[Numpy-discussion] dot() performance depends on data?

[David Cournapeau]

On Sat, Sep 11, 2010 at 2:57 AM, Charles R Harris
<charlesr.harris at gmail.com> wrote:
>
>
> On Fri, Sep 10, 2010 at 11:36 AM, Hagen Fürstenau <hagen at zhuliguan.net>
> 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.

cheers,

David