With AMBER, performance is entirely determined by the GPU (well 98+% to be
absolutely utterly 100% honest)
With GROMACS, performance is a complex brew of the GPU(s) and the CPU(s)
(if you spend enough to get it right, you're up to 30% faster than AMBER,
if you get it wrong you can be <<1/2 the speed)
I'd suggest plugging more GPUs into this box. For independent runs, it'll
scale AMBER throughput linearly...
On Wed, May 8, 2013 at 12:19 PM, Sergio R Aragon <aragons.sfsu.edu> wrote:
> Hello Ying,
>
> We have a machine of this type where the GPU is a GTX-580. To demonstrate
> the much larger efficiency of using a GPU compared to CPU multiprocessing
> with amber, I asked my students to compare both methods for the protein
> 1AO6. Using the GTX-580 you could get about 12 ns/day for an explicit
> water simulation with TIP3P waters in an 8 A octahedral box using ff99SB,
> and the SPDP model in Amber 12. Using 12 CPU cores the performance was a
> factor of 100 slower. Thus, even if you use all 64 cores, the CPU
> performance is unuseable.
>
> I built this machine for teaching computational chemistry methods - you
> need many CPU processors to give many students a chance to go simultaneous
> computations with g09, and other packages that don't parallelize well. But
> for doing MD, it is much better to have even a cheap GTX-560 card in many
> PC's to have many students work at the same time.
>
> Hope that helps somewhat.
>
> Cheers,
>
> Sergio
> SFSU
>
> -----Original Message-----
> From: sun [mailto:sun.ntnu.edu.tw]
> Sent: Wednesday, May 08, 2013 9:40 AM
> To: amber.ambermd.org
> Subject: [AMBER] pmemd performance on AMD 16cores x 4 (total 64 CPU cores)
> + 1 GPU
>
> Hi,
>
> does anyone have experience on the machine of this configuration? and
> benchmarks?
>
> Thanks very much.
>
> Ying-chieh
>
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Received on Wed May 08 2013 - 13:00:02 PDT
