On Thu, Jun 4, 2009 at 10:56 PM, Chris Colbert<sccolb...@gmail.com> wrote: > 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.
in the best of all possible worlds this would be done by a package maintainer.... > > chris > > On Thu, Jun 4, 2009 at 4:54 PM, Chris Colbert <sccolb...@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 >> >> > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion