Received from Keith Brown on Wed, Nov 18, 2015 at 10:12:13PM EST: > I am trying to calculate the dot product. > > something like this, > > A=np.array(([1,2,3],[4,5,6])).astype(np.float64) > print np.dot(A,A.T) > > Instead, I would like to use GEMM (not batched I suppose). > > My A can be large. Something like (800000,3). So, it would seem GPU > could help me a lot here.
The skcuda.linalg.dot() function in scikit-cuda uses the CUBLAS GEMM functions when both arguments have more than one dimension and sufficient GPU memory is available. -- Lev Givon Bionet Group | Neurokernel Project http://lebedov.github.io/ http://neurokernel.github.io/ _______________________________________________ PyCUDA mailing list PyCUDA@tiker.net http://lists.tiker.net/listinfo/pycuda
