[gmx-users] Number of Xeon cores per GTX 1080Ti
pall.szilard at gmail.com
Thu Mar 29 20:57:28 CEST 2018
For that particular benchmark I only measured performance with
1,2,4,8,16 cores with a few different kinds of GPUs. It would be easy
to do the runs on all possible core counts with increments of 1, but
that won't tell a whole lot more than what the performance is of a run
using a E5-2620 v4 CPU (with some GPUs) on a certain core count. Even
extrapolating from that 2620 to a E5-2630 v4 and expecting to get a
good estimate is tricky (given that the latter has 25% more cores for
the same TDP!), let alone to any 26xxv4 CPU or the current-gen Skylake
chips which have different performance characteristics.
As Mark notes, there are some mdp option as well as some system
charateristics that will have a strong influence on performance -- if
tens of % is something you consider "strong" (some users are fine to
be within a 2x ballpark :).
What's worth considering is to try to avoid ending up strongly CPU or
GPU bound from start. That may admittedly could be a difficult task
you would run e.g. both biased MD with large pull groups and all-bonds
constraints with Amber FF on large-ish (>100k) systems as well as
vanilla MD with CHARMM FF with small-ish (<25k) systems. On the same
hardware the former will be more prone to be CPU-bound while the
latter will have relatively more GPU-heavy workload.
There are many factors that influence the performance of a run and
therefore giving a the one right answer to your question is not really
possible. What can say is that 7-10 "core-GHz" per fast Pascal GPU is
generally sufficient for "typical" protein simulations to run at >=85%
On Wed, Mar 28, 2018 at 4:31 AM, Mark Abraham <mark.j.abraham at gmail.com> wrote:
> On Tue, Mar 27, 2018 at 6:43 PM Jochen Hub <jhub at gwdg.de> wrote:
>> Dear Gromacs community, dear Mark,
>> Mark showed in the webinar today that having more than 8 Xeon E5-26XXv4
>> cores does not help when using a GTX 1080Ti and PME on the GPU.
> ... for that particular simulation system.
>> Unfortunately, there were no data points between 4 and 8 CPU cores,
>> hence it was not clear at which #cores the performance actually levels
>> off. With a GTX 1080 (not Ti) I once found that having more than 5 Xeon
>> cores does not help, if not having UB potentials, but I don't have a
>> 1080Ti at hand to test for that.
> Those data points may not have been run. Szilard might have the data - this
> was GLIC 2fs comparing 1080 with 1080Ti from the recent plots he shared.
>> So my questions are:
>> - At which number of E5-26XXv4 cores does the performance for common
>> systems level off with a 1080Ti for your test system (GLIC)?
>> - Does the answer depend strongly on the mdp settings (in particular on
>> the LJ cutoff)?
> Longer LJ cutoff (e.g. from different forcefields) will certainly require
> more non-bonded work, so then fewer CPU cores would be needed to do the
> remaining non-offloaded work. However any sweet spot for a particular .tpr
> would be highly dependent on other effects, such as the ratio of solvent
> (which typically has less LJ and simpler update) to solute, or the density
> of dihedral or U-B interactions. And doing pulling or FEP is very different
> again. The sweet spot for the next project will be elsewhere, sadly.
> This would help us a lot when choosing the appropriate CPU for a 1080Ti.
>> Many thanks for any suggestions,
>> 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 <+49%20551%203914189>
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