belyaeva lab5 ready
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belyaeva_ekaterina_lab_5/.gitignore
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belyaeva_ekaterina_lab_5/.gitignore
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### IntelliJ IDEA ###
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out/
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!**/src/main/**/out/
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!**/src/test/**/out/
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### Eclipse ###
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.apt_generated
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bin/
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!**/src/main/**/bin/
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!**/src/test/**/bin/
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### NetBeans ###
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belyaeva_ekaterina_lab_5/README.md
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belyaeva_ekaterina_lab_5/README.md
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# Лабораторная работа №5
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## Задание
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Кратко: реализовать умножение двух больших квадратных матриц.
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Подробно: в лабораторной работе требуется сделать два алгоритма: обычный и параллельный. В параллельном алгоритме предусмотреть ручное задание количества потоков, каждый из которых будет выполнять умножение элементов матрицы в рамках своей зоны ответственности.
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## Ход работы
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### Последовательный алгоритм
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```
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public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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for (int i = 0; i < rows1; i++) {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[i][j] += matrix1[i][k] * matrix2[k][j];
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}
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}
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}
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return result;
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}
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```
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### Параллельный алгоритм
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```
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public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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int numberOfThreads = 5; // Количество потоков
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ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
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for (int i = 0; i < rows1; i++) {
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final int row = i;
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executor.execute(new Runnable() {
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@Override
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public void run() {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[row][j] += matrix1[row][k] * matrix2[k][j];
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}
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}
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}
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});
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}
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executor.shutdown();
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while (!executor.isTerminated()) {
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// Ожидаем завершения всех потоков
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}
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return result;
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}
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```
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## Результат
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Была проверка времени выполнения алгоритма для матриц размером 100х100, 300х300, 500х500 с разным количеством потоков.
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100х100, 1 поток
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![100thr1.png](screenshots%2F100thr1.png)
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100х100, 5 потоков
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![100thr5.png](screenshots%2F100thr5.png)
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300х300, 1 поток
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![300thr1.png](screenshots%2F300thr1.png)
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300х300, 5 потоков
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![300thr5.png](screenshots%2F300thr5.png)
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500х500, 1 поток
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![500th1.png](screenshots%2F500th1.png)
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500х500, 5 потоков
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![500thr5.png](screenshots%2F500thr5.png)
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Из данных скриншотов видно, что в случае с матрицей 100х100 последовательный алгоритм работает лучше, чем параллельный.
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Для остальных матриц параллельный алгоритм работает лучше, а также увеличение кол-ва потоков уменьшает время выполнения алгоритма. (хотя в случае матрицы 100х100 - сильно увеличивает)
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Работоспособность показана в видео: [lab5.mp4](lab5.mp4)
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belyaeva_ekaterina_lab_5/lab5.mp4
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belyaeva_ekaterina_lab_5/lab5.mp4
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belyaeva_ekaterina_lab_5/screenshots/100thr1.png
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belyaeva_ekaterina_lab_5/screenshots/100thr1.png
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belyaeva_ekaterina_lab_5/screenshots/100thr5.png
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belyaeva_ekaterina_lab_5/screenshots/100thr5.png
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belyaeva_ekaterina_lab_5/screenshots/300thr1.png
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belyaeva_ekaterina_lab_5/screenshots/300thr1.png
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belyaeva_ekaterina_lab_5/screenshots/300thr5.png
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belyaeva_ekaterina_lab_5/screenshots/300thr5.png
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belyaeva_ekaterina_lab_5/screenshots/500th1.png
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belyaeva_ekaterina_lab_5/screenshots/500th1.png
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belyaeva_ekaterina_lab_5/screenshots/500thr5.png
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belyaeva_ekaterina_lab_5/src/Matrix100x100.java
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belyaeva_ekaterina_lab_5/src/Matrix100x100.java
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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public class Matrix100x100 {
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private static final int SIZE = 100;
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public static void main(String[] args) {
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int[][] matrix1 = generateMatrix(SIZE, SIZE);
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int[][] matrix2 = generateMatrix(SIZE, SIZE);
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long startTime = System.currentTimeMillis();
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int[][] resultSequential = multiplyMatricesSequential(matrix1, matrix2);
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long endTime = System.currentTimeMillis();
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long sequentialTime = endTime - startTime;
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startTime = System.currentTimeMillis();
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int[][] resultParallel = multiplyMatricesParallel(matrix1, matrix2);
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endTime = System.currentTimeMillis();
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long parallelTime = endTime - startTime;
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System.out.println("Sequential multiplication time: " + sequentialTime + " ms");
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System.out.println("Parallel multiplication time: " + parallelTime + " ms");
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}
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public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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for (int i = 0; i < rows1; i++) {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[i][j] += matrix1[i][k] * matrix2[k][j];
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}
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}
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}
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return result;
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}
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public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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int numberOfThreads = 5; // Количество потоков
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ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
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for (int i = 0; i < rows1; i++) {
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final int row = i;
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executor.execute(new Runnable() {
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@Override
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public void run() {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[row][j] += matrix1[row][k] * matrix2[k][j];
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}
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}
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}
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});
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}
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executor.shutdown();
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while (!executor.isTerminated()) {
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// Ожидаем завершения всех потоков
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}
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return result;
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}
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public static int[][] generateMatrix(int rows, int columns) {
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int[][] matrix = new int[rows][columns];
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for (int i = 0; i < rows; i++) {
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for (int j = 0; j < columns; j++) {
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matrix[i][j] = (int) (Math.random() * 10);
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}
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}
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return matrix;
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}
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}
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belyaeva_ekaterina_lab_5/src/Matrix300x300.java
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belyaeva_ekaterina_lab_5/src/Matrix300x300.java
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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public class Matrix300x300 {
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private static final int SIZE = 300;
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public static void main(String[] args) {
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int[][] matrix1 = generateMatrix(SIZE, SIZE);
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int[][] matrix2 = generateMatrix(SIZE, SIZE);
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long startTime = System.currentTimeMillis();
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int[][] resultSequential = multiplyMatricesSequential(matrix1, matrix2);
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long endTime = System.currentTimeMillis();
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long sequentialTime = endTime - startTime;
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startTime = System.currentTimeMillis();
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int[][] resultParallel = multiplyMatricesParallel(matrix1, matrix2);
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endTime = System.currentTimeMillis();
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long parallelTime = endTime - startTime;
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System.out.println("Sequential multiplication time: " + sequentialTime + " ms");
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System.out.println("Parallel multiplication time: " + parallelTime + " ms");
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}
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public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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for (int i = 0; i < rows1; i++) {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[i][j] += matrix1[i][k] * matrix2[k][j];
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}
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}
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}
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return result;
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}
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public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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int numberOfThreads = 5; // Количество потоков
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ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
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for (int i = 0; i < rows1; i++) {
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final int row = i;
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executor.execute(new Runnable() {
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@Override
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public void run() {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[row][j] += matrix1[row][k] * matrix2[k][j];
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}
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}
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}
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});
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}
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executor.shutdown();
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while (!executor.isTerminated()) {
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// Ожидаем завершения всех потоков
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}
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return result;
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}
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public static int[][] generateMatrix(int rows, int columns) {
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int[][] matrix = new int[rows][columns];
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for (int i = 0; i < rows; i++) {
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for (int j = 0; j < columns; j++) {
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matrix[i][j] = (int) (Math.random() * 10);
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}
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}
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return matrix;
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}
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}
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belyaeva_ekaterina_lab_5/src/Matrix500x500.java
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belyaeva_ekaterina_lab_5/src/Matrix500x500.java
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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public class Matrix500x500 {
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private static final int SIZE = 500;
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public static void main(String[] args) {
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int[][] matrix1 = generateMatrix(SIZE, SIZE);
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int[][] matrix2 = generateMatrix(SIZE, SIZE);
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long startTime = System.currentTimeMillis();
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int[][] resultSequential = multiplyMatricesSequential(matrix1, matrix2);
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long endTime = System.currentTimeMillis();
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long sequentialTime = endTime - startTime;
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startTime = System.currentTimeMillis();
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int[][] resultParallel = multiplyMatricesParallel(matrix1, matrix2);
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endTime = System.currentTimeMillis();
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long parallelTime = endTime - startTime;
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System.out.println("Sequential multiplication time: " + sequentialTime + " ms");
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System.out.println("Parallel multiplication time: " + parallelTime + " ms");
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}
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public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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for (int i = 0; i < rows1; i++) {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[i][j] += matrix1[i][k] * matrix2[k][j];
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}
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}
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}
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return result;
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}
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public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
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int rows1 = matrix1.length;
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int columns1 = matrix1[0].length;
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int columns2 = matrix2[0].length;
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int[][] result = new int[rows1][columns2];
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int numberOfThreads = 1; // Количество потоков
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ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
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for (int i = 0; i < rows1; i++) {
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final int row = i;
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executor.execute(new Runnable() {
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@Override
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public void run() {
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for (int j = 0; j < columns2; j++) {
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for (int k = 0; k < columns1; k++) {
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result[row][j] += matrix1[row][k] * matrix2[k][j];
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}
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}
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}
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});
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}
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executor.shutdown();
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while (!executor.isTerminated()) {
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// Ожидаем завершения всех потоков
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}
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return result;
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}
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public static int[][] generateMatrix(int rows, int columns) {
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int[][] matrix = new int[rows][columns];
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for (int i = 0; i < rows; i++) {
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for (int j = 0; j < columns; j++) {
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matrix[i][j] = (int) (Math.random() * 10);
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}
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}
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return matrix;
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}
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}
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