On Tue, 15 Sep 2015 17:52:02 +0200 Hanno Klemm <kl...@phys.ethz.ch> wrote:
> > Hi, > > I am a newbie with regards to GPU computations and before embarking on > trying to put a calculation onto the GPU, I wanted to ask if there is a > significant uplift in execution speed likely for this scenario and how > to best go about this in pyCuda. > > I have a problem where I have to calculate the probability density of a > few multidimensional Gaussians (order of 10) for many vectors (hundreds > of thousands to millions). The length of the vectors is usually in the > order of 100-600. > > Currently I am doing this in Python with numpy (backed by MKL). I > pre-compute the covariance matrices and their determinants and then I > calculate Does your input data fit in the memory of the GPU ? if so, speed ups of ~100x is probably achievable, (better then 10x) even with an "old Fermi" The algo does not look that difficult. Cheers, Jerome _______________________________________________ PyCUDA mailing list PyCUDA@tiker.net http://lists.tiker.net/listinfo/pycuda
