Hi,
First, make sure you're using the most up to date version of the code. Your
output should contain:
|--------------------- INFORMATION ----------------------
| GPU (CUDA) Version of PMEMD in use: NVIDIA GPU IN USE.
| Version 12.3.1
That being said, do you really need to use 3 GPUs across 3 different nodes
for a single job? I can't imagine you would see much of a speedup (if any).
If fact, with the current code even using 3 GPUs in a single node you
probably don't get that much overall speedup. I think that for Amber14 the
MPI implementation is going to receive a huge boost which may change this
in the future, but for now you're probably better off running separate jobs
on each GPU.
-Dan
On Fri, Jan 3, 2014 at 5:16 PM, Jio M <jiomm.yahoo.com> wrote:
> Hi all,
>
> Just to add, I tested now same job in single GPU and it works fine. My
> previous jobs with same input files worked fine when it uses 3 GPU in same
> node but when I use 3 GPU in different nodes it kills without error as said.
>
> Any ideas?
>
> regards
> JIo
>
>
>
>
>
> On Friday, January 3, 2014 11:26 PM, Jio M <jiomm.yahoo.com> wrote:
>
> Dear all
>
> I have one job with NPT input mdin file but it ends without error in cuda
> versio (pmemd.cuda_SPDP.MPI) but it works fine with pmemd.MPI
>
> here are end lines from cuda job without error:
>
> | Conditional Compilation Defines Used:
> | DIRFRC_COMTRANS
> | DIRFRC_EFS
> | DIRFRC_NOVEC
> | MPI
> | PUBFFT
> | FFTLOADBAL_2PROC
> | BINTRAJ
> | CUDA
>
> | Largest sphere to fit in unit cell has radius = 63.294
>
> Please suggest
>
> thanks
> JIo
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--
-------------------------
Daniel R. Roe, PhD
Department of Medicinal Chemistry
University of Utah
30 South 2000 East, Room 201
Salt Lake City, UT 84112-5820
http://home.chpc.utah.edu/~cheatham/
(801) 587-9652
(801) 585-6208 (Fax)
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Received on Fri Jan 03 2014 - 21:00:02 PST