forked from Alexey/DAS_2024_1
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kuzarin_maxim_lab_5/.gitignore
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kuzarin_maxim_lab_5/.gitignore
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BIN
kuzarin_maxim_lab_5/Images/Resouts.png
Normal file
BIN
kuzarin_maxim_lab_5/Images/Resouts.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 31 KiB |
25
kuzarin_maxim_lab_5/MatrixMultiplication.sln
Normal file
25
kuzarin_maxim_lab_5/MatrixMultiplication.sln
Normal file
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||||
|
||||
Microsoft Visual Studio Solution File, Format Version 12.00
|
||||
# Visual Studio Version 17
|
||||
VisualStudioVersion = 17.10.34916.146
|
||||
MinimumVisualStudioVersion = 10.0.40219.1
|
||||
Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "MatrixMultiplication", "MatrixMultiplication\MatrixMultiplication.csproj", "{EF2DB216-9BCD-4FEE-B9C8-4262A5B7CC30}"
|
||||
EndProject
|
||||
Global
|
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
|
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Debug|Any CPU = Debug|Any CPU
|
||||
Release|Any CPU = Release|Any CPU
|
||||
EndGlobalSection
|
||||
GlobalSection(ProjectConfigurationPlatforms) = postSolution
|
||||
{EF2DB216-9BCD-4FEE-B9C8-4262A5B7CC30}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
||||
{EF2DB216-9BCD-4FEE-B9C8-4262A5B7CC30}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
||||
{EF2DB216-9BCD-4FEE-B9C8-4262A5B7CC30}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
||||
{EF2DB216-9BCD-4FEE-B9C8-4262A5B7CC30}.Release|Any CPU.Build.0 = Release|Any CPU
|
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|
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|
||||
HideSolutionNode = FALSE
|
||||
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|
||||
GlobalSection(ExtensibilityGlobals) = postSolution
|
||||
SolutionGuid = {619485C2-FE35-496B-9E25-4F5465D0C1A1}
|
||||
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|
||||
EndGlobal
|
||||
@ -0,0 +1,10 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFramework>net8.0</TargetFramework>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
</PropertyGroup>
|
||||
|
||||
</Project>
|
||||
117
kuzarin_maxim_lab_5/MatrixMultiplication/Program.cs
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117
kuzarin_maxim_lab_5/MatrixMultiplication/Program.cs
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||||
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||||
using System.Diagnostics;
|
||||
internal class Program
|
||||
{
|
||||
private static string[] _resTableColumnsNames = new string[] { "m*m", "1 t", "2 t", "3 t", "4 t", "5 t", "6 t", "7 t", "8 t" };
|
||||
|
||||
private static void Main(string[] args)
|
||||
{
|
||||
Console.WriteLine(string.Join("\t", _resTableColumnsNames));
|
||||
|
||||
for (int i = 10; i < 10000; i *= 2)
|
||||
{
|
||||
var a = CreateMatrix(i, i);
|
||||
var b = CreateMatrix(i, i);
|
||||
|
||||
List<long> times = new() { i };
|
||||
|
||||
for (int j = 1; j <= 8; j++)
|
||||
{
|
||||
var sw = new Stopwatch();
|
||||
sw.Start();
|
||||
|
||||
MultiplyMatrix(a, b, j);
|
||||
|
||||
sw.Stop();
|
||||
times.Add(sw.ElapsedMilliseconds);
|
||||
}
|
||||
Console.WriteLine(string.Join("\t", times));
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Создаём матрицу случайных элементов
|
||||
/// </summary>
|
||||
/// <param name="x"></param>
|
||||
/// <param name="y"></param>
|
||||
/// <returns></returns>
|
||||
private static int[,] CreateMatrix(int x, int y)
|
||||
{
|
||||
var rnd = new Random();
|
||||
|
||||
var res = new int[y, x];
|
||||
|
||||
for (int i = 0; i < y; i++)
|
||||
{
|
||||
for (int j = 0; j < x; j++)
|
||||
{
|
||||
res[i, j] = rnd.Next(0, 100);
|
||||
}
|
||||
}
|
||||
return res;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Вывести матрицу. Использовался при отладке
|
||||
/// </summary>
|
||||
/// <param name="mx"></param>
|
||||
private static void PrintMatrix(int[,] mx)
|
||||
{
|
||||
for (int i = 0; i < mx.GetLength(0); i++)
|
||||
{
|
||||
for (int j = 0; j < mx.GetLength(1); j++)
|
||||
{
|
||||
Console.Write($"{mx[i, j].ToString("000")}\t");
|
||||
}
|
||||
Console.WriteLine();
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Непосредственно умножение матриц
|
||||
/// </summary>
|
||||
/// <param name="a"></param>
|
||||
/// <param name="b"></param>
|
||||
/// <param name="maxTask"></param>
|
||||
/// <returns></returns>
|
||||
private static int[,] MultiplyMatrix(int[,] a, int[,] b, int maxTask)
|
||||
{
|
||||
int[,] res = new int[a.GetLength(0), b.GetLength(1)];
|
||||
|
||||
var semaphore = new SemaphoreSlim(maxTask, maxTask);
|
||||
|
||||
for (int i = 0; i < a.GetLength(0); i++)
|
||||
{
|
||||
for (int j = 0; j < b.GetLength(1); j++)
|
||||
{
|
||||
semaphore.Wait();
|
||||
int ci = i;
|
||||
int cj = j;
|
||||
_ = Task.Run(() =>
|
||||
{
|
||||
try
|
||||
{
|
||||
res[ci, cj] = CalculateElement(a, b, ci, cj);
|
||||
}
|
||||
finally
|
||||
{
|
||||
semaphore.Release();
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
semaphore.Wait(maxTask);
|
||||
return res;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Вычисление значение одного элемента
|
||||
/// </summary>
|
||||
/// <param name="a"></param>
|
||||
/// <param name="b"></param>
|
||||
/// <param name="i"></param>
|
||||
/// <param name="j"></param>
|
||||
/// <returns></returns>
|
||||
private static int CalculateElement(int[,] a, int[,] b, int i, int j)
|
||||
=> Enumerable.Range(0, a.GetLength(1)).Sum(k => a[i, k] * b[k, j]);
|
||||
}
|
||||
20
kuzarin_maxim_lab_5/README.md
Normal file
20
kuzarin_maxim_lab_5/README.md
Normal file
@ -0,0 +1,20 @@
|
||||
# Лабораторная работа 5
|
||||
Данная работа посвящена параллельному умножению больших матриц (чтобы это был побыстрее)
|
||||
## Описание
|
||||
Основной принцип умножения матриц: строки умножаются на столбцы, таким образом получаются элементы. И так как значения в строках/столбцах не меняется по ходу алгоритма, его достаточно легко можно распаралелить.
|
||||
|
||||
## Запуск
|
||||
Приложение представлет собой консольную программу на C#, которую можно скомпилировать и затем запустит exe файл. В результате в окне консоли появится таблица сравнения времени умножения 2-х квадратных матриц (размер указан в первой колонке) с использованием разного числа потоков(от 1 до 8). Чем больше размер, тем дольше будет идти расчёт.
|
||||
## Результаты
|
||||
Результаты одного из запусков программы представлены ниже.
|
||||
<br/>
|
||||
|
||||
<br/>
|
||||
Как можно заметить, на небольших размерах распаралеливание не приносит никакого выигрыша, а иногда даже удлиняет время работы. Это связана с тем, что работы с потоками (запуск, получение результата и т. п.) - требует дополнительного времени, а из-за малого числа операций в целом, получаем не прирост производительности, а её падение.
|
||||
Противоположно обстоят дела в случае с большими матрицами. Так как там расчётов значительно больше, распаралеливание начинает значительно ускорять вычисление результата. Причём, часто можно видеть, что, например, увеличения числа потоков с 1 до 2 (в 2 раза) сокращает время в 2 раза. Но чем больше потоков, тем прирост меньше (так как вновь вступают в силу факторы, описанные ранее). И прирост производительности пусть и есть, но он очень небольшой.
|
||||
|
||||
## Видеодемонстрация
|
||||
Был записан видеоролик, демонстрирующий процесс запуска и работы системы. Он расположен по [адресу](https://drive.google.com/file/d/1dhA3JUAhhpDUh32xVW7jMuW1BKDX02eV/view?usp=sharing)
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user