Select a computationally intensive problem, such as large-scale numerical simulations, data processing, or scientific computing. Implement parallel computing using Python libraries like multiprocessing, threading, or distributed computing frameworks.

Assignment Question

Description: Develop a Python program that demonstrates advanced parallel computing techniques and optimization strategies for a computationally intensive task. The goal is to significantly improve the efficiency of the task by leveraging parallelism and optimization.

Requirements: Select a computationally intensive problem, such as large-scale numerical simulations, data processing, or scientific computing. Implement parallel computing using Python libraries like multiprocessing, threading, or distributed computing frameworks. Apply optimization techniques to the code, such as algorithmic improvements, memory optimizations, or vectorization. Measure and compare the performance of the optimized parallel code with the non-optimized version. Provide a comprehensive report detailing the problem, the parallelization and optimization strategies employed, and the performance results.