Example of using the multiprocessing module in Python to fully utilize a CPU with 'n' cores.

multiprocessing_example.py

import multiprocessing
from threading import Thread
import random
import string


class ThreadWorker(Thread):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)

    def run(self):
        target = getattr(self, '_target', None)
        args = getattr(self, '_args', None)
        if not all([target, args]):
            raise AttributeError("thread has no attribute 'target' and/or 'args'")

        sum_ = 0
        for arg in args:
            sum_ += target(arg)
        # return sum_


def do_math(x):
    return x*x


def ptarget(queue, t_count):
    
    while True:
        args = queue.get()
        if args:
            workers = []
            for i in range(0, t_count):
                randargs = [random.randint(0, 100) for _ in range(0, 1000)]
                worker = ThreadWorker(args=list(randargs), target=do_math)
                worker.daemon = True
                workers.append(worker)

            for w in workers:
                w.start()

            for w in workers:
                w.join()

            queue.task_done()
            

def init_procs(processes: int = 1, threads: int = 1):

    q = multiprocessing.JoinableQueue()

    # create processes
    procs = [None] * processes
    for i in range(0, processes):
        p = multiprocessing.Process(target=ptarget, args=(q, threads), name=string.ascii_letters[i])
        p.daemon = True
        procs[i] = p

    # start each process
    for p in procs:
        p.start()

    return q


if __name__ == '__main__':
    queue = init_procs(8, 16)

    while True:
        queue.put(random.randint(1, 100))