belyaeva_ekaterina_lab_5 #115
29
belyaeva_ekaterina_lab_5/.gitignore
vendored
Normal file
29
belyaeva_ekaterina_lab_5/.gitignore
vendored
Normal file
@ -0,0 +1,29 @@
|
|||||||
|
### IntelliJ IDEA ###
|
||||||
|
out/
|
||||||
|
!**/src/main/**/out/
|
||||||
|
!**/src/test/**/out/
|
||||||
|
|
||||||
|
### Eclipse ###
|
||||||
|
.apt_generated
|
||||||
|
.classpath
|
||||||
|
.factorypath
|
||||||
|
.project
|
||||||
|
.settings
|
||||||
|
.springBeans
|
||||||
|
.sts4-cache
|
||||||
|
bin/
|
||||||
|
!**/src/main/**/bin/
|
||||||
|
!**/src/test/**/bin/
|
||||||
|
|
||||||
|
### NetBeans ###
|
||||||
|
/nbproject/private/
|
||||||
|
/nbbuild/
|
||||||
|
/dist/
|
||||||
|
/nbdist/
|
||||||
|
/.nb-gradle/
|
||||||
|
|
||||||
|
### VS Code ###
|
||||||
|
.vscode/
|
||||||
|
|
||||||
|
### Mac OS ###
|
||||||
|
.DS_Store
|
98
belyaeva_ekaterina_lab_5/README.md
Normal file
98
belyaeva_ekaterina_lab_5/README.md
Normal file
@ -0,0 +1,98 @@
|
|||||||
|
# Лабораторная работа №5
|
||||||
|
|
||||||
|
## Задание
|
||||||
|
|
||||||
|
Кратко: реализовать умножение двух больших квадратных матриц.
|
||||||
|
|
||||||
|
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.
|
||||||
|
|
||||||
|
## Ход работы
|
||||||
|
|
||||||
|
### Последовательный алгоритм
|
||||||
|
```
|
||||||
|
public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[i][j] += matrix1[i][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
```
|
||||||
|
### Параллельный алгоритм
|
||||||
|
```
|
||||||
|
public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
int numberOfThreads = 5; // Количество потоков
|
||||||
|
ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
final int row = i;
|
||||||
|
executor.execute(new Runnable() {
|
||||||
|
@Override
|
||||||
|
public void run() {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[row][j] += matrix1[row][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
executor.shutdown();
|
||||||
|
while (!executor.isTerminated()) {
|
||||||
|
// Ожидаем завершения всех потоков
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Результат
|
||||||
|
|
||||||
|
Была проверка времени выполнения алгоритма для матриц размером 100х100, 300х300, 500х500 с разным количеством потоков.
|
||||||
|
|
||||||
|
100х100, 1 поток
|
||||||
|
|
||||||
|
![100thr1.png](screenshots%2F100thr1.png)
|
||||||
|
|
||||||
|
100х100, 5 потоков
|
||||||
|
|
||||||
|
![100thr5.png](screenshots%2F100thr5.png)
|
||||||
|
|
||||||
|
300х300, 1 поток
|
||||||
|
|
||||||
|
![300thr1.png](screenshots%2F300thr1.png)
|
||||||
|
|
||||||
|
300х300, 5 потоков
|
||||||
|
|
||||||
|
![300thr5.png](screenshots%2F300thr5.png)
|
||||||
|
|
||||||
|
500х500, 1 поток
|
||||||
|
|
||||||
|
![500th1.png](screenshots%2F500th1.png)
|
||||||
|
|
||||||
|
500х500, 5 потоков
|
||||||
|
|
||||||
|
![500thr5.png](screenshots%2F500thr5.png)
|
||||||
|
|
||||||
|
Из данных скриншотов видно, что в случае с матрицей 100х100 последовательный алгоритм работает лучше, чем параллельный.
|
||||||
|
|
||||||
|
Для остальных матриц параллельный алгоритм работает лучше, а также увеличение кол-ва потоков уменьшает время выполнения алгоритма. (хотя в случае матрицы 100х100 - сильно увеличивает)
|
||||||
|
|
||||||
|
Работоспособность показана в видео: [lab5.mp4](lab5.mp4)
|
BIN
belyaeva_ekaterina_lab_5/lab5.mp4
Normal file
BIN
belyaeva_ekaterina_lab_5/lab5.mp4
Normal file
Binary file not shown.
BIN
belyaeva_ekaterina_lab_5/screenshots/100thr1.png
Normal file
BIN
belyaeva_ekaterina_lab_5/screenshots/100thr1.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 16 KiB |
BIN
belyaeva_ekaterina_lab_5/screenshots/100thr5.png
Normal file
BIN
belyaeva_ekaterina_lab_5/screenshots/100thr5.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 16 KiB |
BIN
belyaeva_ekaterina_lab_5/screenshots/300thr1.png
Normal file
BIN
belyaeva_ekaterina_lab_5/screenshots/300thr1.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 19 KiB |
BIN
belyaeva_ekaterina_lab_5/screenshots/300thr5.png
Normal file
BIN
belyaeva_ekaterina_lab_5/screenshots/300thr5.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 17 KiB |
BIN
belyaeva_ekaterina_lab_5/screenshots/500th1.png
Normal file
BIN
belyaeva_ekaterina_lab_5/screenshots/500th1.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 19 KiB |
BIN
belyaeva_ekaterina_lab_5/screenshots/500thr5.png
Normal file
BIN
belyaeva_ekaterina_lab_5/screenshots/500thr5.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 20 KiB |
84
belyaeva_ekaterina_lab_5/src/Matrix100x100.java
Normal file
84
belyaeva_ekaterina_lab_5/src/Matrix100x100.java
Normal file
@ -0,0 +1,84 @@
|
|||||||
|
import java.util.concurrent.ExecutorService;
|
||||||
|
import java.util.concurrent.Executors;
|
||||||
|
|
||||||
|
public class Matrix100x100 {
|
||||||
|
private static final int SIZE = 100;
|
||||||
|
|
||||||
|
public static void main(String[] args) {
|
||||||
|
int[][] matrix1 = generateMatrix(SIZE, SIZE);
|
||||||
|
int[][] matrix2 = generateMatrix(SIZE, SIZE);
|
||||||
|
|
||||||
|
long startTime = System.currentTimeMillis();
|
||||||
|
int[][] resultSequential = multiplyMatricesSequential(matrix1, matrix2);
|
||||||
|
long endTime = System.currentTimeMillis();
|
||||||
|
long sequentialTime = endTime - startTime;
|
||||||
|
|
||||||
|
startTime = System.currentTimeMillis();
|
||||||
|
int[][] resultParallel = multiplyMatricesParallel(matrix1, matrix2);
|
||||||
|
endTime = System.currentTimeMillis();
|
||||||
|
long parallelTime = endTime - startTime;
|
||||||
|
|
||||||
|
System.out.println("Sequential multiplication time: " + sequentialTime + " ms");
|
||||||
|
System.out.println("Parallel multiplication time: " + parallelTime + " ms");
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[i][j] += matrix1[i][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
int numberOfThreads = 5; // Количество потоков
|
||||||
|
ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
final int row = i;
|
||||||
|
executor.execute(new Runnable() {
|
||||||
|
@Override
|
||||||
|
public void run() {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[row][j] += matrix1[row][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
executor.shutdown();
|
||||||
|
while (!executor.isTerminated()) {
|
||||||
|
// Ожидаем завершения всех потоков
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] generateMatrix(int rows, int columns) {
|
||||||
|
int[][] matrix = new int[rows][columns];
|
||||||
|
for (int i = 0; i < rows; i++) {
|
||||||
|
for (int j = 0; j < columns; j++) {
|
||||||
|
matrix[i][j] = (int) (Math.random() * 10);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return matrix;
|
||||||
|
}
|
||||||
|
}
|
84
belyaeva_ekaterina_lab_5/src/Matrix300x300.java
Normal file
84
belyaeva_ekaterina_lab_5/src/Matrix300x300.java
Normal file
@ -0,0 +1,84 @@
|
|||||||
|
import java.util.concurrent.ExecutorService;
|
||||||
|
import java.util.concurrent.Executors;
|
||||||
|
|
||||||
|
public class Matrix300x300 {
|
||||||
|
private static final int SIZE = 300;
|
||||||
|
|
||||||
|
public static void main(String[] args) {
|
||||||
|
int[][] matrix1 = generateMatrix(SIZE, SIZE);
|
||||||
|
int[][] matrix2 = generateMatrix(SIZE, SIZE);
|
||||||
|
|
||||||
|
long startTime = System.currentTimeMillis();
|
||||||
|
int[][] resultSequential = multiplyMatricesSequential(matrix1, matrix2);
|
||||||
|
long endTime = System.currentTimeMillis();
|
||||||
|
long sequentialTime = endTime - startTime;
|
||||||
|
|
||||||
|
startTime = System.currentTimeMillis();
|
||||||
|
int[][] resultParallel = multiplyMatricesParallel(matrix1, matrix2);
|
||||||
|
endTime = System.currentTimeMillis();
|
||||||
|
long parallelTime = endTime - startTime;
|
||||||
|
|
||||||
|
System.out.println("Sequential multiplication time: " + sequentialTime + " ms");
|
||||||
|
System.out.println("Parallel multiplication time: " + parallelTime + " ms");
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[i][j] += matrix1[i][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
int numberOfThreads = 5; // Количество потоков
|
||||||
|
ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
final int row = i;
|
||||||
|
executor.execute(new Runnable() {
|
||||||
|
@Override
|
||||||
|
public void run() {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[row][j] += matrix1[row][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
executor.shutdown();
|
||||||
|
while (!executor.isTerminated()) {
|
||||||
|
// Ожидаем завершения всех потоков
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] generateMatrix(int rows, int columns) {
|
||||||
|
int[][] matrix = new int[rows][columns];
|
||||||
|
for (int i = 0; i < rows; i++) {
|
||||||
|
for (int j = 0; j < columns; j++) {
|
||||||
|
matrix[i][j] = (int) (Math.random() * 10);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return matrix;
|
||||||
|
}
|
||||||
|
}
|
84
belyaeva_ekaterina_lab_5/src/Matrix500x500.java
Normal file
84
belyaeva_ekaterina_lab_5/src/Matrix500x500.java
Normal file
@ -0,0 +1,84 @@
|
|||||||
|
import java.util.concurrent.ExecutorService;
|
||||||
|
import java.util.concurrent.Executors;
|
||||||
|
|
||||||
|
public class Matrix500x500 {
|
||||||
|
private static final int SIZE = 500;
|
||||||
|
|
||||||
|
public static void main(String[] args) {
|
||||||
|
int[][] matrix1 = generateMatrix(SIZE, SIZE);
|
||||||
|
int[][] matrix2 = generateMatrix(SIZE, SIZE);
|
||||||
|
|
||||||
|
long startTime = System.currentTimeMillis();
|
||||||
|
int[][] resultSequential = multiplyMatricesSequential(matrix1, matrix2);
|
||||||
|
long endTime = System.currentTimeMillis();
|
||||||
|
long sequentialTime = endTime - startTime;
|
||||||
|
|
||||||
|
startTime = System.currentTimeMillis();
|
||||||
|
int[][] resultParallel = multiplyMatricesParallel(matrix1, matrix2);
|
||||||
|
endTime = System.currentTimeMillis();
|
||||||
|
long parallelTime = endTime - startTime;
|
||||||
|
|
||||||
|
System.out.println("Sequential multiplication time: " + sequentialTime + " ms");
|
||||||
|
System.out.println("Parallel multiplication time: " + parallelTime + " ms");
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] multiplyMatricesSequential(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[i][j] += matrix1[i][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] multiplyMatricesParallel(int[][] matrix1, int[][] matrix2) {
|
||||||
|
int rows1 = matrix1.length;
|
||||||
|
int columns1 = matrix1[0].length;
|
||||||
|
int columns2 = matrix2[0].length;
|
||||||
|
|
||||||
|
int[][] result = new int[rows1][columns2];
|
||||||
|
|
||||||
|
int numberOfThreads = 1; // Количество потоков
|
||||||
|
ExecutorService executor = Executors.newFixedThreadPool(numberOfThreads);
|
||||||
|
|
||||||
|
for (int i = 0; i < rows1; i++) {
|
||||||
|
final int row = i;
|
||||||
|
executor.execute(new Runnable() {
|
||||||
|
@Override
|
||||||
|
public void run() {
|
||||||
|
for (int j = 0; j < columns2; j++) {
|
||||||
|
for (int k = 0; k < columns1; k++) {
|
||||||
|
result[row][j] += matrix1[row][k] * matrix2[k][j];
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
executor.shutdown();
|
||||||
|
while (!executor.isTerminated()) {
|
||||||
|
// Ожидаем завершения всех потоков
|
||||||
|
}
|
||||||
|
|
||||||
|
return result;
|
||||||
|
}
|
||||||
|
|
||||||
|
public static int[][] generateMatrix(int rows, int columns) {
|
||||||
|
int[][] matrix = new int[rows][columns];
|
||||||
|
for (int i = 0; i < rows; i++) {
|
||||||
|
for (int j = 0; j < columns; j++) {
|
||||||
|
matrix[i][j] = (int) (Math.random() * 10);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return matrix;
|
||||||
|
}
|
||||||
|
}
|
Loading…
Reference in New Issue
Block a user