[Numpy-discussion] performance matrix multiplication vs. matlab

Chris Colbert sccolbert at gmail.com
Thu Jun 4 16:56:48 EDT 2009

I should update after reading the thread Sebastian linked:

The current 1.3 version of numpy (don't know about previous versions) uses
the optimized Atlas BLAS routines for numpy.dot() if numpy was compiled with
these libraries. I've verified this on linux only, thought it shouldnt be
any different on windows AFAIK.


On Thu, Jun 4, 2009 at 4:54 PM, Chris Colbert <sccolbert at gmail.com> wrote:

> Sebastian is right.
> Since Matlab r2007 (i think that's the version) it has included support for
> multi-core architecture. On my core2 Quad here at the office, r2008b has no
> problem utilizing 100% cpu for large matrix multiplications.
> If you download and build atlas and lapack from source and enable parrallel
> threads in atlas, then compile numpy against these libraries, you should
> achieve similar if not better performance (since the atlas routines will be
> tuned to your system).
> If you're on Windows, you need to do some trickery to get threading to work
> (the instructions are on the atlas website).
> Chris
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20090604/fb0ca13f/attachment.html>

More information about the NumPy-Discussion mailing list