Perhaps it's my inability to properly use openmp, but when working on
scikits.image on algorithms doing per-pixel manipulation with numpy arrays
(using Cython), i saw better performance using Python threads and releasing
the GIL than I did with openmp. I found the openmp overhead to be quite
large,
hi,
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.
cheers,
On Sat, Feb 13, 2010 at 2:20 PM, David Cournapeau wrote:
> On Sat, Feb 13, 2010 at 6:20 PM, Wolfgang
On Sat, Feb 13, 2010 at 6:20 PM, Wolfgang Kerzendorf
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 multipl
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 sp
