What methods or libraries have you used to implement parallel computing and task distribution in multi-processor systems?

In Python, the following modules and libraries are often used for parallel computing and task distribution in multi-processor systems:

• multiprocessing — a standard module for creating processes, allowing functions to run in parallel in different processes.
• concurrent.futures — provides a convenient interface for parallel task execution with ThreadPoolExecutor and ProcessPoolExecutor.
• joblib — a library for simple parallel execution of loops and functions, often used in scientific computing.
• dask — for distributed computing and working with large data.

Example using multiprocessing:

from multiprocessing import Pool

def f(x):
    return x * x

if __name__ == '__main__':
    with Pool(4) as p:
        results = p.map(f, [1, 2, 3, 4, 5])
    print(results)  # [1, 4, 9, 16, 25]