What methods are used to perform parallel task execution on multiprocessor systems?

Parallel execution of tasks on multi-processor systems in Python is implemented in several ways:

• multiprocessing module — allows creating processes that run in parallel and are not limited by GIL (Global Interpreter Lock). This is an efficient method for CPU-bound tasks.

• Threads (threading) — suitable for I/O-bound tasks, as in Python, due to GIL, threads do not execute in parallel on multiple cores.

• concurrent.futures module — provides a convenient interface for running tasks in threads (ThreadPoolExecutor) or processes (ProcessPoolExecutor).

Example of 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]