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Task2 #1

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ff0bb7c
feat: add solution of task 1
ibmpowerpc Apr 27, 2026
14712fe
feat: add solution of task 2
ibmpowerpc Apr 28, 2026
677d169
feat: add kernel composition
ibmpowerpc Apr 30, 2026
0cdd5e3
feat: add benchmarking & arg parsing library
ibmpowerpc May 1, 2026
03f1780
feat: add images
ibmpowerpc May 1, 2026
854ec46
refactor: remove redundant checks
ibmpowerpc May 10, 2026
7dcc949
readme: added plot analysis
ibmpowerpc Jun 4, 2026
9e2fa9c
readme: add plot & rewrite analysis
ibmpowerpc Jun 4, 2026
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5 changes: 4 additions & 1 deletion .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,9 @@ build/
!gradle/wrapper/gradle-wrapper.jar
!**/src/main/**/build/
!**/src/test/**/build/
output/*
benchmark-results/*
plots/*

### IntelliJ IDEA ###
.idea/modules.xml
Expand Down Expand Up @@ -42,4 +45,4 @@ bin/
.vscode/

### Mac OS ###
.DS_Store
.DS_Store
6 changes: 6 additions & 0 deletions .idea/gradle.xml
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47 changes: 47 additions & 0 deletions README.md
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@@ -0,0 +1,47 @@
# Анализ производительности
Эксперимент проводился на машине со следующими характеристиками: macOS 15.7.7, MacBook Air, Apple M3 CPU с 8 ядрами, 16 GB LPDDR5 RAM, Apple M3 GPU с 8 ядрами. macOS фиксированную частоту CPU не показывает.

## Результаты измерений

Ядро свёртки: `gaussian3`.

Размер изображения fox.bmp: 2464 x 1412 пикселей.

| strategy | partition_kind | partition_value | threads | avg_ms | min_ms | max_ms | stddev_ms | ci95_low_ms | ci95_high_ms | throughput_mp_s | throughput_ci95_low_mp_s | throughput_ci95_high_mp_s |
|------------|----------------|-----------------|---------|------------|------------|------------|-----------|-------------|--------------|-----------------|--------------------------|---------------------------|
| sequential | none | - | 1 | 35.706878 | 34.784208 | 37.341875 | 0.758688 | 35.322929 | 36.090827 | 97.477332 | 96.445753 | 98.508912 |
| pixels | none | - | 1 | 38.955314 | 38.332459 | 40.153666 | 0.439817 | 38.732736 | 39.177892 | 89.322240 | 88.819319 | 89.825161 |
| rows | none | - | 1 | 35.227875 | 34.960041 | 35.719541 | 0.212832 | 35.120167 | 35.335583 | 98.765140 | 98.464459 | 99.065822 |
| columns | none | - | 1 | 39.751442 | 39.227875 | 40.233417 | 0.286755 | 39.606323 | 39.896560 | 87.527315 | 87.207807 | 87.846824 |
| grid | grid | 2x2 | 1 | 35.236372 | 34.970125 | 35.804875 | 0.249382 | 35.110168 | 35.362577 | 98.742557 | 98.391473 | 99.093640 |
| grid | grid | 4x4 | 1 | 35.559728 | 35.198875 | 37.073000 | 0.495082 | 35.309182 | 35.810274 | 97.857317 | 97.187501 | 98.527132 |
| grid | tile | 32x32 | 1 | 36.646395 | 35.969125 | 37.088916 | 0.311479 | 36.488765 | 36.804024 | 94.945340 | 94.533800 | 95.356881 |
| grid | tile | 64x64 | 1 | 35.720978 | 35.420000 | 36.130958 | 0.184447 | 35.627635 | 35.814321 | 97.400867 | 97.147436 | 97.654298 |
| grid | tile | 128x128 | 1 | 35.391764 | 35.250333 | 35.690833 | 0.156303 | 35.312664 | 35.470864 | 98.306235 | 98.087437 | 98.525034 |
| pixels | none | - | 2 | 106.870856 | 99.278542 | 117.567000 | 4.554990 | 104.565712 | 109.175999 | 32.609167 | 31.917432 | 33.300902 |
| rows | none | - | 2 | 18.318461 | 18.148250 | 18.669375 | 0.178265 | 18.228247 | 18.408676 | 189.943501 | 189.016865 | 190.870137 |
| columns | none | - | 2 | 22.482153 | 21.733333 | 23.283625 | 0.474377 | 22.242085 | 22.722221 | 154.817026 | 153.157035 | 156.477017 |
| grid | grid | 2x2 | 2 | 18.286422 | 18.093167 | 18.627292 | 0.203578 | 18.183397 | 18.389447 | 190.281519 | 189.215578 | 191.347461 |
| grid | grid | 4x4 | 2 | 18.261758 | 18.065584 | 18.745792 | 0.215349 | 18.152777 | 18.370740 | 190.541079 | 189.415229 | 191.666929 |
| grid | tile | 32x32 | 2 | 19.121575 | 18.890834 | 19.631333 | 0.216260 | 19.012132 | 19.231018 | 181.971307 | 180.943323 | 182.999291 |
| grid | tile | 64x64 | 2 | 18.507408 | 18.395625 | 18.822333 | 0.130973 | 18.441127 | 18.573690 | 187.996550 | 187.330276 | 188.662824 |
| grid | tile | 128x128 | 2 | 18.237692 | 18.126250 | 18.552500 | 0.149770 | 18.161898 | 18.313486 | 190.779883 | 189.995350 | 191.564416 |
| pixels | none | - | 4 | 123.311592 | 119.402875 | 133.228750 | 3.485566 | 121.547652 | 125.075531 | 28.234697 | 27.845904 | 28.623490 |
| rows | none | - | 4 | 9.509681 | 9.402167 | 9.837625 | 0.159100 | 9.429165 | 9.590196 | 365.948807 | 362.921513 | 368.976101 |
| columns | none | - | 4 | 11.534620 | 11.386459 | 11.899417 | 0.178398 | 11.444338 | 11.624902 | 301.694633 | 299.369870 | 304.019397 |
| grid | grid | 2x2 | 4 | 9.639872 | 9.435375 | 10.236958 | 0.280458 | 9.497941 | 9.781804 | 361.190220 | 356.047826 | 366.332614 |
| grid | grid | 4x4 | 4 | 9.549867 | 9.439958 | 9.867000 | 0.160937 | 9.468422 | 9.631312 | 364.410330 | 361.371091 | 367.449569 |
| grid | tile | 32x32 | 4 | 9.963600 | 9.803458 | 10.268583 | 0.157785 | 9.883750 | 10.043450 | 349.268477 | 346.507582 | 352.029373 |
| grid | tile | 64x64 | 4 | 9.713842 | 9.553750 | 10.400125 | 0.241588 | 9.591581 | 9.836102 | 358.364671 | 354.032386 | 362.696957 |
| grid | tile | 128x128 | 4 | 9.655564 | 9.470958 | 9.937917 | 0.121603 | 9.594024 | 9.717104 | 360.380848 | 358.096359 | 362.665337 |
| pixels | none | - | 8 | 161.366297 | 158.185500 | 165.082833 | 2.538605 | 160.081586 | 162.651009 | 21.565648 | 21.394590 | 21.736707 |
| rows | none | - | 8 | 7.134322 | 6.794458 | 7.658750 | 0.255865 | 7.004837 | 7.263808 | 488.243440 | 479.511935 | 496.974945 |
| columns | none | - | 8 | 8.667350 | 8.351375 | 9.046125 | 0.200737 | 8.565763 | 8.768937 | 401.610950 | 396.923880 | 406.298021 |
| grid | grid | 2x2 | 8 | 9.620889 | 9.494167 | 9.906792 | 0.156201 | 9.541840 | 9.699938 | 361.714077 | 358.787946 | 364.640209 |
| grid | grid | 4x4 | 8 | 7.520278 | 7.180750 | 9.192291 | 0.509240 | 7.262567 | 7.777989 | 464.355097 | 450.562296 | 478.147898 |
| grid | tile | 32x32 | 8 | 7.149239 | 7.000417 | 7.481750 | 0.146932 | 7.074881 | 7.223597 | 486.835720 | 481.901353 | 491.770087 |
| grid | tile | 64x64 | 8 | 7.139611 | 6.827333 | 8.497417 | 0.410477 | 6.931881 | 7.347341 | 488.626677 | 476.135460 | 501.117894 |
| grid | tile | 128x128 | 8 | 7.398150 | 7.072500 | 7.968417 | 0.307492 | 7.242538 | 7.553762 | 471.015450 | 461.354857 | 480.676043 |

![gaussian3-throughput.svg](gaussian3-throughput.svg)
На этом графике показана зависимость пропускной способности свёртки от числа потоков и стратегии. Видно, что стратегия pixels сильно проигрывает по скорости остальным стратегиям. Это происходит из-за того, что потоки постоянно обращаются к одной и той же атомарной переменной, отвечающей за индекс пикселя. Атомарная операция `getAndIncrement()` дороже обычного инкремента, потому что требует синхронизации со всеми потоками. Все остальные стратегии при увеличении числа потоков завершают свёртку быстрее, чем последовательная, потому что потоки меньше мешают друг другу. Также видно, что при увеличении числа потоков прирост для каждой стратегии становится меньше, что объясняется законом Амдала. Throughput стратегии grid 2x2 перестаёт расти при увеличении числа потоков с 4 до 8, потому что объём работы на каждый поток слишком маленький, из-за чего потоки могут мешать друг другу, как в стратегии pixels.
20 changes: 18 additions & 2 deletions build.gradle.kts
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@@ -1,21 +1,37 @@
plugins {
application
kotlin("jvm") version "2.1.10"
}

group = "org.example"
group = "convolution"
version = "1.0-SNAPSHOT"

repositories {
mavenCentral()
}

dependencies {
implementation("org.apache.commons:commons-csv:1.14.1")
implementation("org.jetbrains.kotlinx:kotlinx-cli:0.3.6")
implementation("org.openpnp:opencv:4.9.0-0")
testImplementation(kotlin("test"))
}

tasks.test {
useJUnitPlatform()
}

tasks.register<JavaExec>("benchmarkConvolution") {
group = "application"
description = "Run the convolution benchmark matrix and save the results to CSV."
classpath = sourceSets["main"].runtimeClasspath
mainClass = "convolution.BenchmarkMainKt"
}

application {
mainClass = "convolution.MainKt"
}

kotlin {
jvmToolchain(23)
}
}
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