Re: [task #7807] Speed-up of dispersion models for Clustered analysis -- June 15, 2014 - 15:30

> From the other link you gave at
http://permalink.gmane.org/gmane.science.nmr.relax.devel/6248, the
scipy.linalg access to BLAS has the same timing as the C contiguous
arrays passed into numpy.dot().  See
http://docs.scipy.org/doc/numpy/reference/generated/numpy.ascontiguousarray.html
for how to fix this in __init__().

Regards,

Edward



On 15 June 2014 14:59, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx> wrote:
> Hi Ed.
>
> At the wiki, I added some references for faster dot:
> http://wiki.nmr-relax.com/Numpy_linalg
>
> http://www.huyng.com/posts/faster-numpy-dot-product/
>
> from scipy.linalg import fblas as FB
> X = FB.dgemm(alpha=1., a=A, b=B, trans_b=True)
>
>
> 2014-06-15 10:30 GMT+02:00 Edward d Auvergne
> <NO-REPLY.INVALID-ADDRESS@xxxxxxx>:
> > Follow-up Comment #199, task #7807 (project relax):
> >
> >
> > The following python script, to be placed in the base relax directory, and
> > the
> > corresponding log file, demonstrate the speed differences of various dot
> > product operations.  This is to help make the numeric dispersion models
> > faster.
> >
> > The script tests 3 different operations:
> >
> > 1) Sequential dot products (a = dot(b, c); a = dot(a, d)).
> > 2) Chained dot products (a = b.dot(c).dot(d)).
> > 3) Using the out argument to avoid memory allocation and garbage
> > collection
> > (dot(b, c, a); dot(a, d, a)).
> >
> > The timings are:
> >
> > 1) 3.71 s.
> > 2) 4.05 s.
> > 3) 1.99 s.
> >
> > As option 1) is the implementation used in the relax trunk, clearly option
> > 3
> > has the potential to significantly speed up the models.
> >
> >
> > (file #21021, file #21022)
> >     _______________________________________________________
> >
> > Additional Item Attachment:
> >
> > File name: dot_speed.py                   Size:2 KB
> > File name: dot_speed.log                  Size:0 KB
> >
> >
> >     _______________________________________________________
> >
> > Reply to this item at:
> >
> >   <http://gna.org/task/?7807>
> >
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