[Numpy-discussion] numarray and ATLAS

[Todd Miller]

On Sat, 2004-10-16 at 07:27, Francesc Alted wrote:
> A Divendres 15 Octubre 2004 19:03, Francesc Alted va escriure:
> > >>> import timeit
> > >>> t1 = timeit.Timer("m3=numarray.dot(m1,m2)", "import numarray;dim1=500;m1=numarray.arange(dim1*dim1,shape=(dim1,dim1), type=numarray.Float32);m2=numarray.arange(dim1*dim1,shape=(dim1,dim1), type=numarray.Float32)")
> > >>> t1.repeat(3,10)
> > [3.7274820804595947, 3.8542821407318115, 3.7117569446563721]
> > 
> > However, Numeric seems to get it:
> > 
> > >>> t3 = timeit.Timer("m3=Numeric.dot(m1,m2)", "import Numeric;dim1=500;m1=Numeric.arange(dim1*dim1, typecode='f');Numeric.reshape(m1, (dim1,dim1));m2=Numeric.arange(dim1*dim1,typecode='f');Numeric.reshape(m2,(dim1,dim1))")
> > >>> t3.repeat(3,10)
> > [0.0093162059783935547, 0.0096318721771240234, 0.0092968940734863281]
> > 
> > i.e. almost 300 faster than numarray
> 
> Ooops! The Numeric test had a bug on it. The correct test would be:
> 
> >>> t3 = timeit.Timer("m3=Numeric.dot(m1,m2)", "import Numeric;dim1=500;m1=Numeric.arange(dim1*dim1, typecode='f');m1=Numeric.reshape(m1, (dim1,dim1));m2=Numeric.arange(dim1*dim1,typecode='f');m2=Numeric.reshape(m2,(dim1,dim1))")
> >>> t3.repeat(3,10)
> [0.47363090515136719, 0.47403502464294434, 0.47770595550537109]
> 
> which is 8 times faster, more or less, than numarray (or Numeric) without
> ATLAS.
> 
> Just to clarify things ;)

Hi Francesc,

I don't think numarray dot() will pick up any boost at all from ATLAS
because it's not written to do it.   Besides that,  there are two
performance problems I know of with numarray's dot() which may dominate
or dilute any ATLAS benefits:

1. dot() requires array creation.

2. dot() requires array copies.

Because it has a class hierarchy and a memory buffer object,  numarray
is at a disadvantage for (1).  (2) just hasn't been optimized yet for
noncontiguous arrays which (I think) are always present when dot()
starts with two contiguous array parameters.

Regards,
Todd