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

2013-04-19 Thread Neal Becker
What sorts of functions take advantage of MKL?

Linear Algebra (equation solving)?

Something like dot product?

exp, log, trig of matrix?

basic numpy arithmetic? (add matrixes)

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

2013-04-19 Thread Matthieu Brucher
Hi,

I think you have at least linear algebra (lapack) and dot. Basic
arithmetics will not benefit, for expm, logm... I don't know.

Matthieu


2013/4/19 Neal Becker ndbeck...@gmail.com

 What sorts of functions take advantage of MKL?

 Linear Algebra (equation solving)?

 Something like dot product?

 exp, log, trig of matrix?

 basic numpy arithmetic? (add matrixes)

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

2013-04-19 Thread Neal Becker
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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Re: [Numpy-discussion] what do I get if I build with MKL?

2013-04-19 Thread Matthieu Brucher
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 ndbeck...@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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Re: [Numpy-discussion] what do I get if I build with MKL?

2013-04-19 Thread KACVINSKY Tom
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-boun...@scipy.org 
[mailto:numpy-discussion-boun...@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 ndbeck...@gmail.commailto:ndbeck...@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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Re: [Numpy-discussion] what do I get if I build with MKL?

2013-04-19 Thread 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.kacvin...@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-boun...@scipy.org [mailto:
 numpy-discussion-boun...@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 ndbeck...@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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Re: [Numpy-discussion] what do I get if I build with MKL?

2013-04-19 Thread Xavier Barthelemy
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.bruc...@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.kacvin...@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-boun...@scipy.org [mailto:
 numpy-discussion-boun...@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 ndbeck...@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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