[Numpy-discussion] algorithm, optimization, or other problem?
Brian Blais
bblais at bryant.edu
Thu Feb 23 09:35:11 CST 2006
Nadav Horesh wrote:
> It is slower.
>
> I did a little study on this issue since I got into the issue of
> algorithms that can not be easily vectorized (like this one).
> On my PC an outer loop step took initially 17.3 seconds, and some
> optimization brought it down to ~11 seconds. The dot product consumed
> about 1/3 of the time. I estimate that objects creation/destruction
> consumes most of the cpu time. It seems that this way comes nowhere near
> cmex speed. I suspect that maybe blitz/boost may bridge the gap.
>
yeah, I realized that pure python would be too slow, because I ran into the exact
same problem with matlab scripting. these time-dependent loops are really a mess
when it comes to speed optimization.
After posting to the Pyrex list, someone pointed out that my loop variables had not
been declared as c datatypes. so, I had loops like:
for it from 0 <= it <= 1000:
for i from 0 <= i <= 100:
(stuff)
and the "it" and "i" were being treated, due to my oversight, as python variables.
for speed, you need to have all the variables in the loop as c datatypes. just
putting a line in like:
cdef int it,i
increases the speed from 8 seconds per block to 0.2 seconds per block, which is
comparable to the mex.
I learned that I have to be a bit more careful! :)
thanks,
Brian Blais
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