Hi all,
I found something today a bit unpleasant: if you install numeric without any BLAS support, 'matrixmultiply is dot==True', so they are fully interchangeable. However, to my surprise, if you build numeric with the blas optimizations, they are NOT identical. The reason is a bug in Numeric.py. After defining dot, the code reads:
#This is obsolete, don't use in new code matrixmultiply = dot
and at the very end of the file, we have:
# try to import blas optimized dot, innerproduct and vdot, if available try: from dotblas import dot, innerproduct, vdot except ImportError: pass
Obviously this means that matrixmultiply is stuck with the _old_ definition of dot, and does not benefit from the blas optimizations. This is BAD, as for a 1024x1024 matrix the difference is staggering:
planck[Numeric]> pylab
In [1]: a=rand(1024,1024)
In [2]: b=rand(1024,1024)
In [3]: from IPython.genutils import timing
In [4]: timing 1,dot,a,b ------> timing(1,dot,a,b) Out[4]: 0.55591500000000005
In [5]: timing 1,matrixmultiply,a,b ------> timing(1,matrixmultiply,a,b) Out[5]: 68.142640999999998
In [6]: _/__ Out[6]: 122.57744619231356
Pretty significant difference...
The fix is trivial. In Numeric.py, at the very end of the file, this part:
# try to import blas optimized dot, innerproduct and vdot, if available try: from dotblas import dot, innerproduct, vdot except ImportError: pass
should read instead:
# try to import blas optimized dot, innerproduct and vdot, if available try: from dotblas import dot, innerproduct, vdot matrixmultiply = dot #### <<<--- NEW LINE except ImportError: pass
I just checked and the problem still exists in Numpy 23.4.
Cheers,
f