60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
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import random
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import time
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import multiprocessing
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import numpy as np
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# Генерация случайной матрицы
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def create_random_matrix(dim):
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return [[random.randint(0, 10) for _ in range(dim)] for _ in range(dim)]
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# Умножение отдельной строки
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def compute_row_product(row_idx, mat_a, mat_b, output_mat):
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dim = len(mat_a)
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for col_idx in range(dim):
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for k in range(dim):
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output_mat[row_idx][col_idx] += mat_a[row_idx][k] * mat_b[k][col_idx]
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# Параллельное умножение матриц
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def parallel_matrix_multiplication(mat_a, mat_b, num_workers):
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dim = len(mat_a)
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result_matrix = [[0] * dim for _ in range(dim)]
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with multiprocessing.Pool(processes=num_workers) as pool:
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pool.starmap(compute_row_product, [(i, mat_a, mat_b, result_matrix) for i in range(dim)])
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return result_matrix
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# Измерение времени выполнения
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def run_benchmark(dim, num_workers=1):
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mat_a = create_random_matrix(dim)
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mat_b = create_random_matrix(dim)
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start_time = time.time()
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parallel_matrix_multiplication(mat_a, mat_b, num_workers)
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elapsed_time = time.time() - start_time
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return elapsed_time
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def main():
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# Размеры матриц
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matrix_dimensions = [100, 300, 500]
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# Количество рабочих процессов
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worker_counts = [1, 2, 4, 6, 8]
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# Печать таблицы с результатами
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print("-*" * 40)
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print(f"{'Количество процессов':<20}{'|100x100 (сек.)':<20}{'|300x300 (сек.)':<20}{'|500x500 (сек.)'}")
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print("-*" * 40)
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for workers in worker_counts:
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row = f"{workers:<20}"
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for dim in matrix_dimensions:
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benchmark_time = run_benchmark(dim, workers)
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row += f"|{benchmark_time:.4f}".ljust(20)
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print(row)
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print("-*" * 40)
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if __name__ == "__main__":
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main()
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