> Sure. Specially because NumPy is all about embarrasingly parallel problems > (after all, this is how an ufunc works, doing operations > element-by-element). > > The point is: are GPUs prepared to compete with a general-purpose CPUs in > all-road operations, like evaluating transcendental functions, conditionals > all of this with a rich set of data types? I would like to believe that this > is the case, but I don't think so (at least not yet).
A lot of nVidia's SDK functions is not done on GPU. There are some functions that they provide where the actual computation is done on the CPU, not on the GPU (I don't have an example here, but nVidia's forum is full of examples ;)) Matthieu -- Information System Engineer, Ph.D. Website: http://matthieu-brucher.developpez.com/ Blogs: http://matt.eifelle.com and http://blog.developpez.com/?blog=92 LinkedIn: http://www.linkedin.com/in/matthieubrucher _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
