From: Souvik Sinha (souvik.sinha893_at_gmail.com)
Date: Thu Jan 25 2018 - 12:59:26 CST
Thanks for your reply.
I was wondering, why 'idlepoll' can't even call gpu to work despite the
probability of a poor performance.
On 25 Jan 2018 19:53, "Giacomo Fiorin" <giacomo.fiorin_at_gmail.com> wrote:
> Hi Souvik, this seems connected to the compilation options. Compiling
> with MPI + SMP + CUDA used to be very poor performance, although I haven't
> tried with the new CUDA kernels (2.12 and later).
> On Thu, Jan 25, 2018 at 4:02 AM, Souvik Sinha <souvik.sinha893_at_gmail.com>
>> NAMD Users,
>> I am trying to run replica exchange ABF simulations in a machine with 32
>> cores and 2 Tesla K40 cards. NAMD_2.12, compiled from source is what I am
>> From this earlier thread, *http://www.ks.uiuc.edu/Research/namd/mailing_list/namd-l.2014-2015/2490.htm
>> I find out that using "twoAwayX" or "idlepoll" might help the GPUs to
>> work but somehow in my situation it's not helping the GPUs to work
>> ("twoAwayX" is speeding up the jobs though). The 'idlepoll' switch
>> generally works fine for Cuda build NAMD versions for non-replica jobs.
>> From the aforesaid thread, I get that running 4 replicas in 32 CPUs and 2
>> GPUs may not provide a big boost to my simulations but I just want to check
>> whether it works or not?
>> I am running command for the job:
>> mpirun -np 32 /home/sgd/program/NAMD_2.12_Source/Linux-x86_64-g++/namd2
>> +idlepoll +replicas 4 $inputfile +stdout log/job0.%d.log
>> My understanding is not helping me much, so any advice will be helpful.
>> Thank you
>> Souvik Sinha
>> Research Fellow
>> Bioinformatics Centre (SGD LAB)
>> Bose Institute
>> Contact: 033 25693275
> Giacomo Fiorin
> Associate Professor of Research, Temple University, Philadelphia, PA
> Contractor, National Institutes of Health, Bethesda, MD
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