I guess the short answer is "you don't". Apart from what Andreas sent, I have two GTX-1070 GPUs and the best parallelization performance I could achieve so far was 30% performance for the second card. Benchmarks at the Amber website suggest a similar picture:
http://ambermd.org/gpus/benchmarks.htm
In addition to software limitations, by running four GPUs at once you're likely to fry your machine (assuming all the cards are on a single unit) due to excessive amounts of heat generated, or surpass power supply capacity. For a membrane protein system, 2 GPUs were enough to cause our unit to shut down, although it might not be the case necessarily for everyone.
Best,
Alican
________________________________________
From: Andreas Tosstorff <andreas.tosstorff.cup.uni-muenchen.de>
Sent: Thursday, May 4, 2017 5:21 AM
To: amber.ambermd.org
Subject: Re: [AMBER] GPUs parallel problem
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
> _______________________________________________
> AMBER mailing list
> AMBER.ambermd.org
> http://lists.ambermd.org/mailman/listinfo/amber
--
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
