Hi Robert,
The easiest way is to put the GPUs into compute exclusive mode. This
can be accomplished using the nvidia-smi tool and ensures that only one
process can use a GPU at any given time.
Alternatively, you can set
[backend-cuda]
device-id = local-rank
which will assign the first MPI rank on the node to the first CUDA
device, and so on and so forth. This approach does not require that the
GPUs be in compute exclusive mode.
Regards, Freddie.
On 28/02/2017 01:15, Robert Sawko wrote:
Dear All,
I just installed PyFR on our GPU cluster - what a breeze. I can run your
examples and tutorials with CUDA backend and I can see them being
offloaded to the GPU. Metis also appears to cooperate.
My question is how to configure multiple GPUs on a single node. Is there
a way to make sure that say four processes will run on four different
GPUs exclusively?
Also, would be possible to share a larger case as an example to actually
flood the GPUs with work. I am more than willing to give PyFR a try but
it will take a while for me to develop case setting skills.
Many thanks,
Robert
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