multiprocessing - reading big input data - program hangs

I want to run parallel computation on some input data which is loaded from a file. (The file can be really big, so I use a generator for this.)

On a certain number of items, my code runs OK but above this threshold the program hangs (some of the worker processes do not end).

Any suggestions? (I am running this with python2.7, 8 CPUs; 5,000 lines still OK, 7,500 does not work.)

Firstly, you need an input file. Generate it in bash:

for i in {0..10000}; do echo -e "$i"'\r' >> counter.txt; done

Then, run this:

python2.7 main.py 100 counter.txt > run_log.txt

main.py:

#!/usr/bin/python2.7
import os, sys, signal, time
import Queue
import multiprocessing as mp

def eat_queue(job_queue, result_queue):
    """Eats input queue, feeds output queue
    """
    proc_name = mp.current_process().name
    while True:
        try:
            job = job_queue.get(block=False)
            if job == None:
                print(proc_name + " DONE")
                return
            result_queue.put(execute(job))
        except Queue.Empty:
            pass    

def execute(x):
    """Does the computation on the input data
    """
    return x*x

def save_result(result):
    """Saves results in a list
    """
    result_list.append(result)

def load(ifilename):
    """Generator reading the input file and
        yielding it row by row
    """
    ifile = open(ifilename, "r")
    for line in ifile:
        line = line.strip()
        num = int(line)
        yield (num)
    ifile.close()
    print("file closed".upper())

def put_tasks(job_queue, ifilename):
    """Feeds the job queue
    """
    for item in load(ifilename):
        job_queue.put(item)
    for _ in range(get_max_workers()):
        job_queue.put(None)

def get_max_workers():
    """Returns optimal number of processes to run
    """
    max_workers = mp.cpu_count() - 2
    if max_workers < 1:
        return 1
    return max_workers

def run(workers_num, ifilename):
    job_queue = mp.Queue()
    result_queue = mp.Queue()

    # decide how many processes are to be created
    max_workers = get_max_workers()
    print "processes available: %d" % max_workers
    if workers_num < 1 or workers_num > max_workers:
        workers_num = max_workers

    workers_list = []
    # a process for feeding job queue with the input file
    task_gen = mp.Process(target=put_tasks, name="task_gen",
                          args=(job_queue, ifilename))
    workers_list.append(task_gen)

    for i in range(workers_num):
        tmp = mp.Process(target=eat_queue, name="w%d" % (i+1),
                                      args=(job_queue, result_queue))
        workers_list.append(tmp)

    for worker in workers_list:
        worker.start()

    for worker in workers_list:
        worker.join()
        print "worker %s finished!" % worker.name

if __name__ == '__main__':
    result_list = []
    args = sys.argv
    workers_num = int(args[1])
    ifilename = args[2]
    run(workers_num, ifilename)