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Parallel vs Sequential Execution in Python — CPU-bound Benchmarking

This project benchmarks and visualizes the performance difference between sequential and multiprocessing execution in Python. It simulates CPU-intensive tasks using heavy mathematical computations, records the execution time of both approaches, and plots the results using Matplotlib.

It’s designed to demonstrate how multiprocessing can significantly improve performance in CPU-bound scenarios — especially useful for students, performance engineers, or anyone curious about Python concurrency.

Key Features

CPU-heavy task simulation using pure Python

Execution time comparison: sequential vs multiprocessing

Matplotlib-based performance visualization

Educational code with clear structure and comments

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Parallel vs Sequential Execution in Python — CPU-bound Benchmarking

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