Fri, 03 Oct 2008 18:59:02 +0200, Gael Varoquaux wrote: > I am doing a calculation where one call numpy.dot ends up taking 90% of > the time (the array is huge: (61373, 500) ). > > Any chance I can make this faster? I would believe BLAS/ATLAS would be > behind this, but from my quick analysis (ldd on > numpy/core/multiarray.so) it doesn't seem so. Have I done something > stupid when building numpy (disclaimer: I am on a system I don't know > well --Mandriva--, so I could very well have done something stupid).
AFAIK, multiarray.so is never linked against ATLAS. The accelerated dot implementation is in _dotblas.so, and can be toggled with alterdot/ restoredot (but the ATLAS one should be active by default). >>> numpy.dot.__module__ 'numpy.core._dotblas' Are your arrays appropriately contiguous? Numpy needs to copy the data if they are not; though I'm not sure if this could account for what you see. -- Pauli Virtanen _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
