3 ms·
They'd probably get a 3X speedup (at least) just by moving to a compiled language. False. The bottleneck is matrix multiplication. numpy uses a BLAS library t
by bravura 17y ago
They'd probably get a 3X speedup (at least) just by moving to a compiled language.
False. The bottleneck is matrix multiplication.
numpy uses a BLAS library to do matrix multiplication, and most BLAS libraries are written in a compiled language.
Hence, you can improve speed by improving your matrix multiplication. Either use a faster BLAS implementation, like goto BLAS (http://www.tacc.utexas.edu/resources/software/ http://www.tacc.utexas.edu/resources/software/), or do your matrix multiplication on a faster processor, like a GPU.
- melonakos 17y agoYou can use Jacket for GPU matrix multiply in MATLAB and a host of other GPU accelerated functions (see http://www.accelereyes.com http://www.accelereyes.com).
- cudamatUser1 17y agoJacket would be a great alternative to CUDAMat and Theano if it didn't cost an arm and a leg (matlab is pricey too), was in python, was released under an open source license, and didn't suck.
- dgibsontx 16y agoHave you looked at pricing lately on Jacket? 50% reduction in March. If you are academic even deeper. Just curious