(sending again) Hi,
I'm the student doing the project. I have a blog here, which contains some initial performance numbers for a couple test ufuncs I did: http://numcorepy.blogspot.com It's really too early yet to give definitive results though; GSoC officially starts in two days :) What I'm finding is that the existing ufuncs are already pretty fast; it appears right now that the main limitation is memory bandwidth. If that's really the case, the performance gains I'll get will be through cache tricks (non-temporal loads/stores), reducing memory accesses and using multiple cores to get more bandwidth. Another alternative we've talked about, and I (more and more likely) may look into is composing multiple operations together into a single ufunc. Again the main idea being that memory accesses can be reduced/eliminated. Andrew dmitrey wrote: > hi all, > has anyone already tried to compare using an ordinary numpy ufunc vs > that one from corepy, first of all I mean the project > http://socghop.appspot.com/student_project/show/google/gsoc2009/python/t124024628235 > > It would be interesting to know what is speedup for (eg) vec ** 0.5 or > (if it's possible - it isn't pure ufunc) numpy.dot(Matrix, vec). Or > any another example. > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
