[SciPy-user] Advantages of Intel's MKL
Nils Wagner
nwagner at iam.uni-stuttgart.de
Sat Dec 9 02:04:28 EST 2006
On Sat, 9 Dec 2006 02:04:26 +0200
Albert Strasheim <fullung at gmail.com> wrote:
> Hello all
>
> On Fri, 08 Dec 2006, Nils Wagner wrote:
>
>> Hi all,
>>
>> What are the advantages of Intel's MKL library in
>>connection with
>> numpy/scipy ?
>
> I'll take a stab at this question. Feel free to
>disagree. Mostly I'd
> compare it with ATLAS. Both MKL and ATLAS are orders of
>magnitude faster
> than NumPy's "LAPACK lite", so you really want to use
>one of these
> libraries.
>
> Pro's of MKL (mostly vs ATLAS):
>
> Don't have to build the library.
>
> Runtime detection of CPU. Useful if you have a single
>Python+NumPy
> installation shared over NFS to a bunch of heterogenous
>machines.
> This is quite likely in cluster-type environments where
>you would use
> something like IPython1 -- I have a configuration
>exactly like this to
> deal with 15 machines in our lab.
>
> I think MKL supports multiple cores through OpenMP by
>just setting
> OMP_NUM_THREADS. ATLAS also has support for pthreads
>though.
>
> Probably about as fast as ATLAS.
>
> Con's of MKL:
>
> Costs money if the non-commercial Linux license doesn't
>apply to
> you and/or doesn't suit your needs (e.g. you need to run
>on Windows).
>
> Those are the points that jump out for me. I'm sure
>there are others.
>
> Comments?
>
> Cheers,
>
> Albert
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Thank you for your notes. If you have installed both,
ATLAS and MKL, which library will be used by default ?
Nils
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