[Numpy-discussion] Really cruel draft of vbench setup for NumPy (.add.reduce benchmarks since 2011)

[Yaroslav Halchenko]

On Wed, 01 May 2013, Sebastian Berg wrote:
> > btw -- is there something like panda's vbench for numpy?  i.e. where
> > it would be possible to track/visualize such performance
> > improvements/hits?


> Sorry if it seemed harsh, but only skimmed mails and it seemed a bit
> like the an obvious piece was missing... There are no benchmark tests I
> am aware of. You can try:

> a = np.random.random((1000, 1000))

> and then time a.sum(1) and a.sum(0), on 1.7. the fast axis (1), is only
> slightly faster then the sum over the slow axis. On earlier numpy
> versions you will probably see something like half the speed for the
> slow axis (only got ancient or 1.7 numpy right now, so reluctant to give
> exact timings).

FWIW -- just as a cruel first attempt look at

http://www.onerussian.com/tmp/numpy-vbench-20130506/vb_vb_reduce.html

why float16 case is so special?

I have pushed this really coarse setup (based on some elderly copy of
pandas' vbench) to
https://github.com/yarikoptic/numpy-vbench

if you care to tune it up/extend and then I could fire it up again on
that box (which doesn't do anything else ATM AFAIK).   Since majority of
time is spent actually building it (did it with ccache though) it would
be neat if you come up with more of benchmarks to run which you might
think could be interesting/important.

-- 
Yaroslav O. Halchenko, Ph.D.
http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org
Senior Research Associate,     Psychological and Brain Sciences Dept.
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
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