On 12/29/11 10:37 PM, Jaidev Deshpande wrote:
Hi!
Along with test coverage, have any of you considered any systematic
monitoring of NumPy performance?
I'm mildly obsessed with performance and benchmarking of NumPy. I used
to use a lot of MATLAB until a year back and I tend to compare Python
performance with it all the time. I generally don't feel happy until
I'm convinced that I've extracted the last bit of speed out of my
Python code.
I think the generalization of this idea is more or less equivalent to
performance benchmarking. Of course, I know there's a lot more than
'MATLAB vs Python' to it. I'd be more than happy to be involved. GSoC
or otherwise.
Where do I start?
We've recently had a discussion about more intelligent timeit commands
and timing objects in Python/Sage. People here might find the
discussion interesting, and it might also be interesting to collaborate
on code. The basic idea was a much smarter timeit command that uses
more intelligent statistics and presents a much more comprehensive look
at the timing information.
Here is the discussion:
https://groups.google.com/forum/#!topic/sage-devel/8lq3twm9Olc
Here is our ticket tracking the issue:
http://trac.sagemath.org/sage_trac/ticket/12168
Here are some examples of the analysis: http://sagenb.org/home/pub/3857/
I've CCd the sage-devel list as well, which is where our discussion
happened.
Thanks,
Jason
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