multiproc.py

#!/usr/bin/env python2

from multiprocessing import Process, Queue
from Queue import Empty
import numpy as np

START = 'START'
FINAL = 'FINAL'
STEPS = 'STEPS'
SIZE  = 'SIZE'
P_IMMUNE = 'P_IMMUNE'

def run_sim (in_, out_):
    try:
        while True:
            sim = in_.get(False) # get simulation from input
            start = np.zeros((sim[SIZE], sim[SIZE]))
            final = np.array(start) # Clone start
            steps = 0
            # Perform the rest of the simulation

            # Store the results in the dict
            sim[START] = start
            sim[FINAL] = final
            sim[STEPS] = steps
            out_.put(sim) # put result in output
    except Empty:
        pass # I expect to get this when the queue is empty. That's OK.


cores = 2 # NB. Make sure this is not higher than the number of cores on your
          # computer!
runs = 10
n = 10
p = .5683645 # Number pulled out of my head at quasi-random

inbox = Queue()
outbox = Queue()

for i in xrange(runs):
    inbox.put({
        SIZE: n,
        P_IMMUNE: p
    })

workers = []
for i in xrange(cores):
    worker = Process(target=run_sim, args=(inbox,outbox))
    worker.start()
    workers.append(worker)

results = []
for i in xrange(runs):
    results.append(outbox.get()) # get results from the workers

# at this point all results collected workers are stopped.

for worker in workers:
    worker.join() # 'rightsize' workers

print results