73 lines
1.8 KiB
Python
73 lines
1.8 KiB
Python
import numpy as np
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from time import time
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import multiprocessing
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def do_task(matrix, start_j, stop_j, queue):
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size = len(matrix[0] - 1)
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if size == 2:
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return matrix[0][0] * matrix[1][1] - matrix[1][0] * matrix[0][1]
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else:
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res = 0
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for j in range(start_j, stop_j):
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tmp = np.delete(matrix, 0, axis=0)
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tmp = np.delete(tmp, j, axis=1)
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a = matrix[0][j]
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b = do_task(tmp, 0, len(tmp[0]), None)
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if j % 2 == 0:
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res += a * b
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else:
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res += a * b * (-1)
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# print(res)
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if queue:
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queue.put(res)
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return res
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def do_threads(matrix, 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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queue = multiprocessing.Queue()
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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=do_task, args=(matrix, start_, stop_, queue))
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processes.append(process)
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process.start()
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total_result = 0
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for p in processes:
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p.join()
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total_result += queue.get()
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# print(total_result)
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stop_test = time()
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print(f'{size}x{size}, time: {stop_test - start_test}')
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matrix2 = np.array([
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[3, -3, -5, 8],
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[-3, 2, 4, -6],
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[2, -5, -7, 6],
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[-4, 3, 5, -6]
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])
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if __name__ == '__main__':
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sizes = [5, 6, 7, 8, 9, 10, 11, 12]
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threads_counts = [1, 4, 6, 8, 12]
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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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m = np.random.randint(3, size=(n, n))
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do_threads(m, n, threads)
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print('-------------------------------------------------')
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