As we know by now GPUs can run some problems many times faster than CPUs (e.g. http://folding.stanford.edu/English/FAQ-highperformance). From what I understand GPUs are useful only with certain classes of numerical problems and discretization schemes, and of course the code must be rewritten to take advantage of the GPU.
I'm part of a group that is purchasing our first beowulf cluster for a climate model and an estuary model using Chombo (http://seesar.lbl.gov/ANAG/chombo/). Getting up to speed (ha) on clusters I started wondering if packages like Chombo, and numerical problems generally, would be rewritten to take advantage of GPUs and GPU clusters, if the latter exist. From decades ago when I actually knew something I vaguely recall that PDEs can be classed as to parabolic, hyperbolic or elliptic. And there are explicit and implicit methods in time. Are some of these classifications much better suited for GPUs than others? Given the very substantial speed improvements with GPUs, will there be a movement to GPU clusters, even if there is a substantial cost in problem reformulation? Or are GPUs only suitable for a rather narrow range of numerical problems? Ralph Finch, P.E. California Dept. of Water Resources Delta Modeling Section, Bay-Delta Office Room 215-13 1416 9th Street Sacramento CA 95814 916-653-7552 [EMAIL PROTECTED] _______________________________________________ Beowulf mailing list, Beowulf@beowulf.org To change your subscription (digest mode or unsubscribe) visit http://www.beowulf.org/mailman/listinfo/beowulf
