94 lines
3.2 KiB
Python
94 lines
3.2 KiB
Python
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import time
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import multiprocessing
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import numpy as np
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def multiply_matrices_sequential(matrix1, matrix2):
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rows1 = len(matrix1)
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cols1 = len(matrix1[0])
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rows2 = len(matrix2)
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cols2 = len(matrix2[0])
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if cols1 != rows2:
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raise ValueError("Число столбцов первой матрицы должно быть равно числу строк второй матрицы.")
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result = [[0 for _ in range(cols2)] for _ in range(rows1)]
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for i in range(rows1):
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for j in range(cols2):
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for k in range(cols1):
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result[i][j] += matrix1[i][k] * matrix2[k][j]
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return result
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def multiply_matrices_parallel(matrix1, matrix2, num_processes):
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rows1 = len(matrix1)
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cols1 = len(matrix1[0])
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rows2 = len(matrix2)
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cols2 = len(matrix2[0])
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if cols1 != rows2:
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raise ValueError("Число столбцов первой матрицы должно быть равно числу строк второй матрицы.")
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chunk_size = rows1 // num_processes
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processes = []
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results = []
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with multiprocessing.Pool(processes=num_processes) as pool:
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for i in range(num_processes):
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start_row = i * chunk_size
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end_row = (i + 1) * chunk_size if i < num_processes - 1 else rows1
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p = pool.apply_async(multiply_matrix_chunk, (matrix1, matrix2, start_row, end_row))
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processes.append(p)
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for p in processes:
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results.append(p.get())
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result = [[0 for _ in range(cols2)] for _ in range(rows1)]
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row_index = 0
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for sub_result in results:
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for row in sub_result:
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result[row_index] = row
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row_index += 1
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return result
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def multiply_matrix_chunk(matrix1, matrix2, start_row, end_row):
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rows2 = len(matrix2)
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cols2 = len(matrix2[0])
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cols1 = len(matrix1[0])
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result = [[0 for _ in range(cols2)] for _ in range(end_row - start_row)]
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for i in range(end_row - start_row):
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for j in range(cols2):
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for k in range(cols1):
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result[i][j] += matrix1[i + start_row][k] * matrix2[k][j]
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return result
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def benchmark(matrix_size, num_processes):
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matrix1 = np.random.rand(matrix_size, matrix_size).tolist()
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matrix2 = np.random.rand(matrix_size, matrix_size).tolist()
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try:
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start_time = time.time()
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sequential_result = multiply_matrices_sequential(matrix1, matrix2)
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end_time = time.time()
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sequential_time = end_time - start_time
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start_time = time.time()
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parallel_result = multiply_matrices_parallel(matrix1, matrix2, num_processes)
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end_time = time.time()
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parallel_time = end_time - start_time
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return sequential_time, parallel_time
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except ValueError as e:
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print(f"Ошибка бенчмарка с размером матрицы {matrix_size} и {num_processes} процессов: {e}")
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return float('inf'), float('inf')
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if __name__ == "__main__":
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sizes = [100, 300, 500]
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num_processes = int(input("Введите количество потоков: "))
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print("Размер | Последовательно | Параллельно")
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for size in sizes:
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sequential_time, parallel_time = benchmark(size, num_processes)
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print(f"{size:6} | {sequential_time:.4f} с \t | {parallel_time:.4f} с")
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