Batch solver

.github/workflows/action.yml

@@ -14,7 +14,7 @@ jobs:
     strategy:
       matrix:
           os: [ubuntu-22.04]
-          julia-version: ['lts', '1']
+          julia-version: ['1']
           julia-arch: [x64]
     steps:
       - uses: actions/checkout@v4

.github/workflows/gpu.yml

@@ -19,7 +19,7 @@ jobs:
       labels: cuda
     strategy:
       matrix:
-        julia-version: ['lts', '1']
+        julia-version: ['1']
         julia-arch: [x64]
         hsl-version: ['2025.7.11']
 
@@ -29,10 +29,5 @@ jobs:
         with:
           channel: ${{ matrix.julia-version }}
       - uses: julia-actions/julia-buildpkg@latest
-      - name: Test MadIPM.jl
-        shell: julia --color=yes {0}
-        run: |
-          using Pkg
-          Pkg.develop(path=".")
-          Pkg.test("MadIPM")
+      - uses: julia-actions/julia-runtest@latest
 

Project.toml

@@ -1,9 +1,10 @@
 name = "MadIPM"
 uuid = "4406d55e-1099-4ca6-ac6a-6cf051b10024"
-authors = ["François Pacaud <francoispacaud8@gmail.com>", "Alexis Montoison <amontoison@anl.gov>"]
 version = "0.2.0"
+authors = ["François Pacaud <francoispacaud8@gmail.com>", "Alexis Montoison <amontoison@anl.gov>"]
 
 [deps]
+BatchQuadraticModels = "412afcf0-3ec6-4826-be17-8d792afa05a8"
 LDLFactorizations = "40e66cde-538c-5869-a4ad-c39174c6795b"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MadNLP = "2621e9c9-9eb4-46b1-8089-e8c72242dfb6"
@@ -13,17 +14,25 @@ QuadraticModels = "f468eda6-eac5-11e8-05a5-ff9e497bcd19"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [weakdeps]
+Atomix = "a9b6321e-bd34-4604-b9c9-b65b8de01458"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
+CUDSS = "45b445bb-4962-46a0-9369-b4df9d0f772e"
 KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
 MadNLPGPU = "d72a61cc-809d-412f-99be-fd81f4b8a598"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 
+[sources]
+BatchQuadraticModels = {rev = "main", url = "https://github.com/klamike/BatchQuadraticModels.jl.git"}
+
 [extensions]
-MadIPMCUDAExt = ["CUDA", "KernelAbstractions", "MadNLPGPU"]
+MadIPMCUDAExt = ["Atomix", "CUDA", "CUDSS", "KernelAbstractions", "MadNLPGPU"]
 MadIPMMathOptInterfaceExt = "MathOptInterface"
 
 [compat]
+Atomix = "1"
+BatchQuadraticModels = "0.1"
 CUDA = "5.4.0"
+CUDSS = "0.6"
 KernelAbstractions = "0.9"
 LDLFactorizations = "0.10.1"
 LinearAlgebra = "1.10"
@@ -39,8 +48,14 @@ Test = "1.10"
 julia = "1.10"
 
 [extras]
+Atomix = "a9b6321e-bd34-4604-b9c9-b65b8de01458"
+CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
+CUDSS = "45b445bb-4962-46a0-9369-b4df9d0f772e"
+KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
+MadNLPGPU = "d72a61cc-809d-412f-99be-fd81f4b8a598"
 MadNLPTests = "b52a2a03-04ab-4a5f-9698-6a2deff93217"
+MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["CUDA", "KernelAbstractions", "MadNLPTests", "MadNLPGPU", "MathOptInterface", "Test"]
+test = ["Atomix", "CUDA", "CUDSS", "KernelAbstractions", "MadNLPTests", "MadNLPGPU", "MathOptInterface", "Test"]

ext/MadIPMCUDAExt/MadIPMCUDAExt.jl

@@ -3,15 +3,25 @@ module MadIPMCUDAExt
 using LinearAlgebra
 using SparseArrays
 using NLPModels
+using BatchQuadraticModels
 using QuadraticModels
 using CUDA
 using CUDA.CUSPARSE
+using CUDSS
 using KernelAbstractions
+import Atomix
 import QuadraticModels: SparseMatrixCOO
+import LinearAlgebra: BlasFloat
 import MadIPM
+import MadNLP
 
-include("cuda_wrapper.jl")
 include("operators.jl")
+include("cuda_wrapper.jl")
+include("cuda_batch_kernels.jl")
+
+function MadIPM._csc_with_nzval(A::CUSPARSE.CuSparseMatrixCSC, nzval, n)
+    return CUSPARSE.CuSparseMatrixCSC(A.colPtr, A.rowVal, nzval, (n, n))
+end
 
 @kernel function _fill_sparse_structure!(rows, cols, Ap, Aj, Ax)
     i = @index(Global, Linear)
@@ -138,4 +148,3 @@ function Base.convert(::Type{QuadraticModel{T, S}}, qp::QuadraticModel{T}) where
 end
 
 end
-