[Numpy-discussion] performance matrix multiplication vs. matlab

[Sebastian Walter]

On Fri, Jun 5, 2009 at 11:58 AM, David
Cournapeau<david at ar.media.kyoto-u.ac.jp> wrote:
> Sebastian Walter wrote:
>> On Thu, Jun 4, 2009 at 10:56 PM, Chris Colbert<sccolbert at 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
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