Python multiprocessing doesn't use more than 1 core

Question

I have a problem with multiprocessing to use more than 1 core. I didn't use .join() which waits the previous process to finish, i have a CPU with 4 cores and i still don't know why this code only uses %20 of the CPU, it supposed to use more than %50.

import multiprocessing
import time
def f(x,y):
    global StartTime
    for ord1 in range(x):
        x *= 2
    print(y, time.time()-StartTime)

if __name__ == "__main__":
    input1 = 500000
    StartTime = time.time()
    p1 = multiprocessing.Process(target=f(input1,1))
    p2 = multiprocessing.Process(target=f(input1,2))
    p3 = multiprocessing.Process(target=f(input1,3))
    p4 = multiprocessing.Process(target=f(input1,4))
    p1.start()
    p2.start()
    p3.start()
    p4.start()
    print("Done")

I guess the program executes them one by one instead of parallel judging from the output:

1 5.373946189880371

2 10.663974285125732

3 15.902992725372314

4 21.29733967781067

Done

So, my question is how do i use multiple cores and execute the code parallelly?

Erik Cederstrand · Accepted Answer · 2018-03-28 18:13:52Z

When starting a process, you need to provide the arguments to your target function via args. See https://docs.python.org/3/library/multiprocessing.html#the-process-class. Otherwise, f(input1, 1) is calculated in your main process, not the worker.

Your main routine should be:

if __name__ == "__main__":
    input1 = 500000
    StartTime = time.time()
    p1 = multiprocessing.Process(target=f, args=(input1,1))
    p2 = multiprocessing.Process(target=f, args=(input1,2))
    p3 = multiprocessing.Process(target=f, args=(input1,3))
    p4 = multiprocessing.Process(target=f, args=(input1,4))
    p1.start()
    p2.start()
    p3.start()
    p4.start()
    print("Done")

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