python multithreading,multiprocessing效率对比

import multiprocessing as mp
import threading as td
import time

def job(q):
    res = 0
    for i in range(1000000):
        res += i + i ** 2 + i**3
    q.put(res)

def multcore():
    q = mp.Queue()
    p1 = mp.Process(target=job,args=(q,))
    p2 = mp.Process(target=job,args=(q,))
    p1.start()
    p2.start()
    p1.join()
    p2.join()
    res1 = q.get()
    res2 = q.get()
    print('multcore: ',res1 + res2)

def normal():
    res = 0
    for _ in range(2):
        for i in range(1000000):
            res += i + i ** 2 + i**3
    print('normal: ',res)

def multithread():
    q = mp.Queue()
    t1 = td.Thread(target=job,args=(q,))
    t2 = td.Thread(target=job,args=(q,))
    t1.start()
    t2.start()
    t1.join()
    t2.join()
    res1 = q.get()
    res2 = q.get()
    print('multithread: ',res1 + res2)

if __name__ == '__main__':
    st = time.time()

    normal()
    st1 = time.time()
    print('normal time: ',st1 - st)

    multithread()
    st2 = time.time()
    print('multithread time: ', st2 - st1)

    multcore()
    print('multcore time: ',time.time() - st2)

result:

normal time:  1.3973419666290283
multithread time:  1.416612148284912
multcore time:  0.7420649528503418