Have a look at this: http://ambermd.org/gpus/
"In other words on a 4 GPU machine you can run a total of two by two GPU
jobs, one on GPUs 0 and 1 and one on GPUs 2 and 3. Running a calculation
across more than 2 GPUs will result in peer to peer being switched off
which will likely mean the calculation will run slower than if it had
been run on a single GPU. To see which GPUs in your system can
communicate via peer to peer you can run the 'gpuP2PCheck' program you
built above."
On 05/04/2017 10:26 AM, Meng Wu wrote:
> Dear All,
> I have a problem about GPUs parallel met these days. There are 4 GPUs/node in our lab, when I use two of them ("export CUDA_VISIBLE_DEVICES=0,1/2,3 mpirun -np 2 pmemd.cuda.MPI -O ..." ), the speed is normal; but when I use all("export CUDA_VISIBLE_DEVICES=0,1,2,3 mpirun -np 4 pmemd.cuda.MPI -O ..."") , the speed dropped dramatically. I don't know what's the problem in and how to deal with it if I want to use 4 GPUs in parallel to get a higher speed.
>
> Any suggestions would be greatly appreciated.Thank you in advance!
>
> All the best,
> Wu Meng
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--
M.Sc. Andreas Tosstorff
Lehrstuhl für Pharmazeutische Technologie und Biopharmazie
Department Pharmazie
LMU München
Butenandtstr. 5-13 ( Haus B)
81377 München
Germany
Tel.: +49 89 2180 77059
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Received on Thu May 04 2017 - 02:30:02 PDT
