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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