On Fri, Jun 5, 2009 at 11:58 AM, David Cournapeau<da...@ar.media.kyoto-u.ac.jp> wrote: > Sebastian Walter wrote: >> 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.... >> > > Numpy packages on windows do use ATLAS, so I am not sure what you are > referring to ? I'm on debian unstable and my numpy (version 1.2.1) uses an unoptimized blas. I had the impression that most ppl that use numpy are on linux. But apparently this is a misconception.
>On a side note, correctly packaging ATLAS is almost > inherently impossible, since the build method of ATLAS can never produce > the same binary (even on the same machine), and the binary is optimized > for the machine it was built on. So if you want the best speed, you > should build atlas by yourself - which is painful on windows (you need > cygwin). in the debian repositories there are different builds of atlas so there could be different builds for numpy, too. But there aren't.... > > On windows, if you really care about speed, you should try linking > against the Intel MKL. That's what Matlab uses internally on recent > versions, so you would get the same speed. But that's rather involved. How much faster is MKL than ATLAS? > > cheers, > > David > _______________________________________________ > 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