Hi On Saturday 29 August 2009 09:42:36 amjad ali wrote: > I perceive following computing setups for GP-GPUs, > > 1) ONE PC with ONE CPU and ONE GPU, > > 2) ONE PC with more than one CPUs and ONE GPU > > 3) ONE PC with one CPU and more than ONE GPUs > > 4) ONE PC with TWO CPUs (e.g. Xeon Nehalems) and more than ONE GPUs > (e.g. Nvidia C1060)
I think no one will be able to answer your question correctly. It will all boil down how your usage scenario will be, e.g. if your codes run only on the GPUs and you have hardly to do anything except providing the initial data to the GPUs I think you might even go to the extreme with a single box and 7 GPUs in it along with a quad CPU. On the other extreme you have code where only a fraction of the code (say 20%) can be put onto the GPU you will probably have to aim at a different CPU to GPU ratio. > > 5) Cluster of PCs with each node having ONE CPU and ONE GPU > > 6) Cluster of PCs with each node having more than one CPUs and ONE GPU > > 7) Cluster of PCs with each node having ONE CPU and more than ONE GPUs > > 8) Cluster of PCs with each node having more than one CPUs and more > than ONE GPUs. > Same as above, it highly depends what will run on the cluster. > > > IMPORTANT QUESTION: Will a cuda based program will be equally good for > some/all of these setups or we need to write different CUDA based programs > for each of these setups to get good efficiency? Not much experience here, sorry Carsten _______________________________________________ Beowulf mailing list, [email protected] sponsored by Penguin Computing To change your subscription (digest mode or unsubscribe) visit http://www.beowulf.org/mailman/listinfo/beowulf
