forked from Alexey/DAS_2024_1
53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
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import multiprocessing
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import time
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from time import time
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import numpy as np
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def matrix_multi(first, second, res, start_i, stop_i, size):
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for i in range(start_i, stop_i):
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for j in range(size):
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res[i][j] = 0
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for k in range(size):
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res[i][j] += first[i][k] * second[k][j]
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def do(first, second, size, threads):
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offset = int(size / threads)
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offset_last = size % threads + offset
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processes = []
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res = np.zeros((size, size))
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start_test = time()
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for i in range(threads):
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start_ = i * offset
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stop_ = start_ + offset_last if i == threads - 1 else start_ + offset
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process = multiprocessing.Process(target=matrix_multi, args=(first, second, res, start_, stop_, size))
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processes.append(process)
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process.start()
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for p in processes:
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p.join()
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stop_test = time()
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print(f'{n}x{n}, time: {stop_test - start_test}')
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if __name__ == "__main__":
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threads_count = 20 # задание кол-ва потоков
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sizes = [100, 300, 500]
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test = [[5, 3, 4], [2, 8, 3], [6, 3, 4]]
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test2 = [[4, 3, 6], [2, 8, 3], [5, 6, 4]]
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threads_counts = [1, 4, 6, 8]
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for threads in threads_counts:
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print('-------------------------------------------------')
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print(f'Threads:{threads}')
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for n in sizes:
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first_matrix = np.random.randint(3, size=(n, n))
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second_matrix = np.random.randint(3, size=(n, n))
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do(first_matrix, second_matrix, n, threads)
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print('-------------------------------------------------')
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