row["total_elements"] * PRECISION_BYTES[row["precision"]], axis=1, - ) - df["cycles_per_byte"] = df["cycles"] / df["total_input_bytes"] - - df = df.sort_values("total_elements") - return df - - -def make_pivoted_dfs( - df: pd.DataFrame, metric: str, precisions: list[str], -) -> list[pd.DataFrame]: - """Create one pivoted DataFrame per precision, with impl as columns.""" - dfs = [] - for prec in precisions: - prec_df = df[df["precision"] == prec] - pivoted = prec_df.pivot_table( - index="total_elements", columns="impl", values=metric, - ) - pivoted.columns = [f"Exp_{c}" for c in pivoted.columns] - pivoted.index.name = f"Exp N ({prec})" - dfs.append(pivoted) - return dfs - -class ExpFPUPlotRow(FPUGridPlotRow): - @classmethod - def plot_grid_cell(cls, ax: Axes, df: pd.DataFrame, *, hide_xlabel: bool) -> None: - for col in df: - ax.plot( - df.index, df[col], - color=IMPL_COLORS[col], marker=IMPL_MARKERS[col], - linestyle="none", - ) - ax.set_xticks(df.index) - if not hide_xlabel: - ax.set_xlabel(df.index.name) - - -class ExpCyclesPerBytePlotRow(GridPlotRow): - ylabel = "Cycles / Byte" - - @classmethod - def yrange(cls, dfs: Sequence[pd.DataFrame]) -> npt.NDArray[np.float64]: - max_val = max(df.max().max() for df in dfs) - step = max(1, int(np.ceil(max_val / 8))) - magnitude = 10 ** int(np.log10(step)) - step = int(np.ceil(step / magnitude)) * magnitude - return np.arange(0, max_val + step + 1, step).astype(np.float64) - - @classmethod - def plot_grid_cell(cls, ax: Axes, df: pd.DataFrame, *, hide_xlabel: bool) -> None: - for col in df: - ax.plot( - df.index, df[col], - color=IMPL_COLORS[col], marker=IMPL_MARKERS[col], - linestyle="none", - ) - ax.set_xticks(df.index) - if not hide_xlabel: - ax.set_xlabel(df.index.name) - - -def get_exp_dfs(df: pd.DataFrame) -> tuple[list[pd.DataFrame], list[pd.DataFrame]]: - precisions = sorted(df["precision"].unique()) - - fpu_dfs = make_pivoted_dfs(df, "fpss_fpu_occupancy", precisions) - cycles_per_byte_dfs = make_pivoted_dfs(df, "cycles_per_byte", precisions) - - return fpu_dfs, cycles_per_byte_dfs - - -def plot_exp(fpu_dfs, cycles_per_byte_dfs): - ncols = len(fpu_dfs) - rows = [ - ExpFPUPlotRow(fpu_dfs, hide_xtick_labels=True), - ExpCyclesPerBytePlotRow(cycles_per_byte_dfs), - ] - return plot_combined( - rows, - legend_cols=3, - rcparams_cfg_file="config/gridplot.mplstyle", - figsize=(ncols * 6, len(rows) * 3.5), - ) - - -def main(): - parser = argparse.ArgumentParser(description="Plot exp kernel results") - parser.add_argument( - "--input", "-i", - default="results/kernels.exp_macro.csv", - help="Input CSV file", - ) - parser.add_argument( - "--output", "-o", - default="output/exp_plots.pdf", - help="Output plot file", - ) - args = parser.parse_args() - - Path(args.output).parent.mkdir(exist_ok=True) - - df = load_and_prepare(args.input) - fpu_dfs, cycles_per_byte_dfs = get_exp_dfs(df) - fig = plot_exp(fpu_dfs, cycles_per_byte_dfs) - savefig(fig, args.output) - print(f"Saved plot to {args.output}") - - -if __name__ == "__main__": - main() diff --git a/plots-mia-thesis/plot_exp_micro.py b/plots-mia-thesis/plot_exp_micro.py deleted file mode 100644 index d5e621de..00000000 --- a/plots-mia-thesis/plot_exp_micro.py +++ /dev/null @@ -1,149 +0,0 @@ -#!/usr/bin/env python3 -""" -Plot exp kernel results from kernels.exp.csv. - -Usage: - python plot_exp.py [--input results/kernels.exp.csv] [--output output/exp_plots.pdf] -""" - -import argparse -from pathlib import Path -from typing import Sequence - -import numpy as np -import numpy.typing as npt -import pandas as pd -from matplotlib.axes import Axes - -from fpu import FPUGridPlotRow -from plot_utils import IMPL_COLORS, IMPL_MARKERS, GridPlotRow, plot_combined, savefig - - -PRECISION_BYTES = {"f16": 2, "f32": 4, "f64": 8} - - -def load_and_prepare(csv_path: str) -> pd.DataFrame: - df = pd.read_csv(csv_path) - - def get_total_elements(row): - parts = row["params"].split("x") - dims = [int(p) for p in parts[:-1]] - return int(np.prod(dims)) - - def get_precision(row): - parts = row["params"].split("x") - return parts[-1] - - df["total_elements"] = df.apply(get_total_elements, axis=1) - df["precision"] = df.apply(get_precision, axis=1) - df = df[df["test"] == "exp_micro"].copy() - df["test"] = "Exp" - - df["total_input_bytes"] = df.apply( - lambda row: row["total_elements"] * PRECISION_BYTES[row["precision"]], axis=1, - ) - df["cycles_per_byte"] = df["cycles"] / df["total_input_bytes"] - - df = df.sort_values("total_elements") - return df - - -def make_pivoted_dfs( - df: pd.DataFrame, metric: str, precisions: list[str], -) -> list[pd.DataFrame]: - """Create one pivoted DataFrame per precision, with impl as columns.""" - dfs = [] - for prec in precisions: - prec_df = df[df["precision"] == prec] - pivoted = prec_df.pivot_table( - index="total_elements", columns="impl", values=metric, - ) - pivoted.columns = [f"Exp_{c}" for c in pivoted.columns] - pivoted.index.name = f"Exp N ({prec})" - dfs.append(pivoted) - return dfs - -class ExpFPUPlotRow(FPUGridPlotRow): - @classmethod - def plot_grid_cell(cls, ax: Axes, df: pd.DataFrame, *, hide_xlabel: bool) -> None: - for col in df: - ax.plot( - df.index, df[col], - color=IMPL_COLORS[col], marker=IMPL_MARKERS[col], - ) - ax.set_xticks(df.index) - if not hide_xlabel: - ax.set_xlabel(df.index.name) - - -class ExpCyclesPerBytePlotRow(GridPlotRow): - ylabel = "Cycles / Byte" - - @classmethod - def yrange(cls, dfs: Sequence[pd.DataFrame]) -> npt.NDArray[np.float64]: - max_val = max(df.max().max() for df in dfs) - step = max(1, int(np.ceil(max_val / 8))) - magnitude = 10 ** int(np.log10(step)) - step = int(np.ceil(step / magnitude)) * magnitude - return np.arange(0, max_val + step + 1, step).astype(np.float64) - - @classmethod - def plot_grid_cell(cls, ax: Axes, df: pd.DataFrame, *, hide_xlabel: bool) -> None: - for col in df: - ax.plot( - df.index, df[col], - color=IMPL_COLORS[col], marker=IMPL_MARKERS[col], - ) - ax.set_xticks(df.index) - if not hide_xlabel: - ax.set_xlabel(df.index.name) - - -def get_exp_dfs(df: pd.DataFrame) -> tuple[list[pd.DataFrame], list[pd.DataFrame]]: - precisions = sorted(df["precision"].unique()) - - fpu_dfs = make_pivoted_dfs(df, "fpss_fpu_occupancy", precisions) - cycles_per_byte_dfs = make_pivoted_dfs(df, "cycles_per_byte", precisions) - - return fpu_dfs, cycles_per_byte_dfs - - -def plot_exp(fpu_dfs, cycles_per_byte_dfs): - ncols = len(fpu_dfs) - rows = [ - ExpFPUPlotRow(fpu_dfs, hide_xtick_labels=True), - ExpCyclesPerBytePlotRow(cycles_per_byte_dfs), - ] - return plot_combined( - rows, - legend_cols=3, - rcparams_cfg_file="config/gridplot.mplstyle", - figsize=(ncols * 6, len(rows) * 3.5), - ) - - -def main(): - parser = argparse.ArgumentParser(description="Plot exp kernel results") - parser.add_argument( - "--input", "-i", - default="results/kernels.exp_micro.csv", - help="Input CSV file", - ) - parser.add_argument( - "--output", "-o", - default="output/exp_plots.pdf", - help="Output plot file", - ) - args = parser.parse_args() - - Path(args.output).parent.mkdir(exist_ok=True) - - df = load_and_prepare(args.input) - fpu_dfs, cycles_per_byte_dfs = get_exp_dfs(df) - fig = plot_exp(fpu_dfs, cycles_per_byte_dfs) - savefig(fig, args.output) - print(f"Saved plot to {args.output}") - - -if __name__ == "__main__": - main() diff --git a/plots-mia-thesis/plot_rq40.py b/plots-mia-thesis/plot_rq40.py deleted file mode 100644 index a81bb639..00000000 --- a/plots-mia-thesis/plot_rq40.py +++ /dev/null @@ -1,256 +0,0 @@ -#!/usr/bin/env python3 -""" -RQ40 plot: realised mantissa bits lost in the softmax *output* as a -function of the `max_bits_lost` attribute attached to math.exp, per -precision. - -For each precision (f16, f32, f64) and each value of max_bits_lost in -the range exposed by XDSL_LINALG_MAX_BITS_LOST_VARIANTS (-1 .. 16) we -reproduce the softmax_polynomial kernel arithmetic in software: - - m = max(x) (in DTYPE) - e_i = exp_target(x_i - m) (in DTYPE) - s = Sum_i e_i (sequential, DTYPE) - inv = 1 / s (DTYPE; for f16, via f32 like - softmax.c's __divsf3 fallback) - z_i = e_i * inv (DTYPE) - -Two runs differ only in `exp_target`: - reference: exp(x_i - m) computed in f64, rounded to DTYPE - (correctly-rounded libm exp at the target precision). - approximated: degree-d Chebyshev-Lobatto interpolant on [-2, 0] - evaluated *exactly as the xDSL passes lower it* — - same arithmetic as plot_rq13's - eval_chebyshev_clenshaw_lowered (every coefficient - rounded to DTYPE, every mul/add/sub rounded back to - DTYPE). The degree d is the one the pass picks at - this (precision, max_bits_lost) — see plot_rq31's - chosen_degree. - -Per (precision, max_bits_lost) we draw `samples` input vectors of size -`n` from uniform(-1, 1) (same distribution as -softmax_polynomial/gendata.py), compute - - ulp_err_i = |approx_i - ref_i| / ulp_DTYPE(ref_i) - -per output element, average across elements and across vectors, then -report - - bits_lost = log2(max(1, mean ulp_err)) - -so the floor of 0 bits corresponds to "within 1 ULP of the reference" -(matches plot_rq42's convention). - -f16 cap: XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 drops bN with N >= 11 -because f16 has 11 mantissa bits and the pass's Chebyshev fit becomes -degenerate (degree 0 -> ZeroDivisionError). We mirror that by skipping -those points on the f16 curve. - -Usage: - python plot_rq40.py [--n 64] [--samples 100] [--seed 0] \\ - [-o plots-mia-thesis/output/rq40_plots.pdf] -""" - -import argparse -import math as pymath -from functools import lru_cache -from pathlib import Path - -import matplotlib.pyplot as plt -import numpy as np - -from plot_rq31 import chosen_degree -from plot_utils import ( - CHEBYSHEV_DOMAIN_LOWER, - CHEBYSHEV_DOMAIN_UPPER, - PRECISION_MANTISSA_BITS, - PRECISION_NUMPY_DTYPE, - PRECISIONS, - chebyshev_lobatto_coeffs, - eval_chebyshev_clenshaw_lowered, - savefig, - ulp, -) - - -# Full XDSL_LINALG_MAX_BITS_LOST_VARIANTS range from the Snakefile. -BITS_LOST_VALUES: list[int] = list(range(-1, 17)) -# f16: snakefile's XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 keeps only N < 11. -F16_BITS_LOST_CAP = 11 - -DEFAULT_N = 64 -DEFAULT_SAMPLES = 100 -DEFAULT_SEED = 0 - -REF_COLOR = "#e31a1c" -IDEAL_COLOR = "#000000" -MANTISSA_LIMIT_COLOR = "#827b7b" - - -@lru_cache(maxsize=None) -def _cached_coeffs(degree: int) -> tuple[float, ...]: - return tuple(chebyshev_lobatto_coeffs(degree)) - - -def _seq_sum(e: np.ndarray, precision: str) -> np.ndarray: - """Sequential sum in DTYPE, matching softmax.c's `s += e[i];` loop.""" - dtype = PRECISION_NUMPY_DTYPE[precision] - s = dtype(0) - for v in e: - s = dtype(s + dtype(v)) - return s - - -def _reciprocal(s: np.ndarray, precision: str) -> np.ndarray: - """1/s as softmax.c does it: f32-emulated for f16 (__divsf3), DTYPE-native otherwise.""" - dtype = PRECISION_NUMPY_DTYPE[precision] - if precision == "f16": - return dtype(np.float32(1.0) / np.float32(s)) - return dtype(dtype(1.0) / s) - - -def _softmax_finish(e: np.ndarray, precision: str) -> np.ndarray: - """Steps 2b/3 of softmax.c: sum(e), 1/s, e *= inv_s.""" - dtype = PRECISION_NUMPY_DTYPE[precision] - s = _seq_sum(e, precision) - inv = _reciprocal(s, precision) - return (e * inv).astype(dtype) - - -def softmax_reference(x: np.ndarray, precision: str) -> np.ndarray: - """softmax.c arithmetic in DTYPE with exp replaced by correctly-rounded - libm exp at the target precision (computed in f64, rounded to DTYPE).""" - dtype = PRECISION_NUMPY_DTYPE[precision] - xd = x.astype(dtype) - m = xd.max() - xp = (xd - m).astype(dtype) - e = np.exp(xp.astype(np.float64)).astype(dtype) - return _softmax_finish(e, precision) - - -def softmax_approx(x: np.ndarray, degree: int, precision: str) -> np.ndarray: - """softmax.c arithmetic in DTYPE with exp replaced by the Chebyshev - approximation as the xDSL passes lower it (same lowered Clenshaw as - plot_rq13). The degree is the one the pass picks at this - (precision, max_bits_lost).""" - dtype = PRECISION_NUMPY_DTYPE[precision] - xd = x.astype(dtype) - m = xd.max() - xp = (xd - m).astype(dtype) - coeffs = list(_cached_coeffs(degree)) - e = eval_chebyshev_clenshaw_lowered(coeffs, xp, precision) - return _softmax_finish(e, precision) - - -def per_vector_mean_ulp_err( - x: np.ndarray, degree: int, precision: str, -) -> float: - """Average over output elements of |approx_i - ref_i| / ulp(ref_i).""" - approx = softmax_approx(x, degree, precision).astype(np.float64) - ref = softmax_reference(x, precision).astype(np.float64) - ulps = ulp(ref, precision) - diff = np.abs(approx - ref) - with np.errstate(divide="ignore", invalid="ignore"): - ulp_err = diff / ulps - ulp_err = np.where(np.isfinite(ulp_err), ulp_err, 0.0) - return float(ulp_err.mean()) - - -def measure_bits_lost( - precision: str, bits_lost: int, n: int, samples: int, seed: int, -) -> float | None: - if precision == "f16" and bits_lost >= F16_BITS_LOST_CAP: - return None - mantissa = PRECISION_MANTISSA_BITS[precision] - degree, _ = chosen_degree( - bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa, - ) - rng = np.random.default_rng(np.uint64(seed) ^ np.uint64(bits_lost & 0xFFFF)) - errs = [ - per_vector_mean_ulp_err(rng.uniform(-1.0, 1.0, n), degree, precision) - for _ in range(samples) - ] - return pymath.log2(max(1.0, float(np.mean(errs)))) - - -def plot_rq40(n: int, samples: int, seed: int) -> plt.Figure: - fig, axes = plt.subplots( - 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 5.0, 4.5), - ) - for col, precision in enumerate(PRECISIONS): - ax = axes[col] - mantissa = PRECISION_MANTISSA_BITS[precision] - - xs: list[int] = [] - ys: list[float] = [] - for b in BITS_LOST_VALUES: - v = measure_bits_lost(precision, b, n, samples, seed) - if v is None: - continue - xs.append(b) - ys.append(v) - - ax.plot( - xs, ys, - marker="o", linestyle="-", color=REF_COLOR, - label="measured softmax error", - ) - ideal_y = np.maximum(np.array(xs, dtype=float), 0.0) - ax.plot( - xs, ideal_y, - color=IDEAL_COLOR, linestyle=":", linewidth=1.0, - label="User-specified bound (max_bits_lost)", - ) - ax.axhline( - mantissa, - color=MANTISSA_LIMIT_COLOR, linestyle="--", linewidth=0.8, - label="all mantissa bits lost", - ) - - ax.set_xticks(BITS_LOST_VALUES) - ax.set_xlim(BITS_LOST_VALUES[0] - 0.5, BITS_LOST_VALUES[-1] + 0.5) - ax.set_ylim(-1, mantissa + 4) - ax.set_xlabel( - r"User-specified exp accuracy bound (max bits lost, looser $\rightarrow$)" - ) - ax.set_title(precision) - ax.grid(True, alpha=0.3) - if col == 0: - ax.set_ylabel( - r"measured bits lost $=\log_2(\max(1,\,\overline{\mathrm{ULP\ error}}))$" - ) - ax.legend(loc="best", fontsize=7) - - fig.tight_layout() - return fig - - -def main() -> None: - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument( - "--n", type=int, default=DEFAULT_N, - help="Size of each sample input vector", - ) - parser.add_argument( - "--samples", type=int, default=DEFAULT_SAMPLES, - help="Number of sample input vectors per (precision, max_bits_lost)", - ) - parser.add_argument( - "--seed", type=int, default=DEFAULT_SEED, - help="Base seed for input-vector sampling", - ) - parser.add_argument( - "--output", "-o", - default="plots-mia-thesis/output/rq40_plots.pdf", - help="Output plot file", - ) - args = parser.parse_args() - - Path(args.output).parent.mkdir(parents=True, exist_ok=True) - fig = plot_rq40(args.n, args.samples, args.seed) - savefig(fig, args.output) - print(f"Saved plot to {args.output}") - - -if __name__ == "__main__": - main() diff --git a/plots-mia-thesis/plot_rq41.py b/plots-mia-thesis/plot_rq41.py index 4ca7441e..0985b04e 100644 --- a/plots-mia-thesis/plot_rq41.py +++ b/plots-mia-thesis/plot_rq41.py @@ -1,111 +1,225 @@ #!/usr/bin/env python3 """ -RQ41 plot: per-element comparison of correctly-rounded exp(x_i) against the -degree-d Chebyshev-Lobatto approximation, for d = 2..12 and three input -vectors per precision (f16, f32, f64). - -Inputs are generated the way the softmax_polynomial kernel sees them: - x ~ uniform(-1, 1, N) (mirrors softmax_polynomial/gendata.py) - x' = x - max(x) (the max-shift the kernel performs before exp) -so every x'_i lies in [CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER] = -[-2, 0] — the domain on which the pass fits exp. The Chebyshev coefficients -are computed with the same DCT-I formula used by xdsl_kernel_generate_source_chebyshev -in the Snakefile, so the curves here correspond exactly to what the xDSL -pipeline emits. - -Three different random seeds give three different input vectors per precision. -Each panel: - x-axis = element index i - y-axis = exp(x'_i) -with a "true" curve (correctly-rounded exp in the target precision) and one -curve per degree d in [CHEBYSHEV_DEGREES][2..12]. +RQ41 plot: realised mantissa bits lost in the softmax *output* as a +function of the `max_bits_lost` attribute attached to math.exp, per +precision. + +For each precision (f16, f32, f64) and each value of max_bits_lost in +the range exposed by XDSL_LINALG_MAX_BITS_LOST_VARIANTS (-1 .. 16) we +reproduce the softmax_polynomial kernel arithmetic in software: + + m = max(x) (in DTYPE) + e_i = exp_target(x_i - m) (in DTYPE) + s = Sum_i e_i (sequential, DTYPE) + inv = 1 / s (DTYPE; for f16, via f32 like + softmax.c's __divsf3 fallback) + z_i = e_i * inv (DTYPE) + +Two runs differ only in `exp_target`: + reference: exp(x_i - m) computed in f64, rounded to DTYPE + (correctly-rounded libm exp at the target precision). + approximated: degree-d Chebyshev-Lobatto interpolant on [-2, 0] + evaluated *exactly as the xDSL passes lower it* — + same arithmetic as plot_rq13's + eval_chebyshev_clenshaw_lowered (every coefficient + rounded to DTYPE, every mul/add/sub rounded back to + DTYPE). The degree d is the one the pass picks at + this (precision, max_bits_lost) — see plot_rq31's + chosen_degree. + +Per (precision, max_bits_lost) we draw `samples` input vectors of size +`n` from uniform(-1, 1) (same distribution as +softmax_polynomial/gendata.py), compute + + ulp_err_i = |approx_i - ref_i| / ulp_DTYPE(ref_i) + +per output element, average across elements and across vectors, then +report + + bits_lost = log2(max(1, mean ulp_err)) + +so the floor of 0 bits corresponds to "within 1 ULP of the reference". + +f16 cap: XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 drops bN with N >= 11 +because f16 has 11 mantissa bits and the pass's Chebyshev fit becomes +degenerate (degree 0 -> ZeroDivisionError). We mirror that by skipping +those points on the f16 curve. Usage: - python plot_rq41.py [--n 16] [--seeds 0 1 2] \\ + python plot_rq41.py [--n 64] [--samples 100] [--seed 0] \\ [-o plots-mia-thesis/output/rq41_plots.pdf] """ import argparse +import math as pymath +from functools import lru_cache from pathlib import Path import matplotlib.pyplot as plt import numpy as np +from plot_rq31 import chosen_degree from plot_utils import ( - CHEBYSHEV_DEGREES, - DEGREE_COLORS, - DEGREE_LINESTYLES, + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + PRECISION_MANTISSA_BITS, PRECISION_NUMPY_DTYPE, PRECISIONS, chebyshev_lobatto_coeffs, - eval_chebyshev, + eval_chebyshev_clenshaw_lowered, savefig, + ulp, ) -DEFAULT_N = 16 -DEFAULT_SEEDS = [0, 1, 2] +# Full XDSL_LINALG_MAX_BITS_LOST_VARIANTS range from the Snakefile. +BITS_LOST_VALUES: list[int] = list(range(-1, 17)) +# f16: snakefile's XDSL_LINALG_MAX_BITS_LOST_VARIANTS_F16 keeps only N < 11. +F16_BITS_LOST_CAP = 11 +DEFAULT_N = 64 +DEFAULT_SAMPLES = 100 +DEFAULT_SEED = 0 -def softmax_xprime(seed: int, n: int, precision: str) -> np.ndarray: - """Reproduce the per-element input that softmax_polynomial feeds to - exp_kernel: gendata's uniform(-1, 1, N) sequence cast to `precision`, - then x - max(x). Uses the legacy global RNG to match gendata.py.""" +REF_COLOR = "#e31a1c" +IDEAL_COLOR = "#000000" +MANTISSA_LIMIT_COLOR = "#827b7b" + + +@lru_cache(maxsize=None) +def _cached_coeffs(degree: int) -> tuple[float, ...]: + return tuple(chebyshev_lobatto_coeffs(degree)) + + +def _seq_sum(e: np.ndarray, precision: str) -> np.ndarray: + """Sequential sum in DTYPE, matching softmax.c's `s += e[i];` loop.""" dtype = PRECISION_NUMPY_DTYPE[precision] - np.random.seed(seed) - x = np.random.uniform(-1.0, 1.0, n).astype(dtype) - return (x - x.max()).astype(dtype) + s = dtype(0) + for v in e: + s = dtype(s + dtype(v)) + return s -def chebyshev_approx(x_prime: np.ndarray, degree: int, precision: str) -> np.ndarray: - """Degree-d Chebyshev-Lobatto interpolant of exp on [-2, 0], evaluated in - float64 then rounded to `precision` to match the dtype of the kernel.""" +def _reciprocal(s: np.ndarray, precision: str) -> np.ndarray: + """1/s as softmax.c does it: f32-emulated for f16 (__divsf3), DTYPE-native otherwise.""" dtype = PRECISION_NUMPY_DTYPE[precision] - approx = eval_chebyshev(chebyshev_lobatto_coeffs(degree), x_prime.astype(np.float64)) - return approx.astype(dtype) + if precision == "f16": + return dtype(np.float32(1.0) / np.float32(s)) + return dtype(dtype(1.0) / s) -def plot_rq41(n: int, seeds: list[int]) -> plt.Figure: - fig, axes = plt.subplots( - len(PRECISIONS), len(seeds), - figsize=(len(seeds) * 4.0, len(PRECISIONS) * 3.0), - sharex=True, +def _softmax_finish(e: np.ndarray, precision: str) -> np.ndarray: + """Steps 2b/3 of softmax.c: sum(e), 1/s, e *= inv_s.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + s = _seq_sum(e, precision) + inv = _reciprocal(s, precision) + return (e * inv).astype(dtype) + + +def softmax_reference(x: np.ndarray, precision: str) -> np.ndarray: + """softmax.c arithmetic in DTYPE with exp replaced by correctly-rounded + libm exp at the target precision (computed in f64, rounded to DTYPE).""" + dtype = PRECISION_NUMPY_DTYPE[precision] + xd = x.astype(dtype) + m = xd.max() + xp = (xd - m).astype(dtype) + e = np.exp(xp.astype(np.float64)).astype(dtype) + return _softmax_finish(e, precision) + + +def softmax_approx(x: np.ndarray, degree: int, precision: str) -> np.ndarray: + """softmax.c arithmetic in DTYPE with exp replaced by the Chebyshev + approximation as the xDSL passes lower it (same lowered Clenshaw as + plot_rq13). The degree is the one the pass picks at this + (precision, max_bits_lost).""" + dtype = PRECISION_NUMPY_DTYPE[precision] + xd = x.astype(dtype) + m = xd.max() + xp = (xd - m).astype(dtype) + coeffs = list(_cached_coeffs(degree)) + e = eval_chebyshev_clenshaw_lowered(coeffs, xp, precision) + return _softmax_finish(e, precision) + + +def per_vector_mean_ulp_err( + x: np.ndarray, degree: int, precision: str, +) -> float: + """Average over output elements of |approx_i - ref_i| / ulp(ref_i).""" + approx = softmax_approx(x, degree, precision).astype(np.float64) + ref = softmax_reference(x, precision).astype(np.float64) + ulps = ulp(ref, precision) + diff = np.abs(approx - ref) + with np.errstate(divide="ignore", invalid="ignore"): + ulp_err = diff / ulps + ulp_err = np.where(np.isfinite(ulp_err), ulp_err, 0.0) + return float(ulp_err.mean()) + + +def measure_bits_lost( + precision: str, bits_lost: int, n: int, samples: int, seed: int, +) -> float | None: + if precision == "f16" and bits_lost >= F16_BITS_LOST_CAP: + return None + mantissa = PRECISION_MANTISSA_BITS[precision] + degree, _ = chosen_degree( + bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa, ) + rng = np.random.default_rng(np.uint64(seed) ^ np.uint64(bits_lost & 0xFFFF)) + errs = [ + per_vector_mean_ulp_err(rng.uniform(-1.0, 1.0, n), degree, precision) + for _ in range(samples) + ] + return pymath.log2(max(1.0, float(np.mean(errs)))) - for row, precision in enumerate(PRECISIONS): - dtype = PRECISION_NUMPY_DTYPE[precision] - for col, seed in enumerate(seeds): - ax = axes[row][col] - x_prime = softmax_xprime(seed, n, precision) - idx = np.arange(n) - - exp_true = np.exp(x_prime.astype(np.float64)).astype(dtype) - ax.plot( - idx, exp_true, - color="black", marker="o", linestyle="-", linewidth=1.4, - label="exp(x) (correctly rounded)" if (row == 0 and col == 0) else None, - ) - for d in CHEBYSHEV_DEGREES: - approx = chebyshev_approx(x_prime, d, precision) - ax.plot( - idx, approx, - color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], - marker="x", markersize=4, linewidth=0.8, - label=f"d={d}" if (row == 0 and col == 0) else None, - ) - - if col == 0: - ax.set_ylabel(f"{precision}\nexp(x'_i)") - if row == len(PRECISIONS) - 1: - ax.set_xlabel("element index i") - ax.set_title(f"seed={seed}, N={n}") - ax.grid(True, alpha=0.3) - - axes[0][0].legend(ncol=2, fontsize=7, loc="upper left", bbox_to_anchor=(0.0, -0.0)) - fig.suptitle( - "Softmax exp inputs: correctly-rounded vs degree-d Chebyshev approximation" +def plot_rq41(n: int, samples: int, seed: int) -> plt.Figure: + fig, axes = plt.subplots( + 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 5.0, 4.5), ) + for col, precision in enumerate(PRECISIONS): + ax = axes[col] + mantissa = PRECISION_MANTISSA_BITS[precision] + + xs: list[int] = [] + ys: list[float] = [] + for b in BITS_LOST_VALUES: + v = measure_bits_lost(precision, b, n, samples, seed) + if v is None: + continue + xs.append(b) + ys.append(v) + + ax.plot( + xs, ys, + marker="o", linestyle="-", color=REF_COLOR, + label="measured softmax error", + ) + ideal_y = np.maximum(np.array(xs, dtype=float), 0.0) + ax.plot( + xs, ideal_y, + color=IDEAL_COLOR, linestyle=":", linewidth=1.0, + label="User-specified bound (max_bits_lost)", + ) + ax.axhline( + mantissa, + color=MANTISSA_LIMIT_COLOR, linestyle="--", linewidth=0.8, + label="all mantissa bits lost", + ) + + ax.set_xticks(BITS_LOST_VALUES) + ax.set_xlim(BITS_LOST_VALUES[0] - 0.5, BITS_LOST_VALUES[-1] + 0.5) + ax.set_ylim(-1, mantissa + 4) + ax.set_xlabel( + r"User-specified exp accuracy bound (max bits lost, looser $\rightarrow$)" + ) + ax.set_title(precision) + ax.grid(True, alpha=0.3) + if col == 0: + ax.set_ylabel( + r"measured bits lost $=\log_2(\max(1,\,\overline{\mathrm{ULP\ error}}))$" + ) + ax.legend(loc="best", fontsize=7) + fig.tight_layout() return fig @@ -114,11 +228,15 @@ def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument( "--n", type=int, default=DEFAULT_N, - help="Number of elements per input vector", + help="Size of each sample input vector", + ) + parser.add_argument( + "--samples", type=int, default=DEFAULT_SAMPLES, + help="Number of sample input vectors per (precision, max_bits_lost)", ) parser.add_argument( - "--seeds", type=int, nargs="+", default=DEFAULT_SEEDS, - help="Random seeds for the three input vectors", + "--seed", type=int, default=DEFAULT_SEED, + help="Base seed for input-vector sampling", ) parser.add_argument( "--output", "-o", @@ -128,7 +246,7 @@ def main() -> None: args = parser.parse_args() Path(args.output).parent.mkdir(parents=True, exist_ok=True) - fig = plot_rq41(args.n, args.seeds) + fig = plot_rq41(args.n, args.samples, args.seed) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq42.py b/plots-mia-thesis/plot_rq42.py index 9dca4c79..1162eaba 100644 --- a/plots-mia-thesis/plot_rq42.py +++ b/plots-mia-thesis/plot_rq42.py @@ -1,208 +1,124 @@ #!/usr/bin/env python3 """ -RQ42 plot: Does the kernel-level exp accuracy/perf trade-off translate to -the softmax operator? Mirrors rq32's layout so the two plots can be -compared directly: same x-axis (`max_bits_lost`), same left y-axis -(avg cycles/byte). Adds a twin right y-axis showing the end-to-end softmax -output accuracy (avg bits lost in the softmax output across 100 sampled -input vectors). - -Performance is loaded from `results/kernels.softmax_polynomial.csv` — same -processing as rq32. Accuracy is measured offline: - for each (precision, max_bits_lost): - 1. recover the Chebyshev degree the pass picks (chosen_degree) - 2. sample 100 input vectors of size DEFAULT_N from uniform(-1, 1) - 3. run the softmax kernel in target precision: max-shift, - Chebyshev approx of exp on [-2, 0], sum, normalize - 4. reference = softmax in float64, rounded to target precision - 5. per output element i: bits_lost_i = log2(max(1, ULP error_i)) - 6. average over output elements per vector, then over the 100 vectors. - -Caveat: the float64 reference is itself ~1 ULP off correctly-rounded for -f64; the bottom of the f64 accuracy curve conflates polynomial error with -libm's residual roundoff (same caveat as plot_rq12). +RQ42 plot: per-precision performance of the softmax_polynomial kernel as a +function of the `max_bits_lost` attribute attached to math.exp. Mirrors +plot_rq2's layout for the exp kernel — same x-axis (max_bits_lost), +one column per precision (f16/f32/f64), one row per metric: + - row 1: avg cycles / byte (lower = faster) + - row 2: avg FPU utilization (column `fpss_fpu_occupancy` in the CSV) + +Data source: `results/kernels.softmax_polynomial.csv`. The plot picks up +every row with `impl = linalg_xdsl_b` (the Snakefile's +XDSL_LINALG_MAX_BITS_LOST_VARIANTS), groups by precision and +max_bits_lost, and averages each metric across the input sizes that were +benchmarked. The `baseline` rows (libm exp_kernel — added by the +baseline.c.template in kernels/softmax_polynomial) are drawn as a +horizontal reference line per panel. + +If the CSV does not yet contain baseline rows (the variants are +registered in the Snakefile but the run hasn't been triggered yet) the +baseline line is omitted and only the polynomial curve is drawn. Usage: python plot_rq42.py [-i results/kernels.softmax_polynomial.csv] \\ - [--n 64] [--samples 100] [-o plots-mia-thesis/output/rq42_plots.pdf] + [-o plots-mia-thesis/output/rq42_plots.pdf] """ import argparse import re -from functools import lru_cache from pathlib import Path import matplotlib.pyplot as plt import numpy as np import pandas as pd -from plot_rq31 import chosen_degree from plot_utils import ( - CHEBYSHEV_DOMAIN_LOWER, - CHEBYSHEV_DOMAIN_UPPER, - PRECISION_MANTISSA_BITS, - PRECISION_NUMPY_DTYPE, PRECISIONS, annotate_kernel_df, - chebyshev_lobatto_coeffs, - eval_chebyshev, savefig, - ulp, ) BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") -DEFAULT_N = 64 -DEFAULT_SAMPLES = 100 -DEFAULT_SEED = 0 +POLY_COLOR = "#33a02c" # matches rq32 +BASELINE_COLOR = "#1f78b4" # matches rq32 -PERF_COLOR = "#33a02c" # matches rq32 -ACC_COLOR = "#e31a1c" - -@lru_cache(maxsize=None) -def _cached_coeffs(degree: int) -> tuple[float, ...]: - return tuple(chebyshev_lobatto_coeffs(degree)) - - -def load_softmax_csv(csv_path: str) -> pd.DataFrame: +def load_bits_lost_csv(csv_path: str) -> pd.DataFrame: df = pd.read_csv(csv_path) df = df[df["impl"].str.match(BITS_LOST_VARIANT_RE)].copy() df["max_bits_lost"] = df["impl"].str.extract(BITS_LOST_VARIANT_RE).astype(int) return annotate_kernel_df(df) -def softmax_approx(x: np.ndarray, degree: int, precision: str) -> np.ndarray: - """Reproduce softmax_polynomial kernel arithmetic in `precision`: - m = max(x) (in dtype) - e = approx_d(x - m) (Chebyshev eval, in dtype) - s = sum(e) (in dtype) - z = e / s (in dtype) - Polynomial eval is done in float64 and cast to dtype — same approach - plot_rq12 uses; the kernel's Clenshaw eval in DTYPE differs slightly but - not enough to matter for the translation question.""" - dtype = PRECISION_NUMPY_DTYPE[precision] - x = x.astype(dtype) - m = x.max() - xp = (x - m).astype(dtype) - coeffs = list(_cached_coeffs(degree)) - e = eval_chebyshev(coeffs, xp.astype(np.float64)).astype(dtype) - s = dtype(e.sum()) - return (e / s).astype(dtype) - - -def softmax_reference_f64(x: np.ndarray) -> np.ndarray: - """Reference softmax computed entirely in float64.""" - x64 = x.astype(np.float64) - m = x64.max() - e = np.exp(x64 - m) - return e / e.sum() - - -def per_vector_bits_lost(x: np.ndarray, degree: int, precision: str) -> float: - """Average over output elements of bits_lost_i = log2(max(1, ULP_err_i)).""" - dtype = PRECISION_NUMPY_DTYPE[precision] - approx = softmax_approx(x, degree, precision) - ref_f64 = softmax_reference_f64(x) - ref_rn = ref_f64.astype(dtype) - ulps = ulp(ref_f64, precision) # ULP at the true value, in target precision - diff = np.abs(approx.astype(np.float64) - ref_rn.astype(np.float64)) - with np.errstate(divide="ignore", invalid="ignore"): - ulp_err = diff / ulps - ulp_err = np.where(np.isfinite(ulp_err), ulp_err, 0.0) - bits = np.log2(np.maximum(1.0, ulp_err)) - return float(bits.mean()) - - -def measure_accuracy( - precision: str, bits_lost: int, n: int, samples: int, seed: int, -) -> float: - mantissa = PRECISION_MANTISSA_BITS[precision] - degree, _ = chosen_degree( - bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa +def load_baseline_csv(csv_path: str) -> pd.DataFrame: + df = pd.read_csv(csv_path) + df = df[df["impl"] == "baseline"].copy() + if df.empty: + return df + return annotate_kernel_df(df) + + +def avg_per_bits_lost(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: + return ( + df[df["precision"] == precision] + .groupby("max_bits_lost")[metric] + .mean() + .sort_index() ) - rng = np.random.default_rng(np.uint64(seed) ^ np.uint64(bits_lost & 0xFFFF)) - vecs = [rng.uniform(-1.0, 1.0, n) for _ in range(samples)] - return float(np.mean([per_vector_bits_lost(x, degree, precision) for x in vecs])) - - -def aggregate( - df: pd.DataFrame, n: int, samples: int, seed: int, -) -> pd.DataFrame: - """One row per (precision, max_bits_lost): - - cycles_per_byte_mean = avg over the N values benchmarked - - softmax_output_bits_lost = avg over `samples` input vectors of size n - """ - rows = [] - for (precision, bits_lost), group in df.groupby(["precision", "max_bits_lost"]): - mantissa = PRECISION_MANTISSA_BITS[precision] - degree, capped = chosen_degree( - bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa - ) - bits = measure_accuracy( - precision, int(bits_lost), n=n, samples=samples, seed=seed, - ) - rows.append({ - "precision": precision, - "max_bits_lost": int(bits_lost), - "degree": degree, - "capped": capped, - "cycles_per_byte_mean": group["cycles_per_byte"].mean(), - "softmax_output_bits_lost": bits, - }) - return pd.DataFrame(rows).sort_values(["precision", "max_bits_lost"]) - - -def plot_rq42(agg: pd.DataFrame) -> plt.Figure: + + +def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: + if df.empty or "precision" not in df.columns or metric not in df.columns: + return float("nan") + sub = df.loc[df["precision"] == precision, metric] + return float("nan") if sub.empty else float(sub.mean()) + + +METRICS: list[tuple[str, str]] = [ + ("cycles_per_byte", "avg cycles / byte"), + ("fpss_fpu_occupancy", "avg FPU utilization"), +] + + +def plot_rq42(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: fig, axes = plt.subplots( - 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 5.0, 4.5), sharey=False, + len(METRICS), len(PRECISIONS), + figsize=(len(PRECISIONS) * 4.5, len(METRICS) * 4.0), + sharey=False, ) - for i, precision in enumerate(PRECISIONS): - ax = axes[i] - sub = agg[agg["precision"] == precision].sort_values("max_bits_lost") - if sub.empty: - ax.set_title(f"{precision} (no data)") + + for row_idx, (metric, ylabel) in enumerate(METRICS): + for col_idx, precision in enumerate(PRECISIONS): + ax = axes[row_idx, col_idx] + series = avg_per_bits_lost(poly_df, precision, metric) + baseline = avg_baseline(baseline_df, precision, metric) + + if not series.empty: + ax.plot( + series.index, series.values, + marker="o", linestyle="-", color=POLY_COLOR, + label="Chebyshev polynomial (softmax)", + ) + if not np.isnan(baseline): + ax.axhline( + baseline, color=BASELINE_COLOR, linestyle="--", + label=f"libm baseline ({baseline:.3g})", + ) + + ax.set_title(precision) + if row_idx == len(METRICS) - 1: + ax.set_xlabel( + r"User-specified exp accuracy bound (max bits lost, looser $\rightarrow$)" + ) + if col_idx == 0: + ax.set_ylabel(ylabel) + if not series.empty: + ax.set_xticks(series.index) ax.grid(True, alpha=0.3) - continue - - # Left axis: avg cycles/byte (mirrors rq32). - l_perf, = ax.plot( - sub["max_bits_lost"], sub["cycles_per_byte_mean"], - marker="o", linestyle="-", color=PERF_COLOR, - label="avg cycles / byte (softmax)", - ) - - # Right axis: softmax output bits lost. - ax2 = ax.twinx() - l_acc, = ax2.plot( - sub["max_bits_lost"], sub["softmax_output_bits_lost"], - marker="s", linestyle="--", color=ACC_COLOR, - label="avg bits lost in softmax output", - ) - - # Reference y = x line: "exp bound translates 1:1 to softmax output". - xs = sub["max_bits_lost"].to_numpy() - l_ref, = ax2.plot( - xs, np.maximum(xs, 0.0), - color="black", linestyle=":", linewidth=1.0, - label="ideal: output bits lost = max_bits_lost", - ) - - ax.set_xticks(xs) - ax.set_xlabel(r"max_bits_lost (looser $\rightarrow$)") - ax.set_ylabel("avg cycles / byte", color=PERF_COLOR) - ax2.set_ylabel("softmax output bits lost", color=ACC_COLOR) - ax.tick_params(axis="y", labelcolor=PERF_COLOR) - ax2.tick_params(axis="y", labelcolor=ACC_COLOR) - ax.set_title(precision) - ax.grid(True, alpha=0.3) - if i == 0: - ax.legend(handles=[l_perf, l_acc, l_ref], loc="best", fontsize=7) - - fig.suptitle( - "RQ4: Softmax operator — does the kernel-level exp trade-off translate?" - ) + ax.legend(loc="best", fontsize=8) + fig.tight_layout() return fig @@ -212,19 +128,7 @@ def main() -> None: parser.add_argument( "--input", "-i", default="results/kernels.softmax_polynomial.csv", - help="softmax_polynomial measurement CSV", - ) - parser.add_argument( - "--n", type=int, default=DEFAULT_N, - help="Size of each sample input vector for the accuracy measurement", - ) - parser.add_argument( - "--samples", type=int, default=DEFAULT_SAMPLES, - help="Number of sample input vectors per variant", - ) - parser.add_argument( - "--seed", type=int, default=DEFAULT_SEED, - help="Base seed for input-vector sampling", + help="Input CSV with softmax_polynomial measurements", ) parser.add_argument( "--output", "-o", @@ -234,9 +138,9 @@ def main() -> None: args = parser.parse_args() Path(args.output).parent.mkdir(parents=True, exist_ok=True) - df = load_softmax_csv(args.input) - agg = aggregate(df, n=args.n, samples=args.samples, seed=args.seed) - fig = plot_rq42(agg) + poly_df = load_bits_lost_csv(args.input) + baseline_df = load_baseline_csv(args.input) + fig = plot_rq42(poly_df, baseline_df) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq43.py b/plots-mia-thesis/plot_rq43.py index 218cd4bb..f31fa1b1 100644 --- a/plots-mia-thesis/plot_rq43.py +++ b/plots-mia-thesis/plot_rq43.py @@ -1,111 +1,210 @@ #!/usr/bin/env python3 """ -RQ43 plot: per-precision performance of the softmax_polynomial kernel as a -function of the `max_bits_lost` attribute attached to math.exp. Mirrors -plot_rq32's layout for the exp kernel — same x-axis (max_bits_lost), -same y-axis (avg cycles / byte), one panel per precision (f16/f32/f64) — -but draws softmax_polynomial measurements instead of exp_micro. - -Data source: `results/kernels.softmax_polynomial.csv`. The plot picks up -every row with `impl = linalg_xdsl_b` (the Snakefile's -XDSL_LINALG_MAX_BITS_LOST_VARIANTS), groups by precision and -max_bits_lost, and averages cycles/byte across the input sizes that were -benchmarked. The `baseline` rows (libm exp_kernel — added by the -baseline.c.template in kernels/softmax_polynomial) are drawn as a -horizontal reference line per panel. - -If the CSV does not yet contain baseline rows (the variants are -registered in the Snakefile but the run hasn't been triggered yet) the -baseline line is omitted and only the polynomial curve is drawn. +RQ43 plot: accuracy vs performance Pareto scatter for the +softmax_polynomial kernel, one panel per precision (f16/f32/f64). + + x = measured average bits lost in the softmax output + (log2 of the average ULP error, i.e. log2(max(1, ULP error)) — + the ULP error itself is computed exactly as in plot_rq41: softmax.c + arithmetic in DTYPE with exp replaced by the lowered Clenshaw + Chebyshev approximation, compared against the same kernel with + correctly-rounded libm exp, averaged over `samples` random input + vectors of size `n`) + y = avg cycles / byte for the softmax_polynomial kernel + (same number as plot_rq42, loaded from + results/kernels.softmax_polynomial.csv) + +Each (precision, max_bits_lost) variant becomes one scatter point. Points +are connected in order of increasing max_bits_lost and labelled with the +corresponding `bN` (or `bN..M` when several adjacent budgets pick the +same chosen degree and therefore land on the same (cycles, ulp) point). + +A libm `baseline` reference is drawn as a single point at 0 bits lost +(libm always delivers reference precision) and the baseline cycles/byte +mean for that precision, when the CSV contains the baseline rows +registered by the Snakefile (kernels/softmax_polynomial/ +baseline.c.template). + +ULP errors below 1 are floored to 1 before the log2, so "within 1 ULP of +the reference" maps to 0 bits lost at the left edge instead of running off +to -inf; this matches the floor plot_rq41 uses for the bits conversion. Usage: python plot_rq43.py [-i results/kernels.softmax_polynomial.csv] \\ + [--n 64] [--samples 100] [--seed 0] \\ [-o plots-mia-thesis/output/rq43_plots.pdf] """ import argparse import re +from functools import lru_cache from pathlib import Path import matplotlib.pyplot as plt import numpy as np import pandas as pd +from plot_rq31 import chosen_degree +from plot_rq41 import ( + F16_BITS_LOST_CAP, + per_vector_mean_ulp_err, +) +from plot_rq42 import ( + BITS_LOST_VARIANT_RE, + avg_baseline, + load_baseline_csv, + load_bits_lost_csv, +) from plot_utils import ( + CHEBYSHEV_DOMAIN_LOWER, + CHEBYSHEV_DOMAIN_UPPER, + PRECISION_MANTISSA_BITS, PRECISIONS, - annotate_kernel_df, savefig, ) -BITS_LOST_VARIANT_RE = re.compile(r"linalg_xdsl_b(-?\d+)$") - -POLY_COLOR = "#33a02c" # matches rq32 -BASELINE_COLOR = "#1f78b4" # matches rq32 - - -def load_bits_lost_csv(csv_path: str) -> pd.DataFrame: - df = pd.read_csv(csv_path) - df = df[df["impl"].str.match(BITS_LOST_VARIANT_RE)].copy() - df["max_bits_lost"] = df["impl"].str.extract(BITS_LOST_VARIANT_RE).astype(int) - return annotate_kernel_df(df) - - -def load_baseline_csv(csv_path: str) -> pd.DataFrame: - df = pd.read_csv(csv_path) - df = df[df["impl"] == "baseline"].copy() - if df.empty: - return df - return annotate_kernel_df(df) - - -def avg_per_bits_lost(df: pd.DataFrame, precision: str, metric: str) -> pd.Series: - return ( - df[df["precision"] == precision] - .groupby("max_bits_lost")[metric] - .mean() - .sort_index() +DEFAULT_N = 64 +DEFAULT_SAMPLES = 100 +DEFAULT_SEED = 0 + +# Sub-ULP runs are clipped to this floor so log10(x) is finite. +ULP_FLOOR = 1.0 + +POINT_COLOR = "#33a02c" +BASELINE_COLOR = "#1f78b4" + + +@lru_cache(maxsize=None) +def _measure_for_degree( + precision: str, degree: int, n: int, samples: int, seed: int, +) -> float: + """Mean ULP error of the softmax output for a given (precision, degree). + Keyed on `degree` (not `max_bits_lost`) and seeded deterministically so + that all max_bits_lost variants that resolve to the same chosen_degree + produce *identical* measurements — they emit the same code, so the plot + should treat them as the same Pareto point.""" + rng = np.random.default_rng(np.uint64(seed)) + errs = [ + per_vector_mean_ulp_err(rng.uniform(-1.0, 1.0, n), degree, precision) + for _ in range(samples) + ] + return float(np.mean(errs)) + + +def _measure_ulp_err( + precision: str, bits_lost: int, n: int, samples: int, seed: int, +) -> float | None: + """Mean ULP error of the softmax output for (precision, max_bits_lost), + via the chosen_degree the pass would pick at that budget. Mirrors + plot_rq41 except it returns the raw ULP error (not log2).""" + if precision == "f16" and bits_lost >= F16_BITS_LOST_CAP: + return None + mantissa = PRECISION_MANTISSA_BITS[precision] + degree, _ = chosen_degree( + bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa, ) - - -def avg_baseline(df: pd.DataFrame, precision: str, metric: str) -> float: - if df.empty or "precision" not in df.columns or metric not in df.columns: - return float("nan") - sub = df.loc[df["precision"] == precision, metric] - return float("nan") if sub.empty else float(sub.mean()) - - -def plot_rq43(poly_df: pd.DataFrame, baseline_df: pd.DataFrame) -> plt.Figure: + return _measure_for_degree(precision, degree, n, samples, seed) + + +def collect_points( + poly_df: pd.DataFrame, n: int, samples: int, seed: int, +) -> pd.DataFrame: + """One row per (precision, max_bits_lost) in poly_df, carrying both + the measured ULP error (computed offline, à la rq41) and the avg + cycles/byte (averaged over input sizes, à la rq42).""" + rows = [] + for (precision, bits_lost), group in poly_df.groupby(["precision", "max_bits_lost"]): + ulp_err = _measure_ulp_err( + precision, int(bits_lost), n, samples, seed, + ) + if ulp_err is None: + continue + rows.append({ + "precision": precision, + "max_bits_lost": int(bits_lost), + "ulp_err": ulp_err, + "cycles_per_byte": float(group["cycles_per_byte"].mean()), + }) + return pd.DataFrame(rows) + + +def _format_bits_label(bs: list[int]) -> str: + """Collapse a sorted list of max_bits_lost values into a compact label + (`3` / `-1...1` / `-1,2,5`) for annotating coincident points. The + `max_bits_lost` meaning is stated once in the legend, not per point.""" + if len(bs) == 1: + return f"{bs[0]}" + if bs == list(range(bs[0], bs[-1] + 1)): + return f"{bs[0]}...{bs[-1]}" + return ",".join(str(b) for b in bs) + + +def plot_rq43( + points: pd.DataFrame, baseline_df: pd.DataFrame, +) -> plt.Figure: fig, axes = plt.subplots( 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False, ) for col_idx, precision in enumerate(PRECISIONS): ax = axes[col_idx] - series = avg_per_bits_lost(poly_df, precision, "cycles_per_byte") + sub = points[points["precision"] == precision].copy() baseline = avg_baseline(baseline_df, precision, "cycles_per_byte") - if not series.empty: + if not sub.empty: + # Bits lost = log2(ULP error), floored at 0 (ULP error floored + # at 1) so "within 1 ULP" sits at the left edge. + sub["x"] = np.log2(np.maximum(sub["ulp_err"].to_numpy(), ULP_FLOOR)) + # Variants whose chosen_degree collapses to the same value land + # on the same (cycles, ulp) point — group them so the line and + # annotations don't stack on top of each other. + grp = sub.groupby( + [sub["x"].round(9), sub["cycles_per_byte"].round(6)], + sort=False, + ) + groups = [] + for (x, y), g in grp: + bs = sorted(int(b) for b in g["max_bits_lost"]) + groups.append((float(x), float(y), bs)) + groups.sort(key=lambda t: min(t[2])) + + xs = [g[0] for g in groups] + ys = [g[1] for g in groups] ax.plot( - series.index, series.values, - marker="o", linestyle="-", color=POLY_COLOR, - label="Chebyshev polynomial (softmax)", + xs, ys, + marker="o", linestyle="-", color=POINT_COLOR, + label="Chebyshev polynomial (label = max_bits_lost)", ) + for x, y, bs in groups: + ax.annotate( + _format_bits_label(bs), + (x, y), + textcoords="offset points", + xytext=(8, 8), + fontsize=8, + ha="left", va="bottom", + bbox=dict( + boxstyle="round,pad=0.15", + fc="white", ec="none", alpha=0.75, + ), + ) + if not np.isnan(baseline): - ax.axhline( - baseline, color=BASELINE_COLOR, linestyle="--", + # libm always delivers reference precision, so it sits at 0 bits + # lost — a single point rather than a horizontal line. + ax.plot( + 0.0, baseline, + marker="^", markersize=7, linestyle="none", + color=BASELINE_COLOR, label=f"libm baseline ({baseline:.3g})", ) ax.set_title(precision) - ax.set_xlabel( - r"User-specified exp accuracy bound (max bits lost, looser $\rightarrow$)" - ) + ax.set_xlabel("measured average bits lost (softmax output)") if col_idx == 0: ax.set_ylabel("avg cycles / byte") - if not series.empty: - ax.set_xticks(series.index) - ax.grid(True, alpha=0.3) + ax.grid(True, which="both", alpha=0.3) ax.legend(loc="best", fontsize=8) fig.tight_layout() @@ -117,7 +216,19 @@ def main() -> None: parser.add_argument( "--input", "-i", default="results/kernels.softmax_polynomial.csv", - help="Input CSV with softmax_polynomial measurements", + help="softmax_polynomial measurement CSV", + ) + parser.add_argument( + "--n", type=int, default=DEFAULT_N, + help="Size of each sample input vector for the accuracy measurement", + ) + parser.add_argument( + "--samples", type=int, default=DEFAULT_SAMPLES, + help="Number of sample input vectors per (precision, max_bits_lost)", + ) + parser.add_argument( + "--seed", type=int, default=DEFAULT_SEED, + help="Base seed for input-vector sampling", ) parser.add_argument( "--output", "-o", @@ -129,7 +240,8 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) poly_df = load_bits_lost_csv(args.input) baseline_df = load_baseline_csv(args.input) - fig = plot_rq43(poly_df, baseline_df) + points = collect_points(poly_df, n=args.n, samples=args.samples, seed=args.seed) + fig = plot_rq43(points, baseline_df) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq44.py b/plots-mia-thesis/plot_rq44.py deleted file mode 100644 index 65934ca9..00000000 --- a/plots-mia-thesis/plot_rq44.py +++ /dev/null @@ -1,242 +0,0 @@ -#!/usr/bin/env python3 -""" -RQ44 plot: accuracy vs performance Pareto scatter for the -softmax_polynomial kernel, one panel per precision (f16/f32/f64). - - x = measured average ULP error of the softmax output - (computed exactly as in plot_rq40 — softmax.c arithmetic in DTYPE - with exp replaced by the lowered Clenshaw Chebyshev approximation, - compared against the same kernel with correctly-rounded libm exp, - averaged over `samples` random input vectors of size `n`) - y = avg cycles / byte for the softmax_polynomial kernel - (same number as plot_rq43, loaded from - results/kernels.softmax_polynomial.csv) - -Each (precision, max_bits_lost) variant becomes one scatter point. Points -are connected in order of increasing max_bits_lost and labelled with the -corresponding `bN` (or `bN..M` when several adjacent budgets pick the -same chosen degree and therefore land on the same (cycles, ulp) point). - -A libm `baseline` reference (a single horizontal line at the baseline -cycles/byte mean for that precision) is drawn when the CSV contains the -baseline rows registered by the Snakefile (kernels/softmax_polynomial/ -baseline.c.template). - -x-axis is log-scaled. ULP errors below 1 are floored to 1 so "within 1 -ULP of the reference" sits at the left edge instead of running off to --inf; this matches the floor plot_rq40 / plot_rq42 use for the bits -conversion. - -Usage: - python plot_rq44.py [-i results/kernels.softmax_polynomial.csv] \\ - [--n 64] [--samples 100] [--seed 0] \\ - [-o plots-mia-thesis/output/rq44_plots.pdf] -""" - -import argparse -import re -from functools import lru_cache -from pathlib import Path - -import matplotlib.pyplot as plt -import numpy as np -import pandas as pd - -from plot_rq31 import chosen_degree -from plot_rq40 import ( - F16_BITS_LOST_CAP, - per_vector_mean_ulp_err, -) -from plot_rq43 import ( - BITS_LOST_VARIANT_RE, - avg_baseline, - load_baseline_csv, - load_bits_lost_csv, -) -from plot_utils import ( - CHEBYSHEV_DOMAIN_LOWER, - CHEBYSHEV_DOMAIN_UPPER, - PRECISION_MANTISSA_BITS, - PRECISIONS, - savefig, -) - - -DEFAULT_N = 64 -DEFAULT_SAMPLES = 100 -DEFAULT_SEED = 0 - -# Sub-ULP runs are clipped to this floor so log10(x) is finite. -ULP_FLOOR = 1.0 - -POINT_COLOR = "#33a02c" -BASELINE_COLOR = "#1f78b4" - - -@lru_cache(maxsize=None) -def _measure_for_degree( - precision: str, degree: int, n: int, samples: int, seed: int, -) -> float: - """Mean ULP error of the softmax output for a given (precision, degree). - Keyed on `degree` (not `max_bits_lost`) and seeded deterministically so - that all max_bits_lost variants that resolve to the same chosen_degree - produce *identical* measurements — they emit the same code, so the plot - should treat them as the same Pareto point.""" - rng = np.random.default_rng(np.uint64(seed)) - errs = [ - per_vector_mean_ulp_err(rng.uniform(-1.0, 1.0, n), degree, precision) - for _ in range(samples) - ] - return float(np.mean(errs)) - - -def _measure_ulp_err( - precision: str, bits_lost: int, n: int, samples: int, seed: int, -) -> float | None: - """Mean ULP error of the softmax output for (precision, max_bits_lost), - via the chosen_degree the pass would pick at that budget. Mirrors - plot_rq40 except it returns the raw ULP error (not log2).""" - if precision == "f16" and bits_lost >= F16_BITS_LOST_CAP: - return None - mantissa = PRECISION_MANTISSA_BITS[precision] - degree, _ = chosen_degree( - bits_lost, CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER, mantissa, - ) - return _measure_for_degree(precision, degree, n, samples, seed) - - -def collect_points( - poly_df: pd.DataFrame, n: int, samples: int, seed: int, -) -> pd.DataFrame: - """One row per (precision, max_bits_lost) in poly_df, carrying both - the measured ULP error (computed offline, à la rq40) and the avg - cycles/byte (averaged over input sizes, à la rq43).""" - rows = [] - for (precision, bits_lost), group in poly_df.groupby(["precision", "max_bits_lost"]): - ulp_err = _measure_ulp_err( - precision, int(bits_lost), n, samples, seed, - ) - if ulp_err is None: - continue - rows.append({ - "precision": precision, - "max_bits_lost": int(bits_lost), - "ulp_err": ulp_err, - "cycles_per_byte": float(group["cycles_per_byte"].mean()), - }) - return pd.DataFrame(rows) - - -def _format_bits_label(bs: list[int]) -> str: - """Collapse a sorted list of max_bits_lost values into a compact label - (`b3` / `b-1..1` / `b-1,2,5`) for annotating coincident points.""" - if len(bs) == 1: - return f"b{bs[0]}" - if bs == list(range(bs[0], bs[-1] + 1)): - return f"b{bs[0]}..{bs[-1]}" - return "b" + ",".join(str(b) for b in bs) - - -def plot_rq44( - points: pd.DataFrame, baseline_df: pd.DataFrame, -) -> plt.Figure: - fig, axes = plt.subplots( - 1, len(PRECISIONS), figsize=(len(PRECISIONS) * 4.5, 4.0), sharey=False, - ) - - for col_idx, precision in enumerate(PRECISIONS): - ax = axes[col_idx] - sub = points[points["precision"] == precision].copy() - baseline = avg_baseline(baseline_df, precision, "cycles_per_byte") - - if not sub.empty: - sub["x"] = np.maximum(sub["ulp_err"].to_numpy(), ULP_FLOOR) - # Variants whose chosen_degree collapses to the same value land - # on the same (cycles, ulp) point — group them so the line and - # annotations don't stack on top of each other. - grp = sub.groupby( - [sub["x"].round(9), sub["cycles_per_byte"].round(6)], - sort=False, - ) - groups = [] - for (x, y), g in grp: - bs = sorted(int(b) for b in g["max_bits_lost"]) - groups.append((float(x), float(y), bs)) - groups.sort(key=lambda t: min(t[2])) - - xs = [g[0] for g in groups] - ys = [g[1] for g in groups] - ax.plot( - xs, ys, - marker="o", linestyle="-", color=POINT_COLOR, - label="Chebyshev polynomial (per max_bits_lost)", - ) - for x, y, bs in groups: - ax.annotate( - _format_bits_label(bs), - (x, y), - textcoords="offset points", - xytext=(8, 8), - fontsize=8, - ha="left", va="bottom", - bbox=dict( - boxstyle="round,pad=0.15", - fc="white", ec="none", alpha=0.75, - ), - ) - - if not np.isnan(baseline): - ax.axhline( - baseline, color=BASELINE_COLOR, linestyle="--", - label=f"libm baseline ({baseline:.3g})", - ) - - ax.set_xscale("log") - ax.set_title(precision) - ax.set_xlabel("measured average ULP error (softmax output)") - if col_idx == 0: - ax.set_ylabel("avg cycles / byte") - ax.grid(True, which="both", alpha=0.3) - ax.legend(loc="best", fontsize=8) - - fig.tight_layout() - return fig - - -def main() -> None: - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument( - "--input", "-i", - default="results/kernels.softmax_polynomial.csv", - help="softmax_polynomial measurement CSV", - ) - parser.add_argument( - "--n", type=int, default=DEFAULT_N, - help="Size of each sample input vector for the accuracy measurement", - ) - parser.add_argument( - "--samples", type=int, default=DEFAULT_SAMPLES, - help="Number of sample input vectors per (precision, max_bits_lost)", - ) - parser.add_argument( - "--seed", type=int, default=DEFAULT_SEED, - help="Base seed for input-vector sampling", - ) - parser.add_argument( - "--output", "-o", - default="plots-mia-thesis/output/rq44_plots.pdf", - help="Output plot file", - ) - args = parser.parse_args() - - Path(args.output).parent.mkdir(parents=True, exist_ok=True) - poly_df = load_bits_lost_csv(args.input) - baseline_df = load_baseline_csv(args.input) - points = collect_points(poly_df, n=args.n, samples=args.samples, seed=args.seed) - fig = plot_rq44(points, baseline_df) - savefig(fig, args.output) - print(f"Saved plot to {args.output}") - - -if __name__ == "__main__": - main() diff --git a/plots-mia-thesis/output/rq44_plots.pdf b/plots-mia-thesis/plots-mia-thesis/output/rq43_plots.pdf similarity index 52% rename from plots-mia-thesis/output/rq44_plots.pdf rename to plots-mia-thesis/plots-mia-thesis/output/rq43_plots.pdf index 8da01f78cdba6410db550e3b027cbd70d1094aef..7911c5f618ea5a10df89aee4af99ce0dfe8e2434 100644 GIT binary patch delta 11507 zcmZvC1yoes_qK>Rgh5FU-7qsuFhdClBHc(zcR38L4z1EMbTUY+zsHBtVB|Q-_3<1Y65m{r`QVk;KZ^gAw zZ)?u8$s4R!-(xcUAVp`JYZ?6U;f-&ZJajf%!{U90!ACm>lCz2_E_tmHFBGh^9o1x( zBvae3Ns6v>eX9TdWw^BT>%F7hZPiHZ{`joyPt5T;Fj8`+*W>p6Ln7=W(ayQ0@7t47 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+stays readable) and three input vectors per precision (f16, f32, f64). + +Inputs are generated the way the softmax_polynomial kernel sees them: + x ~ uniform(-1, 1, N) (mirrors softmax_polynomial/gendata.py) + x' = x - max(x) (the max-shift the kernel performs before exp) +so every x'_i lies in [CHEBYSHEV_DOMAIN_LOWER, CHEBYSHEV_DOMAIN_UPPER] = +[-2, 0] — the domain on which the pass fits exp. The Chebyshev coefficients +are computed with the same DCT-I formula used by xdsl_kernel_generate_source_chebyshev +in the Snakefile, and each approximation is evaluated with Clenshaw's +recurrence entirely in the target precision (via +`eval_chebyshev_clenshaw_lowered`, exactly as plot_rq13 does for exp), so the +curves here correspond bit-for-bit to what the xDSL pipeline emits — every +mul/add/sub rounded back to the element type, not summed in f64. + +Three different random seeds give three different input vectors per precision. +Each panel: + x-axis = element index i + y-axis = exp(x'_i) +with a "true" curve (correctly-rounded exp in the target precision) and one +curve per degree d in DEGREES = {2, 3, 4, 6, 12}. + +Usage: + python softmax_appendix.py [--n 16] [--seeds 0 1 2] \\ + [-o plots-mia-thesis/output/softmax_appendix.pdf] +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from plot_utils import ( + DEGREE_COLORS, + DEGREE_LINESTYLES, + PRECISION_NUMPY_DTYPE, + PRECISIONS, + chebyshev_lobatto_coeffs, + eval_chebyshev_clenshaw_lowered, + savefig, +) + + +DEFAULT_N = 16 +DEFAULT_SEEDS = [0, 1, 2] + +# Hand-picked subset of Chebyshev degrees to plot — restricted from the full +# 2..12 range so the visible per-degree variation stays readable. +DEGREES = [2, 3, 4, 6, 12] + + +def softmax_xprime(seed: int, n: int, precision: str) -> np.ndarray: + """Reproduce the per-element input that softmax_polynomial feeds to + exp_kernel: gendata's uniform(-1, 1, N) sequence cast to `precision`, + then x - max(x). Uses the legacy global RNG to match gendata.py.""" + dtype = PRECISION_NUMPY_DTYPE[precision] + np.random.seed(seed) + x = np.random.uniform(-1.0, 1.0, n).astype(dtype) + return (x - x.max()).astype(dtype) + + +def chebyshev_approx(x_prime: np.ndarray, degree: int, precision: str) -> np.ndarray: + """Degree-d Chebyshev-Lobatto interpolant of exp on [-2, 0], evaluated + with Clenshaw's recurrence entirely in `precision` — the exact arithmetic + the xDSL lowering emits, reproduced the same way plot_rq13 does + (`eval_chebyshev_clenshaw_lowered`), rather than summing in f64 and + rounding only the final value.""" + return eval_chebyshev_clenshaw_lowered( + chebyshev_lobatto_coeffs(degree), x_prime, precision + ) + + +def plot_softmax_appendix(n: int, seeds: list[int]) -> plt.Figure: + fig, axes = plt.subplots( + len(PRECISIONS), len(seeds), + figsize=(len(seeds) * 4.0, len(PRECISIONS) * 3.0), + sharex=True, + ) + + for row, precision in enumerate(PRECISIONS): + dtype = PRECISION_NUMPY_DTYPE[precision] + for col, seed in enumerate(seeds): + ax = axes[row][col] + x_prime = softmax_xprime(seed, n, precision) + idx = np.arange(n) + + exp_true = np.exp(x_prime.astype(np.float64)).astype(dtype) + ax.plot( + idx, exp_true, + color="black", marker="o", linestyle="-", linewidth=1.4, + label="exp(x) (correctly rounded)" if (row == 0 and col == 0) else None, + ) + + for d in DEGREES: + approx = chebyshev_approx(x_prime, d, precision) + ax.plot( + idx, approx, + color=DEGREE_COLORS[d], linestyle=DEGREE_LINESTYLES[d], + marker="x", markersize=4, linewidth=0.8, + label=f"d={d}" if (row == 0 and col == 0) else None, + ) + + if col == 0: + ax.set_ylabel(f"{precision}\nexp(x'_i)") + if row == len(PRECISIONS) - 1: + ax.set_xlabel("element index i") + ax.set_title(f"seed={seed}, N={n}") + ax.grid(True, alpha=0.3) + + axes[0][0].legend(ncol=2, fontsize=7, loc="upper left", bbox_to_anchor=(0.0, -0.0)) + fig.suptitle( + "Softmax exp inputs: correctly-rounded vs degree-d Chebyshev approximation" + ) + fig.tight_layout() + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--n", type=int, default=DEFAULT_N, + help="Number of elements per input vector", + ) + parser.add_argument( + "--seeds", type=int, nargs="+", default=DEFAULT_SEEDS, + help="Random seeds for the three input vectors", + ) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/softmax_appendix.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_softmax_appendix(args.n, args.seeds) + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() From 6d5625a1acf098070a36df3bcd8cdd22351234e2 Mon Sep 17 00:00:00 2001 From: szerdick Date: Thu, 4 Jun 2026 16:50:26 +0200 Subject: [PATCH 30/33] stale artifact --- .../plots-mia-thesis/output/rq43_plots.pdf | Bin 25902 -> 0 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plots-mia-thesis/output/rq2_plots.pdf | Bin 23699 -> 23618 bytes plots-mia-thesis/output/rq31_plots.pdf | Bin 21304 -> 21335 bytes plots-mia-thesis/output/rq32_plots.pdf | Bin 20149 -> 20105 bytes plots-mia-thesis/output/rq41_plots.pdf | Bin 20898 -> 20852 bytes plots-mia-thesis/output/rq42_plots.pdf | Bin 25933 -> 25842 bytes plots-mia-thesis/output/rq43_plots.pdf | Bin 21125 -> 21079 bytes plots-mia-thesis/output/softmax_appendix.pdf | Bin 45320 -> 44931 bytes plots-mia-thesis/plot_rq11.py | 2 ++ plots-mia-thesis/plot_rq12.py | 2 ++ plots-mia-thesis/plot_rq13.py | 2 ++ plots-mia-thesis/plot_rq2.py | 2 ++ plots-mia-thesis/plot_rq31.py | 2 ++ plots-mia-thesis/plot_rq32.py | 2 ++ plots-mia-thesis/plot_rq41.py | 2 ++ plots-mia-thesis/plot_rq42.py | 2 ++ plots-mia-thesis/plot_rq43.py | 2 ++ plots-mia-thesis/plot_utils.py | 5 +++++ plots-mia-thesis/softmax_appendix.py | 2 ++ 21 files changed, 25 insertions(+) diff --git a/plots-mia-thesis/output/rq11_plots.pdf 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+ despine, eval_chebyshev, savefig, ) @@ -67,6 +68,7 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) fig = plot_rq11() + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq12.py b/plots-mia-thesis/plot_rq12.py index e8423a7f..a25df0d2 100644 --- a/plots-mia-thesis/plot_rq12.py +++ b/plots-mia-thesis/plot_rq12.py @@ -36,6 +36,7 @@ PRECISION_NUMPY_DTYPE, PRECISIONS, chebyshev_lobatto_coeffs, + despine, eval_chebyshev, savefig, ulp, @@ -111,6 +112,7 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) fig = plot_rq12(args.xmin, args.xmax, args.npoints) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq13.py b/plots-mia-thesis/plot_rq13.py index f8c099ec..4e329d0a 100644 --- a/plots-mia-thesis/plot_rq13.py +++ b/plots-mia-thesis/plot_rq13.py @@ -53,6 +53,7 @@ PRECISION_NUMPY_DTYPE, PRECISIONS, chebyshev_lobatto_coeffs, + despine, eval_chebyshev_clenshaw_lowered, savefig, ulp, @@ -132,6 +133,7 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) fig = plot_rq13(args.xmin, args.xmax, args.npoints) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq2.py b/plots-mia-thesis/plot_rq2.py index 592ab69f..17fe53e6 100644 --- a/plots-mia-thesis/plot_rq2.py +++ b/plots-mia-thesis/plot_rq2.py @@ -27,6 +27,7 @@ from plot_utils import ( PRECISIONS, + despine, load_baseline_csv, load_chebyshev_csv, load_vendor_csv, @@ -123,6 +124,7 @@ def main() -> None: vendor_df = load_vendor_csv(args.exp_macro) fig = plot_rq2(poly_df, baseline_df, vendor_df) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq31.py b/plots-mia-thesis/plot_rq31.py index 58c7961f..b83cbed3 100644 --- a/plots-mia-thesis/plot_rq31.py +++ b/plots-mia-thesis/plot_rq31.py @@ -37,6 +37,7 @@ CHEBYSHEV_DOMAIN_UPPER, PRECISION_MANTISSA_BITS, PRECISIONS, + despine, savefig, ) @@ -149,6 +150,7 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) fig = plot_rq31(args.xmin, args.xmax, args.bits_lost) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq32.py b/plots-mia-thesis/plot_rq32.py index d48d9d80..3cfefb39 100644 --- a/plots-mia-thesis/plot_rq32.py +++ b/plots-mia-thesis/plot_rq32.py @@ -32,6 +32,7 @@ from plot_utils import ( PRECISIONS, annotate_kernel_df, + despine, load_baseline_csv, savefig, ) @@ -117,6 +118,7 @@ def main() -> None: poly_df = load_bits_lost_csv(args.input) baseline_df = load_baseline_csv(args.input) fig = plot_rq32(poly_df, baseline_df) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq41.py b/plots-mia-thesis/plot_rq41.py index 0985b04e..14ebdab5 100644 --- a/plots-mia-thesis/plot_rq41.py +++ b/plots-mia-thesis/plot_rq41.py @@ -66,6 +66,7 @@ PRECISION_NUMPY_DTYPE, PRECISIONS, chebyshev_lobatto_coeffs, + despine, eval_chebyshev_clenshaw_lowered, savefig, ulp, @@ -247,6 +248,7 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) fig = plot_rq41(args.n, args.samples, args.seed) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq42.py b/plots-mia-thesis/plot_rq42.py index 1162eaba..2480e2e5 100644 --- a/plots-mia-thesis/plot_rq42.py +++ b/plots-mia-thesis/plot_rq42.py @@ -35,6 +35,7 @@ from plot_utils import ( PRECISIONS, annotate_kernel_df, + despine, savefig, ) @@ -141,6 +142,7 @@ def main() -> None: poly_df = load_bits_lost_csv(args.input) baseline_df = load_baseline_csv(args.input) fig = plot_rq42(poly_df, baseline_df) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_rq43.py b/plots-mia-thesis/plot_rq43.py index f31fa1b1..b42ca223 100644 --- a/plots-mia-thesis/plot_rq43.py +++ b/plots-mia-thesis/plot_rq43.py @@ -60,6 +60,7 @@ CHEBYSHEV_DOMAIN_UPPER, PRECISION_MANTISSA_BITS, PRECISIONS, + despine, savefig, ) @@ -242,6 +243,7 @@ def main() -> None: baseline_df = load_baseline_csv(args.input) points = collect_points(poly_df, n=args.n, samples=args.samples, seed=args.seed) fig = plot_rq43(points, baseline_df) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") diff --git a/plots-mia-thesis/plot_utils.py b/plots-mia-thesis/plot_utils.py index adf3d6c4..57f148cb 100644 --- a/plots-mia-thesis/plot_utils.py +++ b/plots-mia-thesis/plot_utils.py @@ -382,6 +382,11 @@ def get_legend_entries(dfs: Sequence[pd.DataFrame]) -> dict[str, tuple[str, str, } +def despine(fig: Figure): + """Drop the top and right spines on every axis of `fig`.""" + sns.despine(fig=fig, top=True, right=True) + + def savefig(fig: Figure, filename: str): fig.savefig(filename) diff --git a/plots-mia-thesis/softmax_appendix.py b/plots-mia-thesis/softmax_appendix.py index ce836a5d..282f8952 100644 --- a/plots-mia-thesis/softmax_appendix.py +++ b/plots-mia-thesis/softmax_appendix.py @@ -41,6 +41,7 @@ PRECISION_NUMPY_DTYPE, PRECISIONS, chebyshev_lobatto_coeffs, + despine, eval_chebyshev_clenshaw_lowered, savefig, ) @@ -139,6 +140,7 @@ def main() -> None: Path(args.output).parent.mkdir(parents=True, exist_ok=True) fig = plot_softmax_appendix(args.n, args.seeds) + despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}") From 14c0c6ed4c79bb9c31deb58ff7d125b59c40ce55 Mon Sep 17 00:00:00 2001 From: szerdick Date: Thu, 4 Jun 2026 18:53:55 +0200 Subject: [PATCH 32/33] small ir figure --- plots-mia-thesis/ir_annotated.py | 203 ++++++++++++++++++ .../output/polynomial_eval_ir.pdf | Bin 0 -> 53395 bytes 2 files changed, 203 insertions(+) create mode 100644 plots-mia-thesis/ir_annotated.py create mode 100644 plots-mia-thesis/output/polynomial_eval_ir.pdf diff --git a/plots-mia-thesis/ir_annotated.py b/plots-mia-thesis/ir_annotated.py new file mode 100644 index 00000000..cd44b2d4 --- /dev/null +++ b/plots-mia-thesis/ir_annotated.py @@ -0,0 +1,203 @@ +#!/usr/bin/env python3 +""" +Annotated IR figure: a concrete `polynomial.eval` op with its four compile-time +aspects (approximation family, coefficients/degree, approximation domain, and +evaluation scheme) highlighted in different colours, keyed to the enumeration +in the polynomial-dialect section of the thesis. + +The op is the degree-2 Chebyshev-Lobatto interpolant of exp on [-2, 0] for an +f16 operand. Coefficients are the DCT-I values from +`plot_utils.chebyshev_lobatto_coeffs` (reproduced by `make_ir_snippet()`). + +Storage format follows the polynomial dialect merged into xDSL upstream main: +`EvalOp.get` stores the coefficients, the ring's `coefficientType`, AND the +domain bounds in the *operand* element type -- so for an f16 exp everything is +f16 (the values shown are the f16-rounded coefficients). NOTE: the xDSL build +pinned in this repo (and the 170 kernels/*.xdsl.mlir files) predate that change +and still use `coefficientType = f64`; this figure reflects the current +upstream convention the thesis describes. + +The header comment shows the thesis-facing `max_bits_lost` attribute on +`math.exp`. For degree 2 on [-2, 0] in f16 the bits-lost bound gives +bits_lost(2) ~ 8.30 and bits_lost(1) ~ 10.89, so max_bits_lost = 9 is the +realistic budget that selects exactly this degree-2 polynomial (8 would bump to +degree 3, 11 would drop to degree 1). + +Usage: + python ir_annotated.py [--output plots-mia-thesis/output/polynomial_eval_ir.pdf] +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +from matplotlib.patches import FancyBboxPatch + +from plot_utils import ( + dark_blue, + dark_green, + dark_gray, + dark_red, + light_blue, + light_green, + light_red, + savefig, +) + +# A fourth hue (orange) completes the four-aspect palette; the rest come from +# the shared ColorBrewer-Paired project palette in plot_utils. +light_orange = "#fdbf6f" +dark_orange = "#ff7f00" + +# aspect key -> (fill, edge, legend label) +ASPECTS = { + "family": (light_blue, dark_blue, + "approximation family (Chebyshev basis; extensible)"), + "coeff": (light_green, dark_green, + "coefficients $c_0\\dots c_d$ $\\Rightarrow$ degree $d$ (DCT-I, compile time)"), + "domain": (light_orange, dark_orange, + "approximation domain $[lower, upper]$ $\\Rightarrow$ affine map to $[-1, 1]$"), + "scheme": (light_red, dark_red, + "evaluation scheme (Clenshaw recurrence; extensible)"), +} + +# Degree-2 Chebyshev-Lobatto coefficients of exp on [-2, 0], stored in the +# operand format f16 (see module docstring). f16-rounded: note 0.4324 != the +# f64 value 0.4323, i.e. the rounding to the coefficient type is visible. +COEFFS = "0.9355, 0.4324, 0.1998" + +# The op, on a single line. Each line is a list of (text, aspect-key | None) +# segments; highlighted segments get a coloured box drawn behind them. +CODE_LINES: list[list[tuple[str, str | None]]] = [ + [ + ("%r = ", None), + ("polynomial.eval ", None), + ("#polynomial.", None), + ("typed_chebyshev_polynomial", "family"), + ("<[", None), + (COEFFS, "coeff"), + ("]> : !polynomial.polynomial>, ", None), + ("%x ", None), + ("{", None), + ('scheme = "clenshaw"', "scheme"), + (", ", None), + ("domain_lower = -2.0 : f16", "domain"), + (", ", None), + ("domain_upper = 0.0 : f16", "domain"), + ("} ", None), + (": f16", None), + ], +] + +# grey provenance comments shown above / below the op. +# The pass selects the lowest Chebyshev degree meeting the `max_bits_lost` +# budget (the thesis-facing attribute on `math.exp`). On [-2, 0] in f16 the +# bits-lost bound puts degree 2 in the window max_bits_lost in [8.30, 10.89), +# so 9 is the realistic budget that yields the small polynomial shown here. +HEADER = "// math.exp (f16, max_bits_lost = 9) --lower-exp-to-polynomial-->" +FOOTER = ("// --expand-polynomial-eval--> 12 branch-free mulf/addf/subf ops" + " (no branches, no memory)") + +FONT = 11.5 +CHAR_IN = 0.6 * FONT / 72.0 # monospace advance width (DejaVu Sans Mono ~0.6em) +LINE_IN = 0.30 # vertical pitch per text line, inches +LEFT_PAD = 1 # margin columns +RIGHT_PAD = 2 + + +def make_ir_snippet() -> list[float]: + """Recompute the degree-2 coefficients on [-2, 0] (the DCT-I the pass uses) + and round them to f16, the operand/coefficient type the upstream dialect + stores. Should match COEFFS above.""" + import numpy as np + + from plot_utils import chebyshev_lobatto_coeffs + + return [float(np.float16(c)) for c in chebyshev_lobatto_coeffs(2)] + + +def _seg_len(line: list[tuple[str, str | None]]) -> int: + return sum(len(t) for t, _ in line) + + +def plot_ir() -> plt.Figure: + # Rows (top to bottom): header, blank, op (one line), blank, footer, + # blank, legend (one horizontal row). + code_cols = max(_seg_len(l) for l in CODE_LINES) + ncols = LEFT_PAD + max(code_cols, len(HEADER), len(FOOTER)) + RIGHT_PAD + n_rows = 8 + + fig_w = ncols * CHAR_IN + fig_h = n_rows * LINE_IN + fig = plt.figure(figsize=(fig_w, fig_h)) + ax = fig.add_axes((0, 0, 1, 1)) + ax.set_xlim(0, ncols) + ax.set_ylim(0, n_rows) + ax.axis("off") + + def row_y(i: int) -> float: + return n_rows - 0.5 - i + + # --- provenance header ------------------------------------------------ + ax.text(LEFT_PAD, row_y(0), HEADER, family="monospace", fontsize=FONT - 1.5, + color=dark_gray, va="center", ha="left", fontstyle="italic") + + # --- the op, with highlighted aspects --------------------------------- + for li, line in enumerate(CODE_LINES): + y = row_y(li + 2) + col = LEFT_PAD + for text, key in line: + if key is not None: + fill, edge, _ = ASPECTS[key] + ax.add_patch(FancyBboxPatch( + (col - 0.15, y - 0.42), + len(text) + 0.3, 0.84, + boxstyle="round,pad=0.02,rounding_size=0.18", + linewidth=1.2, edgecolor=edge, facecolor=fill, zorder=1, + )) + weight = "bold" if (text.strip() == "polynomial.eval") else "normal" + ax.text(col, y, text, family="monospace", fontsize=FONT, + va="center", ha="left", zorder=2, fontweight=weight) + col += len(text) + + # --- footer ----------------------------------------------------------- + ax.text(LEFT_PAD, row_y(4), FOOTER, family="monospace", + fontsize=FONT - 1.5, color=dark_gray, va="center", ha="left", + fontstyle="italic") + + # --- legend: 2x2 grid keyed to the op-line width --------------------- + swatch_w = 2.0 + gap_after_swatch = 0.6 + col_x = [LEFT_PAD, LEFT_PAD + (ncols - LEFT_PAD - RIGHT_PAD) / 2] + for j, (key, (fill, edge, label)) in enumerate(ASPECTS.items()): + r, c = divmod(j, 2) + x = col_x[c] + y = row_y(6 + r) + ax.add_patch(FancyBboxPatch( + (x, y - 0.30), swatch_w, 0.6, + boxstyle="round,pad=0.02,rounding_size=0.18", + linewidth=1.2, edgecolor=edge, facecolor=fill, zorder=1, + )) + ax.text(x + swatch_w + gap_after_swatch, y, label, + fontsize=FONT - 1.5, va="center", ha="left", color="#222222") + + return fig + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--output", "-o", + default="plots-mia-thesis/output/polynomial_eval_ir.pdf", + help="Output plot file", + ) + args = parser.parse_args() + + Path(args.output).parent.mkdir(parents=True, exist_ok=True) + fig = plot_ir() + savefig(fig, args.output) + print(f"Saved plot to {args.output}") + + +if __name__ == "__main__": + main() diff --git a/plots-mia-thesis/output/polynomial_eval_ir.pdf 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exist_ok=True) fig = plot_rq31(args.xmin, args.xmax, args.bits_lost) - despine(fig) savefig(fig, args.output) print(f"Saved plot to {args.output}")