On 8-Jul-09, at 6:16 PM, Pauli Virtanen wrote: > Just to tickle some interest, a "pathological" case before > optimization: > > In [1]: import numpy as np > In [2]: x = np.zeros((80000, 256)) > In [3]: %timeit x.sum(axis=0) > 10 loops, best of 3: 850 ms per loop > > After optimization: > > In [1]: import numpy as np > In [2]: x = np.zeros((80000, 256)) > In [3]: %timeit x.sum(axis=0) > 10 loops, best of 3: 78.5 ms per loop
Not knowing a terrible lot about cache optimization, I have nothing to contribute but encouragement. :) Pauli, this is fantastic work! Just curious about regressions: have you tested on any non-x86 hardware? Being a frequent user of an older ppc machine I worry about such things (and plan to give your benchmark a try tomorrow on both ppc and ppc64 OS X). Cheers, David _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
