On Fri, Sep 10, 2010 at 6:41 PM, David Cournapeau <[email protected]>wrote:
> On Sat, Sep 11, 2010 at 2:57 AM, Charles R Harris > <[email protected]> wrote: > > > > > > On Fri, Sep 10, 2010 at 11:36 AM, Hagen Fürstenau <[email protected]> > > wrote: > >> > >> Hi, > >> > >> I'm multiplying two 1000x1000 arrays with numpy.dot() and seeing > >> significant performance differences depending on the data. It seems to > >> take much longer on matrices with many zeros than on random ones. I > >> don't know much about optimized MM implementations, but is this normal > >> behavior for some reason? > >> > > > > Multiplication by zero used to be faster than multiplication by random > > numbers. However, modern hardware and compilers may have changed that to > > pretty much a wash. More likely you are seeing cache issues due to data > > localization or even variations in the time given the thread running the > > multiplication. > > That's actually most likely a denormal issue. The a and b matrix (from > mm.py) have many very small numbers, which could cause numbers to be > denormal. Maybe a has more denormals than b. Denormal cause > significant performance issues on Intel hardware at least. > > Unfortunately, we don't have a way in numpy to check for denormal that > I know of. > > The matrices could be scaled up to check that. Chuck
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