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

[Matthieu Brucher]

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 at 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 at scipy.org [mailto:
> numpy-discussion-bounces at 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 at 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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