74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
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import numpy as np
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import time
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import multiprocessing
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import concurrent.futures
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def multiply_matrices_sequential(matrix_a, matrix_b):
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if len(matrix_a[0]) != len(matrix_b):
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raise ValueError("матрицы имеют разную длину")
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result = [[0 for _ in range(len(matrix_b[0]))] for _ in range(len(matrix_a))]
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for i in range(len(matrix_a)):
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for j in range(len(matrix_b[0])):
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for k in range(len(matrix_b)):
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result[i][j] += matrix_a[i][k] * matrix_b[k][j]
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return result
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def multiply_row(args):
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matrix_a, matrix_b, i = args
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row_result = [0 for _ in range(len(matrix_b[0]))]
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for j in range(len(matrix_b[0])):
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for k in range(len(matrix_b)):
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row_result[j] += matrix_a[i][k] * matrix_b[k][j]
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return row_result, i
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def multiply_matrices_parallel(matrix_a, matrix_b, threads):
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if len(matrix_a[0]) != len(matrix_b):
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raise ValueError("матрицы имеют разную длину")
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result = [[0 for _ in range(len(matrix_b[0]))] for _ in range(len(matrix_a))]
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with multiprocessing.Pool(processes=threads) as pool:
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args_list = [(matrix_a, matrix_b, i) for i in range(len(matrix_a))]
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rows_results = pool.map(multiply_row, args_list)
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for row_result, row_index in rows_results:
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result[row_index] = row_result
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return result
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# Бенчмарк тесты
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def benchmark(matrix_size, num_threads):
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A = np.random.rand(matrix_size, matrix_size)
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B = np.random.rand(matrix_size, matrix_size)
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# Последовательное умножение
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start_time = time.time()
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multiply_matrices_sequential(A, B)
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sequential_time = time.time() - start_time
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# Параллельное умножение
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start_time = time.time()
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multiply_matrices_parallel(A, B, num_threads)
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parallel_time = time.time() - start_time
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print(f"Размер матрицы: {matrix_size}x{matrix_size}")
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print(f"Время последовательного алгоритма: {sequential_time:.4f} секунд")
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print(f"Время параллельного алгоритма ({num_threads} потоков): {parallel_time:.4f} секунд")
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print("\n")
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if __name__ == '__main__':
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# Проведение бенчмарков
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sizes = [100, 300, 500]
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for size in sizes:
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benchmark(size, num_threads=1) # 1 поток для проверки равенства результатов
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benchmark(size, num_threads=4) # 4 потока
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