Merge pull request '[Л/Р 5] Савицкий Александр' (#78) from Savitskiy_ISEbd-41/distributed-computing:savitskiy_av_lab5 into main

Reviewed-on: http://student.git.athene.tech/v.moiseev/distributed-computing/pulls/78
This commit is contained in:
Vladislav Moiseev 2023-12-17 23:05:30 +04:00
commit 196d2d2a1b
9 changed files with 716 additions and 0 deletions

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<OutputType>Exe</OutputType>
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using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace ConsoleApp1
{
public class MatrixService
{
static readonly Random rand = new Random();
public int[,] RandomGenerateMatrix(int dimensionsCount)
{
int[,] result = new int[dimensionsCount, dimensionsCount];
for (int i = 0; i < dimensionsCount; i++)
{
for (int j = 0; j < dimensionsCount; j++)
{
result[i, j] = rand.Next(1000);
}
}
return result;
}
public int[,] MultiplicationMatrix(int[,] matrix1, int[,] matrix2, int threadCount)
{
var result = new int[matrix1.GetLength(0), matrix1.GetLength(1)];
for(int i = 0; i < result.GetLength(0); i++)
{
for (int j = 0; j < result.GetLength(1); j++)
{
result[i, j] = 0;
}
}
for (int i = 0; i < matrix1.GetLength(0); i++)
{
Parallel.For(0, matrix2.GetLength(1), new ParallelOptions() { MaxDegreeOfParallelism = threadCount },
(j) =>
{
for (int k = 0; k < matrix2.GetLength(0); k++)
{
var value = matrix1[i, k] * matrix2[k, j];
Interlocked.Add(ref result[i, j], value);
}
});
}
return result;
}
}
}

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// See https://aka.ms/new-console-template for more information
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using ConsoleApp1;
BenchmarkRunner.Run<MatrixTest>();
//var matrixService = new MatrixService();
//var testArr1 = new int[3, 3]
//{
// {5, 1, 6 },
// {-1, 7, 9 },
// {-8, 2, 3 },
//};
//var testArr2 = new int[3, 3]
//{
// {8, 1, 4 },
// {5, -5, 7 },
// {-3, -2, 7 },
//};
//var result = matrixService.MultiplicationMatrix(testArr1, testArr2, 12);
//for(int i = 0; i < result.GetLength(0); i++)
//{
// for (int j = 0; j < result.GetLength(1); j++)
// {
// Console.Write(result[i, j] + " ");
// }
// Console.WriteLine();
//}
[MemoryDiagnoser]
public class MatrixTest
{
int[,] firstMatrix100;
int[,] secondMatrix100;
int[,] firstMatrix300;
int[,] secondMatrix300;
int[,] firstMatrix500;
int[,] secondMatrix500;
MatrixService matrixService;
public MatrixTest()
{
matrixService = new MatrixService();
firstMatrix100 = matrixService.RandomGenerateMatrix(100);
secondMatrix100 = matrixService.RandomGenerateMatrix(100);
firstMatrix300 = matrixService.RandomGenerateMatrix(300);
secondMatrix300 = matrixService.RandomGenerateMatrix(300);
firstMatrix500 = matrixService.RandomGenerateMatrix(500);
secondMatrix500 = matrixService.RandomGenerateMatrix(500);
}
[Benchmark]
public int[,] MultiplicationMatrix100MonoThread()
{
return matrixService.MultiplicationMatrix(firstMatrix100, secondMatrix100, 1);
}
[Benchmark]
public int[,] MultiplicationMatrix100MultiThread()
{
return matrixService.MultiplicationMatrix(firstMatrix100, secondMatrix100, 12);
}
[Benchmark]
public int[,] MultiplicationMatrix300MonoThread()
{
return matrixService.MultiplicationMatrix(firstMatrix300, secondMatrix300, 1);
}
[Benchmark]
public int[,] MultiplicationMatrix300MultiThread()
{
return matrixService.MultiplicationMatrix(firstMatrix300, secondMatrix300, 12);
}
[Benchmark]
public int[,] MultiplicationMatrix500MonoThread()
{
return matrixService.MultiplicationMatrix(firstMatrix500, secondMatrix500, 1);
}
[Benchmark]
public int[,] MultiplicationMatrix500MultiThread()
{
return matrixService.MultiplicationMatrix(firstMatrix500, secondMatrix500, 12);
}
}

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# Отчет по лабораторной работе №5
Выполнил студент гр. ИСЭбд-41 Савицкий А.В.
## Создание приложения
Выбрал язык C#, Консольное приложение.
Проверяю правильность работы алгоритма
```cs
public int[,] MultiplicationMatrix(int[,] matrix1, int[,] matrix2, int threadCount)
{
var result = new int[matrix1.GetLength(0), matrix1.GetLength(1)];
for(int i = 0; i < result.GetLength(0); i++)
{
for (int j = 0; j < result.GetLength(1); j++)
{
result[i, j] = 0;
}
}
for (int i = 0; i < matrix1.GetLength(0); i++)
{
Parallel.For(0, matrix2.GetLength(1), new ParallelOptions() { MaxDegreeOfParallelism = threadCount },
(j) =>
{
for (int k = 0; k < matrix2.GetLength(0); k++)
{
var value = matrix1[i, k] * matrix2[k, j];
Interlocked.Add(ref result[i, j], value);
}
});
}
return result;
}
```
![](pic/1.png)
Установил библиотеку BenchmarkDotNet для замера производительности алгоритма.
## Бенчмарки
Делаю 6 пробных запусков
Матрицы 100х100, 300х300, 500х500
Количество потоков 1,12
![](pic/2.png)
Нас интересуют преимущественно две колонки - Mean и Allocated.
Mean показывает среднее время выполнения бенчмарка
Allocated показывает количество выделенной памяти
Для матриц 100х100 однопоточный алгоритм отработал быстрее чем многопоточный, однако для более больших матриц время выполнения серьезно уменшилось.
Вывод: Параллельный алгоритм работает быстрее чем однопоточный, если мы обрабатываем большие данные. Также многопоточное выполнение занимает больше памяти.

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