61 lines
2.4 KiB
Python
61 lines
2.4 KiB
Python
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import numpy as np
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import time
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from multiprocessing import Pool
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def determinant(matrix):
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return np.linalg.det(matrix)
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def parallel_determinant(matrix, num_threads):
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size = matrix.shape[0]
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step = size // num_threads
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pool = Pool(processes=num_threads)
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blocks = []
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for i in range(0, size, step):
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blocks.append(matrix[i:i+step, i:i+step])
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dets = pool.map(determinant, blocks)
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return np.prod(dets)
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def benchmark(num_threads):
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matrix1 = np.random.rand(100, 100)
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start_time = time.time()
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det1 = determinant(matrix1)
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end_time = time.time()
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execution_time = end_time - start_time
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print("Матрица 100x100:", matrix1)
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print("Детерминант матрицы 100x100:", det1)
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print("Последовательное время выполнения:", execution_time, "сек")
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start_time = time.time()
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detp1 = parallel_determinant(matrix1, num_threads)
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end_time = time.time()
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execution_time = end_time - start_time
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print("Пареллельное время выполнения:", execution_time, "сек")
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matrix2 = np.random.rand(300, 300)
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start_time = time.time()
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det2 = determinant(matrix2)
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end_time = time.time()
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execution_time = end_time - start_time
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print("Матрица 300x300:", matrix2)
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print("Детерминант матрицы 300x300:", det2)
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print("Последовательное время выполнения:", execution_time, "сек")
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start_time = time.time()
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detp2 = parallel_determinant(matrix2, num_threads)
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end_time = time.time()
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execution_time = end_time - start_time
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print("Пареллельное время выполнения:", execution_time, "сек")
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matrix3 = np.random.rand(500, 500)
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det3 = determinant(matrix3)
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end_time = time.time()
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execution_time = end_time - start_time
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print("Матрица 500x500:", matrix3)
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print("Детерминант матрицы 500x500:", det3)
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print("Последовательное время выполнения:", execution_time, "сек")
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start_time = time.time()
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detp3 = parallel_determinant(matrix3, num_threads)
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end_time = time.time()
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execution_time = end_time - start_time
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print("Пареллельное время выполнения:", execution_time, "сек")
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if __name__ == "__main__":
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print("Введите кол-во поток")
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n = int(input())
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benchmark(n)
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