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 After defining dot, the code reads: #This is obsolete, don't use in new code matrixmultiply = dot and at the very end of the file, we have: # try to import blas optimized dot, innerproduct and vdot, if available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