[SciPy-user] Advantages of Intel's MKL

Nils Wagner 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 
>>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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