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" <[email protected]> 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 <[email protected]> > >> 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:* [email protected] [mailto: >> [email protected]] *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 <[email protected]> >> >> 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? >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> [email protected] >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> >> >> >> >> -- >> Information System Engineer, Ph.D. >> Blog: http://matt.eifelle.com >> LinkedIn: http://www.linkedin.com/in/matthieubrucher >> Music band: http://liliejay.com/ >> >> This email and any attachments are intended solely for the use of the >> individual or entity to whom it is addressed and may be confidential and/or >> privileged. >> >> If you are not one of the named recipients or have received this email in >> error, >> >> (i) you should not read, disclose, or copy it, >> >> (ii) please notify sender of your receipt by reply email and delete this >> email and all attachments, >> >> (iii) Dassault Systemes does not accept or assume any liability or >> responsibility for any use of or reliance on this email. >> >> For other languages, go to http://www.3ds.com/terms/email-disclaimer >> >> _______________________________________________ >> NumPy-Discussion mailing list >> [email protected] >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > > -- > Information System Engineer, Ph.D. > Blog: http://matt.eifelle.com > LinkedIn: http://www.linkedin.com/in/matthieubrucher > Music band: http://liliejay.com/ > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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