import numpy as np
import time
import concurrent.futures

def multiply_matrices(matrix_a, matrix_b):
    return np.dot(matrix_a, matrix_b)

def multiply_matrices_parallel(matrix_a, matrix_b):
    with concurrent.futures.ThreadPoolExecutor() as executor:
        result = executor.submit(np.dot, matrix_a, matrix_b)
    return result.result()

def benchmark_sequential(size):
    matrix_a = np.random.rand(size, size)
    matrix_b = np.random.rand(size, size)

    start_time = time.time()
    multiply_matrices(matrix_a, matrix_b)
    end_time = time.time()

    return end_time - start_time

def benchmark_parallel(size):
    matrix_a = np.random.rand(size, size)
    matrix_b = np.random.rand(size, size)

    start_time = time.time()
    multiply_matrices_parallel(matrix_a, matrix_b)
    end_time = time.time()

    return end_time - start_time

if __name__ == "__main__":
    sizes = [100, 300, 500, 700, 900, 1000, 1200, 1400, 1700, 2000]

    for size in sizes:
        sequential_time = benchmark_sequential(size)
        parallel_time = benchmark_parallel(size)

        print(f"Размер матрицы: {size}x{size}")
        print(f"Время обычное: {sequential_time} с")
        print(f"Время параллельное: {parallel_time} с")
        print(f"Ускорение: {sequential_time / parallel_time}\n")