On Sat, Mar 15, 2008 at 2:48 PM, Gnata Xavier <[EMAIL PROTECTED]> wrote: > Hi, > > Numpy is great : I can see several IDL/matlab projects switching to numpy :) > However, it would be soooo nice to be able to put some OpenMP into the > numpy code. > > It would be nice to be able to be able to use several CPU using the > numpy syntax ie A=sqrt(B). > > Ok, we can use some inline C/C++ code but it is not so easy. > Ok, we can split the data over several python executables (one per CPU) > but A=sqrt(B) is so simple... > > numpy + recent gcc with OpenMP --> :) ? > Any comments ?
Eric Jones tried to use multithreading to split the computation of ufuncs across CPUs. Ultimately, the overhead of locking and unlocking made it prohibitive for medium-sized arrays and only somewhat disappointing improvements in performance for quite large arrays. I'm not familiar enough with OpenMP to determine if this result would be applicable to it. If you would like to try, we can certainly give you pointers as to where to start. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
