[SciPy-user] Advantages of Intel's MKL
nwagner at iam.uni-stuttgart.de
Sat Dec 9 01:04:28 CST 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
>> 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
> than NumPy's "LAPACK lite", so you really want to use
>one of these
> Pro's of MKL (mostly vs ATLAS):
> Don't have to build the library.
> Runtime detection of CPU. Useful if you have a single
> installation shared over NFS to a bunch of heterogenous
> 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
> OMP_NUM_THREADS. ATLAS also has support for pthreads
> Probably about as fast as ATLAS.
> Con's of MKL:
> Costs money if the non-commercial Linux license doesn't
> you and/or doesn't suit your needs (e.g. you need to run
> Those are the points that jump out for me. I'm sure
>there are others.
> SciPy-user mailing list
> SciPy-user at scipy.org
Thank you for your notes. If you have installed both,
ATLAS and MKL, which library will be used by default ?
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