On Wed, Apr 6, 2011 at 9:06 PM, elsa <kerensael...@hotmail.com> wrote:
> Hi guys,
>
> I want to try out some pooling of processors, but I'm not sure if it
> is possible to do what I want to do. Basically, I want to have a
> global object, that is updated during the execution of a function, and
> I want to be able to run this function several times on parallel
> processors. The order in which the function runs doesn't matter, and
> the value of the object doesn't matter to the function, but I do want
> the processors to take turns 'nicely' when updating the object, so
> there are no collisions. Here is an extremely simplified and trivial
> example of what I have in mind:
>
> from multiprocessing import Pool
> import random
>
> p=Pool(4)
> myDict={}
>
> def update(value):
> global myDict
> index=random.random()
> myDict[index]+=value
>
> total=1000
>
> p.map(update,range(total))
>
>
> After, I would also like to be able to use several processors to
> access the global object (but not modify it). Again, order doesn't
> matter:
>
> p1=Pool(4)
>
> def getValues(index):
> global myDict
> print myDict[index]
>
> p1.map(getValues,keys.myDict)
>
> Is there a way to do this
This should give you a synchronized wrapper around an object in shared
memory:
http://docs.python.org/library/multiprocessing.html#multiprocessing.Value
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