86 lines
2.8 KiB
Python
86 lines
2.8 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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from multiprocessing import Pool
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MAX_SIZE = 500
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def generateSquareMatrix(size):
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return [[rnd.randint(0, 100) for _ in range(size)] for _ in range(size)]
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# Функция для перемножения матриц
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def matrixMultiply(matrix1, matrix2, start_i=0, end_i=None):
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l1 = len(matrix1)
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l2 = len(matrix2)
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global result_matrix
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result = result_matrix
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end_i = end_i if end_i is not None else l1
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for i in range(start_i, end_i):
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for j in range(len(matrix2[0])):
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for k in range(l2):
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result[i][j] += matrix1[i - start_i][k] * matrix2[k][j]
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return result
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# Перемножение без использования потоков
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def matrixMultiplyStandard(matrix1, matrix2):
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return matrixMultiply(matrix1, matrix2)
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# Перемножение в отдельном потоке
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def matrixMultiplySingleThread(args):
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matrix1, matrix2, start_i, end_i = args
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matrixMultiply(matrix1, matrix2, start_i, end_i)
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# Параллельное перемножение
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def matrixMultiplyWithThreads(matrix1, matrix2, thread_count):
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l1 = len(matrix1)
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l2 = len(matrix2)
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# Кол-во строк на последний поток, если деление по потокам будет неточным
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last_rows_count = 0
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if l1 % thread_count == 0:
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rows_per_thread = l1 // thread_count
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else:
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rows_per_thread = l1 // thread_count
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last_rows_count = l1 % thread_count
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for i in range(thread_count):
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start_i = i * rows_per_thread
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if (i - 1) == thread_count and last_rows_count > 0:
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end_i = start_i + last_rows_count
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else:
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end_i = start_i + rows_per_thread
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args = []
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args.append((matrix1[start_i:end_i], matrix2, start_i, end_i))
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with Pool(processes = thread_count) as pool:
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pool.map(matrixMultiplySingleThread, args)
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result_matrix = [[0 for _ in range(MAX_SIZE)] for _ in range(MAX_SIZE)]
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if __name__ == "__main__":
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sizes = [100, 300, 500]
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num_threads = [1, 5, 8]
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for size in sizes:
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matrix1 = generateSquareMatrix(size)
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matrix2 = generateSquareMatrix(size)
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# Обычное перемножение
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start_time = time.time()
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matrixMultiplyStandard(matrix1, matrix2)
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end_time = time.time()
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print(f"Обычное перемножение.\t\tРазмер: {size}\t\t|\t {end_time - start_time}")
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# Перемножение в потоках
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for threads in num_threads:
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start_time = time.time()
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matrixMultiplyWithThreads(matrix1, matrix2, threads)
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end_time = time.time()
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print(f"Параллельное перемножение.\tРазмер: {size}, {threads} потоков\t|\t {end_time - start_time}")
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print("=" * 100)
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