On 02/20/2013 10:18 AM, Sergio wrote: > Dag Sverre Seljebotn <d.s.seljebotn <at> astro.uio.no> writes: > >> >> On 02/18/2013 05:26 PM, rif wrote: >>> I have no answer to the question, but I was curious as to why directly >>> calling the cblas would be 10x-20x slower in the first place. That >>> seems surprising, although I'm just learning about python numerics. >> >> The statement was that directly (on the Cython level) calling cblas is >> 10x-20x slower than going through the (slow) SciPy wrapper routines. >> That makes a lot of sense if the matrices are smalle nough. >> >> Dag Sverre > > Soory for expressing myself badly. > > I need to call cblas directly from cython, because it is faster. > > I use matrix multiplication in a tight loop. > > Let the speed with the standard dot be 100, > > Speed using the scipy.linalg.blas routines is 200 > > And speed calling directly atlas from cython is 2000 > > Which is reasonable, since this avoids any type checking. > > The point is that I need to ship an extra atlas lib to do so in windows, > notwithstanding the fact that numpy/scipy incorporate atlas in the windows > build. > > I was wondering if there is a way to build numpy/scipy with atlas dynamically > linked into it, in order to be able to share the atlas libs between my code > and > scipy.
You could also look into OpenBLAS, which is easier to build and generally faster than ATLAS. (But alas, not supported by NumPy/SciPY AFAIK.) Dag Sverre _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
