73 lines
2.7 KiB
Python
73 lines
2.7 KiB
Python
import numpy as np
|
||
import time
|
||
import multiprocessing
|
||
|
||
|
||
def sequential_matrix_multiply(matrix_a, matrix_b):
|
||
result = np.zeros((len(matrix_a), len(matrix_b[0])))
|
||
for i in range(len(matrix_a)):
|
||
for j in range(len(matrix_b[0])):
|
||
for k in range(len(matrix_b)):
|
||
result[i][j] += matrix_a[i][k] * matrix_b[k][j]
|
||
return result
|
||
|
||
|
||
def parallel_matrix_multiply_worker(args):
|
||
matrix_a, matrix_b, row_start, row_end, result = args
|
||
local_result = np.zeros((row_end - row_start, len(matrix_b[0])))
|
||
for i in range(row_start, row_end):
|
||
for j in range(len(matrix_b[0])):
|
||
for k in range(len(matrix_b)):
|
||
local_result[i - row_start][j] += matrix_a[i][k] * matrix_b[k][j]
|
||
result.extend(local_result)
|
||
|
||
|
||
def parallel_matrix_multiply(matrix_a, matrix_b, num_processes=2):
|
||
num_rows_a = len(matrix_a)
|
||
chunk_size = num_rows_a // num_processes
|
||
processes = []
|
||
manager = multiprocessing.Manager()
|
||
result = manager.list()
|
||
|
||
for i in range(num_processes):
|
||
row_start = i * chunk_size
|
||
row_end = (i + 1) * chunk_size if i < num_processes - 1 else num_rows_a
|
||
process_args = (matrix_a, matrix_b, row_start, row_end, result)
|
||
process = multiprocessing.Process(target=parallel_matrix_multiply_worker, args=(process_args,))
|
||
processes.append(process)
|
||
|
||
for process in processes:
|
||
process.start()
|
||
|
||
for process in processes:
|
||
process.join()
|
||
|
||
return np.vstack(result)
|
||
|
||
|
||
def run_test(matrix_size, num_processes=2):
|
||
matrix_a = np.random.rand(matrix_size, matrix_size)
|
||
matrix_b = np.random.rand(matrix_size, matrix_size)
|
||
|
||
start_time = time.time()
|
||
result_sequential = sequential_matrix_multiply(matrix_a, matrix_b)
|
||
sequential_time = time.time() - start_time
|
||
print(f"Последовательноe умножение заняло ({matrix_size}x{matrix_size}): {sequential_time} секунд")
|
||
|
||
start_time = time.time()
|
||
result_parallel = parallel_matrix_multiply(matrix_a, matrix_b, num_processes)
|
||
parallel_time = time.time() - start_time
|
||
print(
|
||
f"Параллельное умножение матрицы ({matrix_size}x{matrix_size}) с {num_processes} потоками заняло: {parallel_time} секунд")
|
||
print("========================================")
|
||
|
||
# Тесты для матриц размером 100x100, 300x300 и 500x500 с разным числом процессов
|
||
|
||
# Бенчмарки для матриц размером 100, 300, 500 строк
|
||
if __name__ == '__main__':
|
||
run_test(100, num_processes=2)
|
||
run_test(100, num_processes=4)
|
||
run_test(300, num_processes=2)
|
||
run_test(300, num_processes=4)
|
||
run_test(500, num_processes=2)
|
||
run_test(500, num_processes=4) |