+
+
++
+
++
+
++
+
++
+
+
+Вывод: Параллельный алгоритм в условии данной задачи не имеет смысла использовать
+
+
+# Видео
+
+Видео с разбором лабораторной - https://drive.google.com/file/d/1Y-dOFRhrAD9epoUAQGOWEEsSCeHMMpIy/view?usp=sharing
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diff --git a/kamyshov_danila_lab_6/src/main/java/org/example/MatrixDeterminant.java b/kamyshov_danila_lab_6/src/main/java/org/example/MatrixDeterminant.java
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+++ b/kamyshov_danila_lab_6/src/main/java/org/example/MatrixDeterminant.java
@@ -0,0 +1,104 @@
+package org.example;
+
+import org.apache.commons.math3.linear.LUDecomposition;
+import org.apache.commons.math3.linear.MatrixUtils;
+import org.apache.commons.math3.linear.RealMatrix;
+
+import java.util.Scanner;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+
+public class MatrixDeterminant {
+
+ static double[][] generateRandomSquareMatrix(int size) {
+ double[][] matrix = new double[size][size];
+ for (int i = 0; i < size; i++) {
+ for (int j = 0; j < size; j++) {
+ matrix[i][j] = Math.random() * 10;
+ }
+ }
+ return matrix;
+ }
+
+ static double sequentialMatrixDeterminant(double[][] matrix) {
+ RealMatrix realMatrix = MatrixUtils.createRealMatrix(matrix);
+ LUDecomposition luDecomposition = new LUDecomposition(realMatrix);
+ return luDecomposition.getDeterminant();
+ }
+
+ static double[] parallelMatrixDeterminant(double[][] matrix, int numThreads) {
+ int rows = matrix.length;
+ int cols = matrix[0].length;
+ int chunkSize = rows / numThreads;
+
+ double[] determinants = new double[numThreads];
+
+ class CalculateDeterminantTask implements Runnable {
+ private final int startRow;
+ private final int endRow;
+ private final double[][] submatrix;
+
+ CalculateDeterminantTask(int startRow, int endRow, double[][] submatrix) {
+ this.startRow = startRow;
+ this.endRow = endRow;
+ this.submatrix = submatrix;
+ }
+
+ @Override
+ public void run() {
+ RealMatrix realSubmatrix = MatrixUtils.createRealMatrix(submatrix);
+ LUDecomposition luDecomposition = new LUDecomposition(realSubmatrix);
+ determinants[startRow / chunkSize] = luDecomposition.getDeterminant();
+ }
+ }
+
+ ExecutorService executorService = Executors.newFixedThreadPool(numThreads);
+
+ for (int i = 0; i < numThreads; i++) {
+ int startRow = i * chunkSize;
+ int endRow = (i + 1) * chunkSize;
+ double[][] submatrix = new double[chunkSize][cols];
+ System.arraycopy(matrix, startRow, submatrix, 0, chunkSize);
+ executorService.submit(new CalculateDeterminantTask(startRow, endRow, submatrix));
+ }
+
+ executorService.shutdown();
+
+ while (!executorService.isTerminated()) {
+ // Ждем, пока все потоки завершат работу
+ }
+
+ return determinants;
+ }
+
+ static void benchmark(int matrixSize, int numThreads) {
+ double[][] matrix = generateRandomSquareMatrix(matrixSize);
+
+ long startTime = System.currentTimeMillis();
+ double sequentialResult = sequentialMatrixDeterminant(matrix);
+ long sequentialTime = System.currentTimeMillis() - startTime;
+
+ startTime = System.currentTimeMillis();
+ double[] parallelResult = parallelMatrixDeterminant(matrix, numThreads);
+ long parallelTime = System.currentTimeMillis() - startTime;
+
+ System.out.println("Matrix size: " + matrixSize + "x" + matrixSize);
+ System.out.println("Sequential algorithm time: " + sequentialTime + " milliseconds");
+ System.out.println("Parallel algorithm time (" + numThreads + " threads): " + parallelTime + " milliseconds");
+ System.out.println("==============================");
+ }
+
+ public static void main(String[] args) {
+ int[] matrixSizes = {100, 300, 500};
+ Scanner scanner = new Scanner(System.in);
+
+ System.out.print("Введите количество потоков: ");
+ int numThreads = scanner.nextInt();
+
+ for (int size : matrixSizes) {
+ benchmark(size, numThreads);
+ }
+
+ scanner.close();
+ }
+}