run a function in another processor in python

[Astan Chee]

Thanks for that. I'll try and see if it makes any difference but I'm using
python 2.6 not 3
Are the multiprocessing modules different? That code (or whatever is using
the multiprocessing module) seems to cause infinite python processes on my
machine and eventually kills it.
I'm running python 2.6 on windows 7 x64 ....is it the ammount of memory/cpu
speed/number of cpu that is the issue?
Thanks for any clarification



On Fri, Dec 10, 2010 at 4:16 AM, geremy condra <debatem1 at gmail.com> wrote:

>  On Thu, Dec 9, 2010 at 5:03 AM, Astan Chee <astan.chee at gmail.com> wrote:
> > Thanks but I'm having trouble with that module too. Currently what I
> > have is something like this:
> >
> > import sys
> > import os
> > import multiprocessing
> >
> > import time
> >
> > def functionTester(num):
> >    return ((num+2)/(num-2))**2
> >
> > num_args = [61,62,33,7,12,16,19,35,36,37,38,55,56,57,63]
> >
> > max_result = 0
> >
> > start = time.time()
> >
> > num_processes = multiprocessing.cpu_count()
> >
> > threads = []
> > len_stas = len(num_args)
> >
> > for list_item in num_args:
> >    if len(threads) < num_processes:
> >        p =
> multiprocessing.Process(target=functionTester,args=[list_item])
> >        p.start()
> >        print p, p.is_alive()
> >        threads.append(p)
> >    else:
> >        for thread in threads:
> >            if not thread.is_alive():
> >                threads.remove(thread)
> >
> > print "Result " + str(max_result)
> > end = time.time()
> > elapsed= end - start
> > print "Took", elapsed, "seconds to execute"
> >
> > But it doesn't give me any return data. It also spawns an infinite
> > number of (sub)processes that crashes my machine. What am I doing
> > wrong here?
> >
> > On 12/9/10, Jean-Michel Pichavant <jeanmichel at sequans.com> wrote:
> >> Astan Chee wrote:
> >>> Hi,
> >>> I've got a python script that calls a function many times with various
> >>> arguments and returns a result. What I'm trying to do is run this
> >>> function each on different processors and compile the result at the
> >>> end based on the function result. The script looks something like
> >>> this:
> >>>
> >>>
> >>> import time
> >>>
> >>> def functionTester(num):
> >>>     return ((num+2)/(num-2))**2
> >>>
> >>> num_args = [1,2,3,7,12,16,19,35,36,37,38,55,56,57,63,44,71,81,91]
> >>>
> >>> max_result = 0
> >>>
> >>> start = time.time()
> >>>
> >>> for n in num_args:
> >>>     result = functionTester(n)
> >>>     if result > max_result:
> >>>         max_result = result
> >>>
> >>> print "Result " + str(max_result)
> >>> end = time.time()
> >>> elapsed= end - start
> >>> print "Took", elapsed, "seconds to execute"
> >>>
> >>>
> >>> What I'm trying to do is run each function on a processor and when its
> >>> done, move on to the next function-argument specifically on windows 7
> >>> x64 using python 2.6. How do I do this?
> >>> Thanks for any help
> >>>
> >> If I'm not wrong, CPU management is handled by your system, meaning
> >> there's no way to 'force' anything to run on a specific CPU. However,
> >> you may try to execute your fonction in a subprocess, so that the system
> >> will use different CPUs (hopefully). You then just need to limit the
> >> number of subprocess alive at the same time.
> >>
> >> Have a look here
> >> http://docs.python.org/library/multiprocessing.html
> >>
> >> JM
> >>
> > --
> > http://mail.python.org/mailman/listinfo/python-list
> >
>
> Here's a way of doing what I think you mean to do. I assume that
> max_result should be the maximum value returned by a run of
> functionTester.
>
> Also, just a note, usually function names like this are spelled
> function_tester rather than functionTester in python.
>
> If you need to de-python3ify it just change the line at the top and
> cast your nums to floats, otherwise you'll get integer division (which
> I again assume you don't want).
>
> #! /usr/bin/env python3
>
> import time
> import multiprocessing
>
>
> def functionTester(num):
>   return ((num+2)/(num-2))**2
>
> num_args = [61,62,33,7,12,16,19,35,36,37,38,55,56,57,63]
>
> num_processes = multiprocessing.cpu_count()
> pool = multiprocessing.Pool(num_processes)
>
> start = time.time()
> results = pool.map(functionTester, num_args)
> end = time.time()
>
> # is this what you meant to do with the results?
> max_result = max(results)
> print("Result " + str(max_result))
>
> elapsed = end - start
> print("Took", elapsed, "seconds to execute")
>
> Geremy Condra
>
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