Hi,
> some test for a 50,000 atoms protein/water system,
> command:
> 1X8 16.44
I am not part of the CUDA developers, but to me, that looks not unusual,
depending on your GPUs. Compare to
http://ambermd.org/gpus/benchmarks.htm#Benchmarks
I assume that 1X8 means 1 8core node with a single GPU, right? 10-20ns/d
for a medium-large system is what I'd expect.
> 1X6 17.98
> 2X6 19.41
> 3X6 20.13
> 4X6 19.70
> 5X6 19.62
> 6X6 19.03
> 10X6 18.33
> It seems that the efficiency is not so high and the best one is 3X6 with
> around 20.1 ns/day. Since I am going to run hundreds of ns, it would
> take such a long time to be finished.....
I would argue that you gain almost nothing from scaling to a third GPU, so
2 or even 1 GPU is the optimal spot to run your simulation. Adding 50%
more resources to gain 5% more efficiency seems wasteful to me. You see
that multi-GPU scaling is not very efficient, which would depend on your
machine setup.
As for the long time your simulation would then take: *are you kidding
me?* I hate to sound exceptionally old here, but when I started doing MD
(say 5 years ago) I'd have killed for multinanosecond simulations on a
single machine, especially when waiting for a three-week 1 ns
equilibration to finish. So I guess the efficiency you see is the best one
could get at the moment and it is actually very very impressive!
Please imagine last paragraph wrapped in <rant> tags ;-)
Thomas
Dr. Thomas Steinbrecher
formerly at the
BioMaps Institute
Rutgers University
610 Taylor Rd.
Piscataway, NJ 08854
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Received on Wed Apr 18 2012 - 01:00:03 PDT
