Merge pull request '[Л/Р 5] Никифорова Татьяна' (#142) from tanya_nik16/distributed-computing:Nikiforova-TS-Lab-5 into main

Reviewed-on: http://student.git.athene.tech/v.moiseev/distributed-computing/pulls/142

tasks/nikiforova-ts/Lab_5/.gitignore

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tasks/nikiforova-ts/Lab_5/Readme.md

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+# Отчёт по лабораторной работе №5
+
+Выполнила: студентка гр. ИСЭбд-41 Никифорова Татьяна Сергеевна.
+
+## Создание приложения
+
+Выбрала язык Python.
+
+Запустим алгоритм с матрицей 10x10 c различными алгоритмами.
+
+![](picture/1.png) 
+![](picture/2.png)
+
+## Бенчмарки
+
+Протекстируем обычный и паралелльный с различными размерами матриц.
+
+Матрица 100х100
+
+![](picture/3-100.png) 
+![](picture/4.png)
+
+Матрица 300х300
+
+![](picture/5-300.png) 
+![](picture/6.png)
+
+Матрица 500х500
+
+![](picture/7-500.png) 
+![](picture/8.png)
+
+Вывод: Для небольших матриц и с небольшим количеством ядер процессора параллельная реализация может не всегда оказаться быстрее из-за дополнительных накладных расходов.
+
+
+
+
+

tasks/nikiforova-ts/Lab_5/work/Lab5.py

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+import numpy as np
+import tkinter as tk
+from tkinter import ttk
+from multiprocessing import Pool
+import time
+
+def multiply_matrices_sequential(matrix_a, matrix_b):
+    return np.dot(matrix_a, matrix_b)
+
+def multiply_matrices_parallel(args):
+    row, matrix_a, matrix_b, cols = args
+    return [sum(matrix_a[row, k] * matrix_b[k, col] for k in range(cols)) for col in range(cols)]
+
+def multiply_matrices(matrix_size, parallel=False, num_threads=None):
+    matrix_a = np.random.randint(1, 10, size=(matrix_size, matrix_size))  # Генерация целых чисел от 1 до 10
+    matrix_b = np.random.randint(1, 10, size=(matrix_size, matrix_size))
+
+    if parallel:
+        start_time = time.time()
+        args = [(row, matrix_a, matrix_b, matrix_size) for row in range(matrix_size)]
+
+        with Pool(num_threads) as pool:
+            result = np.array(pool.map(multiply_matrices_parallel, args))
+
+        end_time = time.time()
+    else:
+        start_time = time.time()
+        result = multiply_matrices_sequential(matrix_a, matrix_b)
+        end_time = time.time()
+
+    execution_time = end_time - start_time
+
+    return matrix_a, matrix_b, result, execution_time
+
+def run_multiplication():
+    matrix_size = int(matrix_size_entry.get())
+    algorithm_choice = algorithm_var.get()
+    parallel = True if algorithm_choice == 'Параелльный' else False
+    num_threads = int(threads_entry.get()) if parallel else None
+
+    matrix_a, matrix_b, result, execution_time = multiply_matrices(matrix_size, parallel, num_threads)
+
+    result_text.config(state=tk.NORMAL)
+    result_text.delete("1.0", tk.END)
+    result_text.insert(tk.END, f"Результат:\n{result}\n\nВремя: {execution_time:.6f} секунд")
+    result_text.config(state=tk.DISABLED)
+
+    matrix_a_text.config(state=tk.NORMAL)
+    matrix_a_text.delete("1.0", tk.END)
+    matrix_a_text.insert(tk.END, f"Матрица A:\n{matrix_a}")
+    matrix_a_text.config(state=tk.DISABLED)
+
+    matrix_b_text.config(state=tk.NORMAL)
+    matrix_b_text.delete("1.0", tk.END)
+    matrix_b_text.insert(tk.END, f"Матрица B:\n{matrix_b}")
+    matrix_b_text.config(state=tk.DISABLED)
+
+# GUI setup
+root = tk.Tk()
+root.title("Matrix Multiplication")
+
+# Matrix Size
+matrix_size_label = ttk.Label(root, text="Размер матрицы:")
+matrix_size_label.grid(row=0, column=0, padx=5, pady=5)
+matrix_size_entry = ttk.Entry(root)
+matrix_size_entry.grid(row=0, column=1, padx=5, pady=5)
+matrix_size_entry.insert(0, "")
+
+# Algorithm Choice
+algorithm_label = ttk.Label(root, text="Алгоритм:")
+algorithm_label.grid(row=1, column=0, padx=5, pady=5)
+algorithm_var = tk.StringVar(value="Обычный")
+algorithm_combobox = ttk.Combobox(root, textvariable=algorithm_var, values=["Обычный", "Паралелльный"])
+algorithm_combobox.grid(row=1, column=1, padx=5, pady=5)
+
+# Threads (only for parallel algorithm)
+threads_label = ttk.Label(root, text="Потоки:")
+threads_label.grid(row=2, column=0, padx=5, pady=5)
+threads_entry = ttk.Entry(root)
+threads_entry.grid(row=2, column=1, padx=5, pady=5)
+threads_entry.insert(0, "4")
+#threads_entry.state(['readonly'])  # make it read-only initially
+
+# Run Button
+run_button = ttk.Button(root, text="Начать", command=run_multiplication)
+run_button.grid(row=3, column=0, columnspan=2, pady=10)
+
+# Result Text
+result_text = tk.Text(root, height=15, width=50, state=tk.DISABLED)
+result_text.grid(row=4, column=0, columnspan=2, padx=10, pady=10)
+
+# Generated Matrix A
+matrix_a_text = tk.Text(root, height=10, width=25, state=tk.DISABLED)
+matrix_a_text.grid(row=5, column=0, padx=10, pady=5)
+
+# Generated Matrix B
+matrix_b_text = tk.Text(root, height=10, width=25, state=tk.DISABLED)
+matrix_b_text.grid(row=5, column=1, padx=10, pady=5)
+
+root.mainloop()