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266432cfda
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0227f5eaa0
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import numpy as np
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import time
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import concurrent.futures
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def multiply_matrices(matrix_a, matrix_b):
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if len(matrix_a[0]) != len(matrix_b):
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raise ValueError("Incompatible matrix dimensions for multiplication")
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result = [[0 for _ in range(len(matrix_b[0]))] for _ in range(len(matrix_a))]
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for i in range(len(matrix_a)):
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for j in range(len(matrix_b[0])):
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for k in range(len(matrix_b)):
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result[i][j] += matrix_a[i][k] * matrix_b[k][j]
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return result
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def multiply_matrices_parallel(matrix_a, matrix_b, num_threads):
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if len(matrix_a[0]) != len(matrix_b):
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raise ValueError("Incompatible matrix dimensions for multiplication")
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result = [[0 for _ in range(len(matrix_b[0]))] for _ in range(len(matrix_a))]
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with concurrent.futures.ThreadPoolExecutor(max_workers=num_threads) as executor:
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futures = []
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for i in range(len(matrix_a)):
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futures.append(executor.submit(_multiply_row, matrix_a, matrix_b, i))
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for i, future in enumerate(concurrent.futures.as_completed(futures)):
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result[i] = future.result()
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return result
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def _multiply_row(matrix_a, matrix_b, i):
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row_result = [0 for _ in range(len(matrix_b[0]))]
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for j in range(len(matrix_b[0])):
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for k in range(len(matrix_b)):
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row_result[j] += matrix_a[i][k] * matrix_b[k][j]
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return row_result
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def benchmark_sequential(size):
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matrix_a = np.random.rand(size, size)
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matrix_b = np.random.rand(size, size)
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start_time = time.time()
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multiply_matrices(matrix_a, matrix_b)
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end_time = time.time()
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return end_time - start_time
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def benchmark_parallel(size, num_threads):
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matrix_a = np.random.rand(size, size)
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matrix_b = np.random.rand(size, size)
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start_time = time.time()
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multiply_matrices_parallel(matrix_a, matrix_b, num_threads)
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end_time = time.time()
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return end_time - start_time
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if __name__ == "__main__":
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sizes = [300]
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threads = [2, 8]
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for size in sizes:
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sequential_time = benchmark_sequential(size)
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print(f"Время обычное: {sequential_time} с")
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print(f"Размер матрицы: {size}x{size}")
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for thread in threads:
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for size in sizes:
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parallel_time = benchmark_parallel(size, thread)
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print(f"Размер матрицы: {size}x{size}")
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print(f"Время параллельное: {parallel_time} с")
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print(f"Потоков: {thread}")
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from flask import Flask, render_template, request
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import numpy as np
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import concurrent.futures
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app = Flask(__name__)
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def multiply_matrices(matrix_a, matrix_b):
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if len(matrix_a[0]) != len(matrix_b):
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raise ValueError("Incompatible matrix dimensions for multiplication")
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result = [[0 for _ in range(len(matrix_b[0]))] for _ in range(len(matrix_a))]
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for i in range(len(matrix_a)):
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for j in range(len(matrix_b[0])):
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for k in range(len(matrix_b)):
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result[i][j] += matrix_a[i][k] * matrix_b[k][j]
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return result
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def multiply_matrices_parallel(matrix_a, matrix_b, num_threads):
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if len(matrix_a[0]) != len(matrix_b):
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raise ValueError("Incompatible matrix dimensions for multiplication")
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result = [[0 for _ in range(len(matrix_b[0]))] for _ in range(len(matrix_a))]
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with concurrent.futures.ThreadPoolExecutor(max_workers=num_threads) as executor:
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futures = []
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for i in range(len(matrix_a)):
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futures.append(executor.submit(_multiply_row, matrix_a, matrix_b, i))
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for i, future in enumerate(concurrent.futures.as_completed(futures)):
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result[i] = future.result()
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return result
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def _multiply_row(matrix_a, matrix_b, i):
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row_result = [0 for _ in range(len(matrix_b[0]))]
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for j in range(len(matrix_b[0])):
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for k in range(len(matrix_b)):
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row_result[j] += matrix_a[i][k] * matrix_b[k][j]
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return row_result
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@app.route('/')
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def index():
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return render_template('index.html')
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@app.route('/multiply', methods=['POST'])
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def multiply():
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n = int(request.form.get('matrix_a'))
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matrix_a = np.random.randint(10, size=(n, n))
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matrix_b = np.random.randint(10, size=(n, n))
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operation_type = request.form.get('operation_type')
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if operation_type == 'sequential':
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result = multiply_matrices(matrix_a, matrix_b)
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elif operation_type == 'parallel':
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result = multiply_matrices_parallel(matrix_a, matrix_b)
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else:
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return "Invalid operation type"
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return render_template('result.html', matrix_a=matrix_a, matrix_b=matrix_b, result=result)
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if __name__ == '__main__':
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app.run(debug=True)
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@ -1,24 +0,0 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta http-equiv="X-UA-Compatible" content="IE=edge">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Matrix Multiplication</title>
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</head>
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<body>
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<h1>Matrix Multiplication</h1>
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<form action="/multiply" method="post">
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<label for="matrix_a">Matrix размер:</label>
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<input type="text" name="matrix_a" required><br>
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<label for="operation_type">Как умножить:</label>
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<select name="operation_type">
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<option value="sequential">Последовательно</option>
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<option value="parallel">Параллельно</option>
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</select><br>
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<button type="submit">Умножение матриц</button>
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</form>
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</body>
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</html>
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@ -1,19 +0,0 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta http-equiv="X-UA-Compatible" content="IE=edge">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Matrix Multiplication Result</title>
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</head>
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<body>
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<h1>Результат</h1>
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<p>Matrix A:</p>
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<pre>{{ matrix_a }}</pre>
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<p>Matrix B:</p>
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<pre>{{ matrix_b }}</pre>
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<p>Result:</p>
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<pre>{{ result }}</pre>
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<a href="/">Назад</a>
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</body>
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</html>
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