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using System;
using System.Diagnostics;
using System.Threading.Tasks;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
public class MatrixDeterminant
{
public static double DeterminantSequential(double[][] matrix)
{
int size = matrix.Length;
if (size == 1)
{
return matrix[0][0];
}
if (size == 2)
{
return matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0];
}
double determinant = 0;
for (int i = 0; i < size; i++)
{
double sign = (i % 2 == 0) ? 1 : -1;
double cofactor = sign * matrix[0][i] * DeterminantSequential(GetSubMatrix(matrix, 0, i));
determinant += cofactor;
}
return determinant;
}
public static double DeterminantParallel(double[][] matrix, int numThreads)
{
int size = matrix.Length;
if (size == 1)
{
return matrix[0][0];
}
if (size == 2)
{
return matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0];
}
double determinant = 0;
Parallel.For(0, size, new ParallelOptions { MaxDegreeOfParallelism = numThreads }, i =>
{
double sign = (i % 2 == 0) ? 1 : -1;
double cofactor = sign * matrix[0][i] * DeterminantSequential(GetSubMatrix(matrix, 0, i));
determinant += cofactor;
});
return determinant;
}
[Benchmark]
public void DeterminantSequential_2x2()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantSequential(matrix);
}
[Benchmark]
public void DeterminantParallel_2x2_4TH()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantParallel(matrix, 4);
}
[Benchmark]
public void DeterminantParallel_2x2_8TH()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantParallel(matrix, 8);
}
[Benchmark]
public void DeterminantParallel_2x2_16TH()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantParallel(matrix, 16);
}
[Benchmark]
public void DeterminantSequential_4x4()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantSequential(matrix);
}
[Benchmark]
public void DeterminantParallel_4x4_4TH()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantParallel(matrix, 4);
}
[Benchmark]
public void DeterminantParallel_4x4_8TH()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantParallel(matrix, 8);
}
[Benchmark]
public void DeterminantParallel_4x4_16TH()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantParallel(matrix, 16);
}
[Benchmark]
public void DeterminantSequential_8x8()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantSequential(matrix);
}
[Benchmark]
public void DeterminantParallel_8x8_4TH()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantParallel(matrix, 4);
}
[Benchmark]
public void DeterminantParallel_8x8_8TH()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantParallel(matrix, 8);
}
[Benchmark]
public void DeterminantParallel_8x8_16TH()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantParallel(matrix, 16);
}
public static double[][] GenerateRandomMatrix(int rows, int cols)
{
double[][] matrix = new double[rows][];
Random rand = new Random();
for (int i = 0; i < rows; i++)
{
matrix[i] = new double[cols];
for (int j = 0; j < cols; j++)
{
matrix[i][j] = rand.Next(1, 10);
}
}
return matrix;
}
private static double[][] GetSubMatrix(double[][] matrix, int rowToRemove, int colToRemove)
{
int size = matrix.Length;
double[][] subMatrix = new double[size - 1][];
for (int i = 0, newRow = 0; i < size; i++)
{
if (i != rowToRemove)
{
subMatrix[newRow] = new double[size - 1];
for (int j = 0, newCol = 0; j < size; j++)
{
if (j != colToRemove)
{
subMatrix[newRow][newCol] = matrix[i][j];
newCol++;
}
}
newRow++;
}
}
return subMatrix;
}
}
class Program
{
static void Main(string[] args)
{
var summary = BenchmarkRunner.Run<MatrixDeterminant>();
Console.ReadLine();
}
}

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# Отчёт по лабораторной работе №6
Выполнила: студентка гр. ИСЭбд-41 Халитова А.М.
## Создание приложения
В приложении были созданы следующие методы:
- Заполнение матрицы рандомными значениями:
```
public static double[][] GenerateRandomMatrix(int rows, int cols)
{
double[][] matrix = new double[rows][];
Random rand = new Random();
for (int i = 0; i < rows; i++)
{
matrix[i] = new double[cols];
for (int j = 0; j < cols; j++)
{
matrix[i][j] = rand.Next(1, 10);
}
}
return matrix;
}
```
- Метод создания подматрицы для удаления строки и столбца в вычислении определителя:
```
private static double[][] GetSubMatrix(double[][] matrix, int rowToRemove, int colToRemove)
{
int size = matrix.Length;
double[][] subMatrix = new double[size - 1][];
for (int i = 0, newRow = 0; i < size; i++)
{
if (i != rowToRemove)
{
subMatrix[newRow] = new double[size - 1];
for (int j = 0, newCol = 0; j < size; j++)
{
if (j != colToRemove)
{
subMatrix[newRow][newCol] = matrix[i][j];
newCol++;
}
}
newRow++;
}
}
return subMatrix;
}
```
- Метод вычисления детерминанта обычным алгоритмом:
```
public static double DeterminantSequential(double[][] matrix)
{
int size = matrix.Length;
if (size == 1)
{
return matrix[0][0];
}
if (size == 2)
{
return matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0];
}
double determinant = 0;
for (int i = 0; i < size; i++)
{
double sign = (i % 2 == 0) ? 1 : -1;
double cofactor = sign * matrix[0][i] * DeterminantSequential(GetSubMatrix(matrix, 0, i));
determinant += cofactor;
}
return determinant;
}
```
- Метод вычисления детерминанта параллельным алгоритмом:
```
public static double DeterminantParallel(double[][] matrix, int numThreads)
{
int size = matrix.Length;
if (size == 1)
{
return matrix[0][0];
}
if (size == 2)
{
return matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0];
}
double determinant = 0;
Parallel.For(0, size, new ParallelOptions { MaxDegreeOfParallelism = numThreads }, i =>
{
double sign = (i % 2 == 0) ? 1 : -1;
double cofactor = sign * matrix[0][i] * DeterminantSequential(GetSubMatrix(matrix, 0, i));
determinant += cofactor;
});
return determinant;
}
```
- Методы генерации матриц различных размеров и с различным числом потоков. Поскольку ресурсы машины не позволяют вычислить детерминанту для больших матриц (процесс занимает большое количество времени и памяти, происходит зависание), вычислять будем для матриц меньших размеров (2, 4, 8):
```
[Benchmark]
public void DeterminantSequential_2x2()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantSequential(matrix);
}
[Benchmark]
public void DeterminantParallel_2x2_4TH()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantParallel(matrix, 4);
}
[Benchmark]
public void DeterminantParallel_2x2_8TH()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantParallel(matrix, 8);
}
[Benchmark]
public void DeterminantParallel_2x2_16TH()
{
double[][] matrix = GenerateRandomMatrix(2, 2);
DeterminantParallel(matrix, 16);
}
[Benchmark]
public void DeterminantSequential_4x4()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantSequential(matrix);
}
[Benchmark]
public void DeterminantParallel_4x4_4TH()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantParallel(matrix, 4);
}
[Benchmark]
public void DeterminantParallel_4x4_8TH()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantParallel(matrix, 8);
}
[Benchmark]
public void DeterminantParallel_4x4_16TH()
{
double[][] matrix = GenerateRandomMatrix(4, 4);
DeterminantParallel(matrix, 16);
}
[Benchmark]
public void DeterminantSequential_8x8()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantSequential(matrix);
}
[Benchmark]
public void DeterminantParallel_8x8_4TH()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantParallel(matrix, 4);
}
[Benchmark]
public void DeterminantParallel_8x8_8TH()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantParallel(matrix, 8);
}
[Benchmark]
public void DeterminantParallel_8x8_16TH()
{
double[][] matrix = GenerateRandomMatrix(8, 8);
DeterminantParallel(matrix, 16);
}
```
Запуск приложения происходит с помощью строки `var summary = BenchmarkRunner.Run<MatrixDeterminant>();`.
## Результаты работы приложения
![](shot.PNG)
Вывод: по результатам работы, для малых матриц парралельный алгоритм не дает прироста в скорости работы. Для матрицы 8 на 8 дает прирост только распараллеливание на малое число потоков. Для вычисления детерминанта больших матриц (больше, чем 8 на 8) не хватает вычислительной мощности моего процессора, но можно предположить что в этом случае увеличение числа потоков приводило бы к увеличению скорости работы.

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