diff --git a/tasks/khalitova-am/lab_5/App/.gitignore b/tasks/khalitova-am/lab_5/App/.gitignore new file mode 100644 index 0000000..2afa2e2 --- /dev/null +++ b/tasks/khalitova-am/lab_5/App/.gitignore @@ -0,0 +1,454 @@ +## Ignore Visual Studio temporary files, build results, and +## files generated by popular Visual Studio add-ons. +## +## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore + +# User-specific files +*.rsuser +*.suo +*.user +*.userosscache +*.sln.docstates + +# User-specific files (MonoDevelop/Xamarin Studio) +*.userprefs + +# Mono auto generated files +mono_crash.* + +# Build results +[Dd]ebug/ +[Dd]ebugPublic/ +[Rr]elease/ +[Rr]eleases/ +x64/ +x86/ +[Ww][Ii][Nn]32/ +[Aa][Rr][Mm]/ +[Aa][Rr][Mm]64/ +bld/ +[Bb]in/ +[Oo]bj/ +[Ll]og/ +[Ll]ogs/ + +# Visual Studio 2015/2017 cache/options directory +.vs/ +# Uncomment if you have tasks that create the project's static files in wwwroot +#wwwroot/ + +# Visual Studio 2017 auto generated files +Generated\ Files/ + +# MSTest test Results +[Tt]est[Rr]esult*/ +[Bb]uild[Ll]og.* + +# NUnit +*.VisualState.xml +TestResult.xml +nunit-*.xml + +# Build Results of an ATL Project +[Dd]ebugPS/ +[Rr]eleasePS/ +dlldata.c + +# Benchmark Results +BenchmarkDotNet.Artifacts/ + +# .NET +project.lock.json +project.fragment.lock.json +artifacts/ + +# Tye +.tye/ + +# ASP.NET Scaffolding +ScaffoldingReadMe.txt + +# StyleCop +StyleCopReport.xml + +# Files built by Visual Studio +*_i.c +*_p.c +*_h.h +*.ilk +*.meta +*.obj +*.iobj +*.pch +*.pdb +*.ipdb +*.pgc +*.pgd +*.rsp +*.sbr +*.tlb +*.tli +*.tlh +*.tmp +*.tmp_proj +*_wpftmp.csproj +*.log +*.vspscc +*.vssscc +.builds +*.pidb +*.svclog +*.scc + +# Chutzpah Test files +_Chutzpah* + +# Visual C++ cache files +ipch/ +*.aps +*.ncb +*.opendb +*.opensdf +*.sdf +*.cachefile +*.VC.db +*.VC.VC.opendb + +# Visual Studio profiler +*.psess +*.vsp +*.vspx +*.sap + +# Visual Studio Trace Files +*.e2e + +# TFS 2012 Local Workspace +$tf/ + +# Guidance Automation Toolkit +*.gpState + +# ReSharper is a .NET coding add-in +_ReSharper*/ +*.[Rr]e[Ss]harper +*.DotSettings.user + +# TeamCity is a build add-in +_TeamCity* + +# DotCover is a Code Coverage Tool +*.dotCover + +# AxoCover is a Code Coverage Tool +.axoCover/* +!.axoCover/settings.json + +# Coverlet is a free, cross platform Code Coverage Tool +coverage*.json +coverage*.xml +coverage*.info + +# Visual Studio code coverage results +*.coverage +*.coveragexml + +# NCrunch +_NCrunch_* +.*crunch*.local.xml +nCrunchTemp_* + +# MightyMoose +*.mm.* +AutoTest.Net/ + +# Web workbench (sass) +.sass-cache/ + +# Installshield output folder +[Ee]xpress/ + +# DocProject is a documentation generator add-in +DocProject/buildhelp/ +DocProject/Help/*.HxT +DocProject/Help/*.HxC +DocProject/Help/*.hhc +DocProject/Help/*.hhk +DocProject/Help/*.hhp +DocProject/Help/Html2 +DocProject/Help/html + +# Click-Once directory +publish/ + +# Publish Web Output +*.[Pp]ublish.xml +*.azurePubxml +# Note: Comment the next line if you want to checkin your web deploy settings, +# but database connection strings (with potential passwords) will be unencrypted +*.pubxml +*.publishproj + +# Microsoft Azure Web App publish settings. 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+using System.Diagnostics; +using System.Threading.Tasks; +using BenchmarkDotNet.Attributes; +using BenchmarkDotNet.Running; + +public class MatrixMultiplication +{ + public static int[][] MultiplySequential(int[][] matrixA, int[][] matrixB) + { + int rowsA = matrixA.Length; + int colsA = matrixA[0].Length; + int colsB = matrixB[0].Length; + + int[][] result = new int[rowsA][]; + + for (int i = 0; i < rowsA; i++) + { + result[i] = new int[colsB]; + + for (int j = 0; j < colsB; j++) + { + for (int k = 0; k < colsA; k++) + { + result[i][j] += matrixA[i][k] * matrixB[k][j]; + } + } + } + + return result; + } + + public static int[][] MultiplyParallel(int[][] matrixA, int[][] matrixB, int numThreads) + { + int rowsA = matrixA.Length; + int colsA = matrixA[0].Length; + int colsB = matrixB[0].Length; + + int[][] result = new int[rowsA][]; + + Parallel.For(0, rowsA, new ParallelOptions { MaxDegreeOfParallelism = numThreads }, i => + { + result[i] = new int[colsB]; + + for (int j = 0; j < colsB; j++) + { + for (int k = 0; k < colsA; k++) + { + result[i][j] += matrixA[i][k] * matrixB[k][j]; + } + } + }); + + return result; + } + + [Benchmark] + public void MultiplySequential_100x100() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplySequential(matrixA, matrixB); + } + + [Benchmark] + public void MultiplyParallel_100x100_4TH() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplyParallel(matrixA, matrixB, 4); + } + [Benchmark] + public void MultiplyParallel_100x100_8TH() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplyParallel(matrixA, matrixB, 8); + + } + [Benchmark] + public void MultiplyParallel_100x100_16TH() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplyParallel(matrixA, matrixB, 16); + + } + + [Benchmark] + public void MultiplySequential_300x300() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplySequential(matrixA, matrixB); + } + + [Benchmark] + public void MultiplyParallel_300x300_4TH() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplyParallel(matrixA, matrixB, 4); + } + [Benchmark] + public void MultiplyParallel_300x300_8TH() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplyParallel(matrixA, matrixB, 8); + } + [Benchmark] + public void MultiplyParallel_300x300_16TH() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplyParallel(matrixA, matrixB, 16); + } + [Benchmark] + public void MultiplySequential_500x500() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplySequential(matrixA, matrixB); + } + + [Benchmark] + public void MultiplyParallel_500x500_4TH() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplyParallel(matrixA, matrixB, 4); + } + [Benchmark] + public void MultiplyParallel_500x500_8TH() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplyParallel(matrixA, matrixB, 8); + } + [Benchmark] + public void MultiplyParallel_500x500_16TH() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplyParallel(matrixA, matrixB, 16); + } + private static int[][] GenerateRandomMatrix(int rows, int cols) + { + int[][] matrix = new int[rows][]; + + Random rand = new Random(); + + for (int i = 0; i < rows; i++) + { + matrix[i] = new int[cols]; + for (int j = 0; j < cols; j++) + { + matrix[i][j] = rand.Next(1, 10); + } + } + + return matrix; + } +} + +class Program +{ + static void Main(string[] args) + { + var summary = BenchmarkRunner.Run(); + Console.ReadLine(); + } +} \ No newline at end of file diff --git a/tasks/khalitova-am/lab_5/README.md b/tasks/khalitova-am/lab_5/README.md new file mode 100644 index 0000000..d8bf936 --- /dev/null +++ b/tasks/khalitova-am/lab_5/README.md @@ -0,0 +1,191 @@ +# Отчёт по лабораторной работе №5 + +Выполнила: студентка гр. ИСЭбд-41 Халитова А.М. + +## Создание приложения + +В приложении были созданы следующие методы: + +- Заполнение матрицы рандомными значениями: +``` + private static int[][] GenerateRandomMatrix(int rows, int cols) + { + int[][] matrix = new int[rows][]; + + Random rand = new Random(); + + for (int i = 0; i < rows; i++) + { + matrix[i] = new int[cols]; + for (int j = 0; j < cols; j++) + { + matrix[i][j] = rand.Next(1, 10); + } + } + + return matrix; + } +``` + +- Перемножение матриц обычным алгоритмом: +``` + public static int[][] MultiplySequential(int[][] matrixA, int[][] matrixB) + { + int rowsA = matrixA.Length; + int colsA = matrixA[0].Length; + int colsB = matrixB[0].Length; + + int[][] result = new int[rowsA][]; + + for (int i = 0; i < rowsA; i++) + { + result[i] = new int[colsB]; + + for (int j = 0; j < colsB; j++) + { + for (int k = 0; k < colsA; k++) + { + result[i][j] += matrixA[i][k] * matrixB[k][j]; + } + } + } + + return result; + } +``` + +- Перемножение матриц параллельным алгоритмом: +``` + public static int[][] MultiplyParallel(int[][] matrixA, int[][] matrixB, int numThreads) + { + int rowsA = matrixA.Length; + int colsA = matrixA[0].Length; + int colsB = matrixB[0].Length; + + int[][] result = new int[rowsA][]; + + Parallel.For(0, rowsA, new ParallelOptions { MaxDegreeOfParallelism = numThreads }, i => + { + result[i] = new int[colsB]; + + for (int j = 0; j < colsB; j++) + { + for (int k = 0; k < colsA; k++) + { + result[i][j] += matrixA[i][k] * matrixB[k][j]; + } + } + }); + + return result; + } +``` + +- Создание матриц различных размеров и с различным количеством потоков для параллельного алгоритма: +``` + [Benchmark] + public void MultiplySequential_100x100() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplySequential(matrixA, matrixB); + } + + [Benchmark] + public void MultiplyParallel_100x100_4TH() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplyParallel(matrixA, matrixB, 4); + } + [Benchmark] + public void MultiplyParallel_100x100_8TH() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplyParallel(matrixA, matrixB, 8); + + } + [Benchmark] + public void MultiplyParallel_100x100_16TH() + { + int[][] matrixA = GenerateRandomMatrix(100, 100); + int[][] matrixB = GenerateRandomMatrix(100, 100); + MultiplyParallel(matrixA, matrixB, 16); + + } + + [Benchmark] + public void MultiplySequential_300x300() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplySequential(matrixA, matrixB); + } + + [Benchmark] + public void MultiplyParallel_300x300_4TH() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplyParallel(matrixA, matrixB, 4); + } + [Benchmark] + public void MultiplyParallel_300x300_8TH() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplyParallel(matrixA, matrixB, 8); + } + [Benchmark] + public void MultiplyParallel_300x300_16TH() + { + int[][] matrixA = GenerateRandomMatrix(300, 300); + int[][] matrixB = GenerateRandomMatrix(300, 300); + MultiplyParallel(matrixA, matrixB, 16); + } + [Benchmark] + public void MultiplySequential_500x500() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplySequential(matrixA, matrixB); + } + + [Benchmark] + public void MultiplyParallel_500x500_4TH() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplyParallel(matrixA, matrixB, 4); + } + [Benchmark] + public void MultiplyParallel_500x500_8TH() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplyParallel(matrixA, matrixB, 8); + } + [Benchmark] + public void MultiplyParallel_500x500_16TH() + { + int[][] matrixA = GenerateRandomMatrix(500, 500); + int[][] matrixB = GenerateRandomMatrix(500, 500); + MultiplyParallel(matrixA, matrixB, 16); + } +``` + +- Запуск приложения: +``` + static void Main(string[] args) + { + var summary = BenchmarkRunner.Run(); + Console.ReadLine(); + } +``` + +## Результаты работы приложения + +![](shot1.PNG) + +По результатам работы: для матриц небольших размеров большое количество потоков не ускоряет (а в некоторых случаях замедляет) работу алгоритма, за счет излишнего переключения процессора. Для больших матриц увеличение количества потоков увеличивает скорость работы алгоритма. В сравнении с однопоточным алгоритмом, работа параллельного в несколько раз быстрее. \ No newline at end of file diff --git a/tasks/khalitova-am/lab_5/shot1.PNG b/tasks/khalitova-am/lab_5/shot1.PNG new file mode 100644 index 0000000..a0465de Binary files /dev/null and b/tasks/khalitova-am/lab_5/shot1.PNG differ