A Friday 16 October 2009 14:02:03 David Cournapeau escrigué: > On Fri, Oct 16, 2009 at 8:53 PM, Pauli Virtanen <pav...@iki.fi> wrote: > > Fri, 16 Oct 2009 12:07:10 +0200, Francesc Alted wrote: > > [clip] > > > >> IMO, NumPy can be improved for unaligned data handling. For example, > >> Numexpr is using this small snippet: > >> > >> from cpuinfo import cpu > >> if cpu.is_AMD() or cpu.is_Intel(): > >> is_cpu_amd_intel = True > >> else: > >> is_cpu_amd_intel = False > >> > >> for detecting AMD/Intel architectures and allowing the code to avoid > >> memcpy() calls for the unaligned arrays. > >> > >> The above code uses the excellent ``cpuinfo.py`` module from Pearu > >> Peterson, which is distributed under NumPy, so it should not be too > >> difficult to take advantage of this for avoiding unnecessary copies in > >> this scenario. > > > > I suppose this kind of check is easiest to do at compile-time, and > > defining a -DFORCE_ALIGNED? This wouldn't cause performance penalties for > > those architectures for which they are not necessary. > > I wonder whether we could switch at runtime (import time) - it could > be useful for testing. > > That being said, I agree that the cpu checks should be done at compile > time - we had quite a few problems with cpuinfo in the past with new > cpu/unhandled cpu, I think a compilation-based method is much more > robust (and simpler) here. There are things where C is just much > easier than python :)
Agreed. I'm relaying in ``cpuinfo.py`` just because it provides what I need in an easy way. BTW, the detection of AMD/Intel (just the vendor) processors seems to work flawlessly for the platforms that I've checked (but I suppose that you are talking about other characteristics, like SSE version, etc). -- Francesc Alted _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
