Re: [AMBER] amber16 on parallel GPUs

From: Hirdesh Kumar <hirdesh.iitd.gmail.com>
Date: Mon, 30 Jan 2017 10:10:03 -0600

Thanks Ross,
Very helpful. I performed the AMBER benchmark check on my system. Result
looks promising, I just have one query:
In "TRPCAGE_PRODUCTION - 304 atoms GB" test,

I got following error>: CPU code 40 cores: | ERROR: Must have 10x more
atoms than processors!

But I guess I can ignore this error ??

Thanks,
Hirdesh

*‚Äč*

On Fri, Jan 27, 2017 at 7:04 PM, Ross Walker <ross.rosswalker.co.uk> wrote:

> Hi Hirdesh,
>
> You are unlikely to see good scaling across 4 1080's unless you have
> custom peer to peer hardware. Take a read through the following pages:
>
> http://ambermd.org/gpus/ <http://ambermd.org/gpus/>
>
> http://ambermd.org/gpus/recommended_hardware.htm#hardware <
> http://ambermd.org/gpus/recommended_hardware.htm#hardware>
>
> and
>
> http://ambermd.org/gpus/benchmarks.htm#Benchmarks <
> http://ambermd.org/gpus/benchmarks.htm#Benchmarks>
>
> If you use GPU's 0 and 1 together or 2 and 3 together you will probably
> see speedup if they have peer to peer connectivity. Likely your best
> approach will be 4 x 1 GPU runs or 2 x 2 GPU runs (or 2 x 1 + 1 x 2). Note
> from the benchmark page you can download the benchmark suite and run it on
> you system and you'll be able to see how each GPU is performing and how
> well 2 and 4 GPU combinations work.
>
> All the best
> Ross
>
> > On Jan 27, 2017, at 16:06, Hirdesh Kumar <hirdesh.iitd.gmail.com> wrote:
> >
> > Hi,
> > I am testing my recently installed amber16 which I built as
> pmemd.cuda.MPI
> >
> > the intallation was successful (no FAILURE in make test.cuda_parallel).
> >
> > Next I submitted a test job as:
> >
> >
> > *export CUDA_VISIBLE_DEVICE=0,1,2,3mpirun -np 4 pmemd.cuda_SPFP.MPI -O
> -i
> > prod1.in <http://prod1.in> -p protein.prmtop -c eq3.rst -r prod1.rst -o
> > prod1.out -x prod1.nc <http://prod1.nc>*
> >
> >
> > Using nvidia-smi, I checked that I can access all 4 GPUs in parallel,
> > however, I am surprised by GPU-utility. Why each GPU is used only ~50%.
> >
> > I previosly had speed of 44 ns/day using a single K80 GPU. However, using
> > these 4 parallel GPUs, I only get speed of 66 ns/day. What is wrong ?
> >
> > Below is the output of "nvidia-smi"
> >
> > +-----------------------------------------------------------
> ------------------+
> > | NVIDIA-SMI 367.57 Driver Version:
> > 367.57 |
> > |-------------------------------+----------------------+----
> ------------------+
> > | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr.
> > ECC |
> > | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util
> Compute
> > M. |
> > |===============================+======================+====
> ==================|
> > | 0 GeForce GTX 1080 Off | 0000:02:00.0 On |
> > N/A |
> > | 52% 72C P2 80W / 180W | 744MiB / 8111MiB | 51%
> > Default |
> > +-------------------------------+----------------------+----
> ------------------+
> > | 1 GeForce GTX 1080 Off | 0000:03:00.0 Off |
> > N/A |
> > | 51% 74C P2 72W / 180W | 525MiB / 8113MiB | 42%
> > Default |
> > +-------------------------------+----------------------+----
> ------------------+
> > | 2 GeForce GTX 1080 Off | 0000:82:00.0 Off |
> > N/A |
> > | 47% 71C P2 71W / 180W | 525MiB / 8113MiB | 44%
> > Default |
> > +-------------------------------+----------------------+----
> ------------------+
> > | 3 GeForce GTX 1080 Off | 0000:83:00.0 Off |
> > N/A |
> > | 51% 73C P2 73W / 180W | 525MiB / 8113MiB | 43%
> > Default |
> > +-------------------------------+----------------------+----
> ------------------+
> >
> >
> > +-----------------------------------------------------------
> ------------------+
> > | Processes: GPU
> > Memory |
> > | GPU PID Type Process name
> > Usage |
> > |===========================================================
> ==================|
> > | 0 3020 G /usr/lib/xorg/Xorg
> > 168MiB |
> > | 0 3566 G compiz
> > 73MiB |
> > | 0 10231 C pmemd.cuda_SPFP.MPI
> > 387MiB |
> > | 0 10232 C pmemd.cuda_SPFP.MPI
> > 111MiB |
> > | 1 10231 C pmemd.cuda_SPFP.MPI
> > 111MiB |
> > | 1 10232 C pmemd.cuda_SPFP.MPI
> > 411MiB |
> > | 2 10233 C pmemd.cuda_SPFP.MPI
> > 411MiB |
> > | 2 10234 C pmemd.cuda_SPFP.MPI
> > 111MiB |
> > | 3 10233 C pmemd.cuda_SPFP.MPI
> > 111MiB |
> > | 3 10234 C pmemd.cuda_SPFP.MPI
> > 411MiB |
> > +-----------------------------------------------------------
> ------------------+
> >
> >
> >
> > Thanks,
> > Hirdesh
> > _______________________________________________
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>
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Received on Mon Jan 30 2017 - 08:30:03 PST
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