try_parallel.py

import numpy as np
from multiprocessing import Pool, Process
import time


def f(x):
    time.sleep(2)
    return x * x


def rand():
    return np.random.random()


def run_map(numW=4, numJobs=20):
    t1 = time.time()
    pool = Pool(numW)
    print(pool.map(f, range(numJobs)))
    t2 = time.time()
    print('Time: ', t2 - t1)


def run_process(numJobs=20):
    t1 = time.time()
    prcs = []
    for i in range(numJobs):
        p = Process(target=f, args=(i,))
        p.start()
        prcs.append(p)
    print('All Processes launched')
    for p in prcs:
        p.join()
    t2 = time.time()
    print('Time: ', t2 - t1)


def run_async(numW=4, numJobs=20):
    t1 = time.time()
    p = Pool(numW)
    resPool = []
    for i in range(numJobs):
        # resPool.append(p.apply_async(f, [i]))
        resPool.append(p.apply_async(rand))
    print('All Processes launched')
    res = []
    for r in resPool:
        res.append(r.get())
    t2 = time.time()
    print('Time: ', t2 - t1)
    p.close()
    return res