A benchmark for using a Python multiprocessing pool to process pool share submissions

share_proc_multiprocessing.py

from multiprocessing import Pool
from vtc_scrypt import getPoWHash
from time import sleep

import gevent
import os
import time

def f(x):
    return getPoWHash(x)

def f_hndle(pipe):
    while True:
        pipe.recv()

header_hex = ("01000000" +
              "81cd02ab7e569e8bcd9317e2fe99f2de44d49ab2b8851ba4a308000000000000" +
              "e320b6c2fffc8d750423db8b1eb942ae710e951ed797f7affc8892b0f1fc122b" +
              "c7f5d74d" +
              "f2b9441a" +
              "42a14695")
header_bin = header_hex.decode('hex')

#durs = []
#for i in xrange(1000):
#    start = time.time()
#    #result = pool.apply(f, [b])
#    result = getPoWHash(header_bin)
#    dur = time.time() - start
#    durs.append(dur)
#
#print "average time {} us".format(sum(durs) / len(durs) * 1000000)
#exit(0)

procs = []
pipes = []

for i in xrange(4):
    pipe = multiprocessing.Pipe()
    proc = multiprocessing.Process(
durs = []
def run_proc():
    for i in xrange(5):
        start = time.time()
        result = pool.apply(f, [header_bin])
        #result = getPoWHash(header_bin)
        dur = time.time() - start
        durs.append(dur)
        sleep(0.01)
        #print "done"

start = time.time()
green = []
for i in xrange(1000):
    green.append(gevent.spawn(run_proc))

gevent.joinall(green)
print "runtime {}".format(time.time() - start)
print "average time {} us".format(sum(durs) / len(durs) * 1000000)