[Numpy-discussion] dot() performance depends on data?
Charles R Harris
Fri Sep 10 19:47:48 CDT 2010
On Fri, Sep 10, 2010 at 6:41 PM, David Cournapeau <email@example.com>wrote:
> On Sat, Sep 11, 2010 at 2:57 AM, Charles R Harris
> <firstname.lastname@example.org> wrote:
> > On Fri, Sep 10, 2010 at 11:36 AM, Hagen Fürstenau <email@example.com>
> > 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.
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