[gmx-users] 2018-beta1: PME/GPU performance question

[Szilárd Páll]

Hi Jochen,

Short answer: (most likely) it is due to the large difference in the
amount of bonded work (relative to the total step time). Does CHARMM36
use UB?

Cheers,
--
Szilárd


On Thu, Nov 30, 2017 at 5:33 PM, Jochen Hub <jhub at gwdg.de> wrote:
> Dear all,
>
> I have a question on the performance of the new PME-on-GPU code (2018-beta1)
> on a Xeon 12-core / GTX 1080 node (Cuda 8, gcc 4.85).
>
> With a 84 kAtoms system, I get that the simulations do not benefit from a
> strong CPU any more. See, using 6 Xeon cores with a GTX 1080 is sufficient.
>
> #CPU  ns/day
>  2    92.88
>  4   113.18
>  6   123.36
>  8   122.62
> 10   125.76
> 12   128.84
>
> (This is nice, as we can buy cheap CPUs).
>
> (with pinning, pinstride 1, one GPU, -ntmpi 1)
>
> On a small system (Charmm36 lipid patch, 30 kAtoms), in contrast, the
> simulations strongly benefit from more CPU cores.
>
> #CPU  ns/day
>  4    84.11
>  6   119.24
>  8   150.84
> 10   159.63
> 12   171.30
>
> Is this the expected behaviour? Do you know why?
>
> Thank you for any hints,
> Jochen
>
> --
> ---------------------------------------------------
> Dr. Jochen Hub
> Computational Molecular Biophysics Group
> Institute for Microbiology and Genetics
> Georg-August-University of Göttingen
> Justus-von-Liebig-Weg 11, 37077 Göttingen, Germany.
> Phone: +49-551-39-14189
> http://cmb.bio.uni-goettingen.de/
> ---------------------------------------------------
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