RE: [Numpy-discussion] Re: Re-implementation of Python Numerical arrays (Numeric) available for download
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Perry Greenfield [mailto:perry@stsci.edu] wrote:
Well, here's my application. I do data mining work, and one of the techniques I want to use Numpy for is to implement robust regression algorithms like least-trimmed-squares. Now for a k-variable regression, the best-of-breed algorithm for this involves taking hundreds of thousands of k-element samples and calculating the fitting hyperplane through them. Small matrix performance is thus something this program lives or dies by, and right now it seems like 'dies' is the right measure -- it is about 10x slower than the Gauss program that does the same thing. :( When I profiled it seems like Numpy is spending almost all of its time in _castCopyAndTranspose. Switching to the Intel MKL LAPACK had no performance effect, but changing _castCopyAndTranspose into a C function was a 20% speed increase. If Numpy2 is even slower on small matrices I'd have to give up using it, and that's a shame: it's a *much* nicer environment than Gauss is. -- Neel Krishnaswami neelk@cswcasa.com
participants (1)
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Krishnaswami, Neel