103 lines
2.2 KiB
Python
103 lines
2.2 KiB
Python
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import random as rnd
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import threading
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import time
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import concurrent.futures
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from copy import deepcopy
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def generateSquareMatrix(size):
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return [[rnd.randint(0, 100) for i in range(size)] for j in range(size)]
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def printMatrix(matrix):
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for row in matrix:
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print(*row, sep="\t")
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testmatrix = generateSquareMatrix(500)
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def process_row(args):
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i, j, m, n = args
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factor = m[j][i] / m[i][i]
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for k in range(i, n):
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m[j][k] -= factor * m[i][k]
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return m[j]
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def parallel_det(matrix, threadss):
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n = len(matrix)
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m = deepcopy(matrix)
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det_value = 1
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def process_row(i, j):
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factor = m[j][i] / m[i][i]
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for k in range(i, n):
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m[j][k] -= factor * m[i][k]
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for i in range(n):
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if m[i][i] == 0:
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for j in range(i + 1, n):
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if m[j][i] != 0:
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m[i], m[j] = m[j], m[i]
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det_value *= -1
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break
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else:
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return 0
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with concurrent.futures.ThreadPoolExecutor(max_workers=threadss) as executor:
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futures = [
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executor.submit(process_row, i, j) for j in range(i + 1, n)
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]
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concurrent.futures.wait(futures)
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det_value *= m[i][i]
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return det_value
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def det(matrix):
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n = len(matrix)
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m = [row[:] for row in matrix]
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det_value = 1
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for i in range(n):
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if m[i][i] == 0:
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for j in range(i + 1, n):
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if m[j][i] != 0:
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m[i], m[j] = m[j], m[i]
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det_value *= -1
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break
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else:
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return 0
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for j in range(i + 1, n):
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factor = m[j][i] / m[i][i]
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for k in range(i, n):
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m[j][k] -= factor * m[i][k]
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det_value *= m[i][i]
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return det_value
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if __name__ == "__main__":
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sizes = [100, 300, 500]
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num_threads = [1, 5, 8, 12]
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for size in sizes:
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matrix1 = generateSquareMatrix(size)
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for threads in num_threads:
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start_time = time.time()
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parallel_det(matrix1, threads)
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end_time = time.time()
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print(f"Parallel size {size}, {threads} thread(s): {end_time - start_time}s")
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print("-" * 100)
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