[gmx-users] strange GPU load distribution

[Mark Abraham]

Hi,

I don't see any problems there, but I note that there are run-time settings
for the driver/runtime to block until no other process is using the GPU,
which may be a contributing factor here.

As Justin noted, if your EM jobs would use a build of GROMACS that is not
configured to have access to the GPUs, then there can be no problem. I
recommend you do that if you want to continue sharing this node between GPU
and non-GPU jobs. There has long been the principle that users must take
active steps to keep GROMACS processes away from each other when sharing
CPU resources, and this is a similar situation.

In the abstract, it would be reasonable to organize mdrun so that we
determine that we might want to use a GPU if we have one before we run the
GPU detection, however that high-level code is in considerable flux in
development branches, and we are highly unlikely to prioritise such a fix
in a stable release branch to suit this use case. I didn't think that some
of the reorganization since 2016 release would have this effect, but
apparently it can. Sorry!

Mark

On Mon, May 7, 2018 at 6:33 AM Alex <nedomacho at gmail.com> wrote:

> Mark,
>
> I am forwarding the response I received from the colleague who prepared
> the box for my GMX install -- this is from the latest installation of
> 2018.1. See text below and please let me know what you think. We have no
> problem rebuilding things, but would like to understand what is wrong
> before we pause all the work.
>
> Thank you,
>
> Alex
>
> "OS Ubuntu 16.04LTS
>
> After checking gcc and kernel-headers were installed I ran the following
>
> #sudo lspci |grep -i nvidia
>
> #curl
>
> http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.1.85-1_amd64.deb
>  > cuda-repo-ubuntu1604_9.1.85-1_amd64.deb
>
> #sudo dpkg -i cuda-repo-ubuntu1604_9.1.85-1_amd64.deb
>
> #sudo apt-key adv
> --fetch-keyshttp://
> developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
>
> #sudo dpkg -i cuda-repo-ubuntu1604_9.1.85-1_amd64.deb
>
> #sudo apt update
>
> #sudo apt upgrade
>
> #sudo /sbin/shutdown -r now
>
> After reboot
>
> #sudo apt-get install cuda
>
> #export PATH=/usr/local/cuda-9.1/bin${PATH:+:${PATH}}
>
> #nvidia-smi
>
> I also compiled the samples in the cuda tree using the Makefile there
> and had no problems."
>
> --
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