[Numpy-discussion] Multithreading support

René Dudfield renesd@gmail....
Sat Feb 13 06:25:56 CST 2010


see: http://numcorepy.blogspot.com/

They see a benefit when working with large arrays.  Otherwise you are
limited by memory - and the extra cores don't help with memory bandwidth.


On Sat, Feb 13, 2010 at 2:20 PM, David Cournapeau <cournape@gmail.com>wrote:

> On Sat, Feb 13, 2010 at 6:20 PM, Wolfgang Kerzendorf
> <wkerzendorf@googlemail.com> wrote:
> > Dear all,
> >
> > I don't know much about parallel programming so I don't know how easy it
> is to do that: When doing simple arrray operations like adding two arrays or
> adding a number to the array, is numpy able to put this on multiple cores? I
> have tried it but it doesnt seem to do that. Is there a special multithread
> implementation of numpy.
> Depending on your definition of simple operations, Numpy supports
> multithreaded execution or not. For ufuncs (which is used for things
> like adding two arrays together, etc...), there is no multithread
> support.
> >
> > IDL has this feature where it checks how many cores available and uses
> them. This feature in numpy would make an already amazing package even
> better.
> AFAIK, using multi-thread at the core level of NumPy has been tried
> only once a few years ago, without much success (no significant
> performance improvement). Maybe the approach was flawed in some ways.
> Some people have suggested using OpenMP, but nobody has every produced
> something significant AFAIK:
> http://mail.scipy.org/pipermail/numpy-discussion/2008-March/031897.html
> Note that Linear algebra operations can run in // depending on your
> libraries. In particular, the dot function runs in // if your
> blas/lapack does.
> cheers,
> David
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