[SciPy-user] about weave performance evaluation

Pau Gargallo pau.gargallo at gmail.com
Thu Nov 3 03:43:44 CST 2005


that was really clear,
thank you guys,

pau

On 10/31/05, Prabhu Ramachandran <prabhu_r at users.sf.net> wrote:
> >>>>> "Dan" == Dan Christensen <jdc at uwo.ca> writes:
>
>     >> 1- i don't understand the 25 fold increase of the last sentence
>     >> of the cited text. Shouldn't we conclude that the use of
>     >> numeric speeds up by a factor 100?
>
>     Dan> I think 25 is correct.  When the numeric method gets err <
>     Dan> eps, it will be farther from the correct solution than when
>     Dan> the pure python method gets err < eps, since it is in effect
>     Dan> taking smaller steps.  To get as accurate an answer, you'd
>     Dan> have to adjust eps to make the code run approximately twice
>     Dan> as long.
>
> Just to explain this a little more clearly, the issue is that the pure
> Python code will converge (in terms of number of iterations taken)
> twice as fast as the Numeric code.  I.e. if the pure Python code takes
> x iterations to converge, the Numeric code will take 2*x iterations
> (because it uses temporaries).  Therefore, if you want to compare the
> time taken for convergence, then you will end up with only a 25 fold
> speed increase instead of the 50 fold increase.  If OTOH, you merely
> want to compare the time taken for 1 single iteration then you get a
> 50 fold speed increase by using Numeric arrays.
>
>     >> 2- in the final comparison the time used by numeric is
>     >> 29.3s. If we want to compare the performance between the
>     >> different implementations, should we divide this time by 2 ?
>
> It depends.  If the timing criterion is convergence to a particular
> error then divide by 2.  If it is just to measure pure performance of
> 100 iterations on a 500x500 problem then the number should be left as
> such.  My intention was to just show pure performance so readers get a
> feel for the kind of speed improvement they get with different options
> for a similar calculation.
>
> cheers,
> prabhu
>
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