[Numpy-discussion] what do I get if I build with MKL?

Xavier Barthelemy xabart@gmail....
Fri Apr 19 18:11:55 CDT 2013


One major advantage you can have using mkl is installing "numexpr"
compiling it with MLK.
That's a strong suggestion to easily use mkl and go faster on common
operations.
Xavier
 On 20/04/2013 1:16 AM, "Matthieu Brucher" <matthieu.brucher@gmail.com>
wrote:

> The graph is a comparison of the dot calls, of course they are better with
> MKL than the default BLAS version ;)
> For the rest, Numpy doesn't benefit from MKL, scipy may if they call
> LAPACK functions wrapped by Numpy or Scipy (I don't remember which does the
> wrapping).
>
> Matthieu
>
>
> 2013/4/19 KACVINSKY Tom <Tom.KACVINSKY@3ds.com>
>
>>  Looks like the *lapack_lite files have internal calls to dgemm.  I alos
>> found this:
>>
>>
>>
>> http://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl
>>
>>
>>
>> So it looks like numpy/scipy performs better with MKL, regardless of how
>> the MKL routines are called (directly, or via a numpy/scipy interface).
>>
>>
>>
>> Tom
>>
>>
>>
>> *From:* numpy-discussion-bounces@scipy.org [mailto:
>> numpy-discussion-bounces@scipy.org] *On Behalf Of *Matthieu Brucher
>> *Sent:* Friday, April 19, 2013 9:50 AM
>>
>> *To:* Discussion of Numerical Python
>> *Subject:* Re: [Numpy-discussion] what do I get if I build with MKL?
>>
>>
>>
>> For the matrix multiplication or array dot, you use BLAS3 functions as
>> they are more or less the same. For the rest, nothing inside Numpy uses
>> BLAS or LAPACK explicitelly IIRC. You have to do the calls yourself.
>>
>>
>>
>> 2013/4/19 Neal Becker <ndbecker2@gmail.com>
>>
>> KACVINSKY Tom wrote:
>>
>> > You also get highly optimized BLAS routines, like dgemm and degemv.
>>
>> And does numpy/scipy just then automatically use them?  When I do a matrix
>> multiply, for example?
>>
>>
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