I have reduced my system to now 1300 atoms. But during equilibration am
getting temperature fluctuations of + /- 7. So like is it like okay or do I
need to fix this. If I need to then how?
On Tue, Jun 26, 2018, 9:58 PM Matias Machado <mmachado.pasteur.edu.uy>
wrote:
> Dear Chhaya,
>
> Implicit solvent isn't as cheap as many people may think... there are many
> reasons for that (e.g. read this paper of Schulten [
> https://www.ncbi.nlm.nih.gov/pubmed/22121340])
>
> Notice for example, that you are explicitly calculating all N^2 Coulomb
> interactions by using a cut-off of 999A!!! You may increase the speed up in
> the CPU code by shortening that cut-off to e.g. 18A (but remember that
> means you are shifting the electrostatic potential and may compromise the
> accuracy of the calculation).
>
> Anyway, I would say that nowadays, is cheaper running systems of >5000
> atoms (or so) in explicit solvent as PME performs better, e.g. compare
> AMBER GPU benchmark on DHFR (23558 atoms) and Nucleosome (25095 atoms) both
> running at 2fs in explicit an implicit solvent respectively [
> http://ambermd.org/gpus/benchmarks.htm]... However, I must mention that
> there are some efforts to get better size scalability in implicit solvent
> (See [https://pubs.acs.org/doi/abs/10.1021/acs.jctc.6b00712]). I that
> sense, I think (IMHO) the main advantage of implicit solvent is a faster
> exploration of the Potential Energy Surface due to a reduced solvent
> friction... which means 1 ns MD at explicit solvent may not by 1 ns at
> implicit one (it may be more)... so there is some speed up there very
> difficult to quantify...
>
> Regarding the CPU vs GPU performance of AMBER code... I don't think is
> fare comparing few CPU cores against thousands in a GPU... but in my own
> experience the CPU code is by far less performant than the GPU one (at
> least in terms of scalability), hopefully the upcoming midpoint version of
> pmemd will narrow that difference...
>
> By the way... the performance you are getting is about the expected one
> for that system size, check as a reference the AMBER GPU benchmark on the
> Nucleosome (25095 atoms) in implicit solvent [
> http://ambermd.org/gpus/benchmarks.htm]:
>
> # 36 CPU : 0.29 ns/day
> # 2 K40 : 8 ns/day
> # 4 K40 : 14 ns/day
>
> (you would expect about twice that values as your system is a half)
>
> Hope this helps...
>
> Best,
>
> MatÃas
>
> ------------------------------------
> PhD.
> Researcher at Biomolecular Simulations Lab.
> Institut Pasteur de Montevideo | Uruguay
> [http://pasteur.uy/en/laboratorios-eng/lsbm]
> [http://www.sirahff.com]
>
>
> ----- Mensaje original -----
> De: "Chhaya Singh" <chhayasingh014.gmail.com>
> Para: "david case" <david.case.rutgers.edu>, "AMBER Mailing List" <
> amber.ambermd.org>, "Carlos Simmerling" <carlos.simmerling.gmail.com>
> Enviados: Lunes, 25 de Junio 2018 3:57:37
> Asunto: Re: [AMBER] Fwd: increase speed in amber using implcit solvent
> model
>
> Hey ,
> i have also tried using gpu as you suggested .
>
> Using 4 K40 GPU , I am getting a speed :
>
> Average timings for last 4950 steps:
> | Elapsed(s) = 27.31 Per Step(ms) = 5.52
> | ns/day = 31.32 seconds/ns = 2758.71
> |
> | Average timings for all steps:
> | Elapsed(s) = 27.59 Per Step(ms) = 5.52
> | ns/day = 31.32 seconds/ns = 2759.04
>
>
> that means i am getting a speed of 31.32 ns/day
>
> i also tried using 2 K40 GPU :
>
> Average timings for last 4950 steps:
> | Elapsed(s) = 42.20 Per Step(ms) = 8.53
> | ns/day = 20.27 seconds/ns = 4262.74
> |
> | Average timings for all steps:
> | Elapsed(s) = 42.63 Per Step(ms) = 8.53
> | ns/day = 20.27 seconds/ns = 4262.90
>
>
>
> is there any improvement that i can make ?
>
>
> On 25 June 2018 at 12:14, Chhaya Singh <chhayasingh014.gmail.com> wrote:
>
> > hello,
> > I am having 13010 atoms in my system.
> > the cpu that i am using has the following details:
> >
> > Intel E5-2670 series CPUs with 16 cores/node and has 64 GB RAM.
> >
> > the command line i am using is :
> >
> > #mpirun -machinefile $PBS_NODEFILE -np $NPROCS $AMBERHOME/bin/sander.MPI
> > -O -i min.in -p fib.prmtop -c fib.inpcrd -r min.rst -o min.out
> >
> >
> > mpirun -machinefile $PBS_NODEFILE -np $NPROCS $AMBERHOME/bin/pmemd.MPI -O
> > -i heat1.in -p fib.prmtop -c min.rst -r heat1.rst -o heat1.out -x
> heat1.nc
> > -inf heat1.mdinfo
> >
> >
> > my min.in file has the following parameters:
> > Stage 1 - minimisation of fibril
> > &cntrl
> > imin=1, maxcyc=1000, ncyc=500,
> > cut=999., rgbmax=999.,igb=8, ntb=0,
> > ntpr=100
> > /
> >
> > using 1 node I am getting a speed of :
> > Average timings for last 50 steps:
> > | Elapsed(s) = 33.80 Per Step(ms) = 675.91
> > | ns/day = 0.06 seconds/ns = 1351821.64
> > |
> > | Average timings for all steps:
> > | Elapsed(s) = 26982.45 Per Step(ms) = 674.56
> > | ns/day = 0.06 seconds/ns = 1349122.30
> >
> > using 2 nodes I am getting a speed of :
> >
> > Average timings for last 150 steps:
> > | Elapsed(s) = 51.65 Per Step(ms) = 344.37
> > | ns/day = 0.13 seconds/ns = 688733.19
> > |
> > | Average timings for all steps:
> > | Elapsed(s) = 13726.02 Per Step(ms) = 343.15
> > | ns/day = 0.13 seconds/ns = 686300.95
> >
> >
> > using 8 nodes:
> > Average timings for last 250 steps:
> > | Elapsed(s) = 23.90 Per Step(ms) = 95.62
> > | ns/day = 0.45 seconds/ns = 191236.85
> > |
> > | Average timings for all steps:
> > | Elapsed(s) = 955.23 Per Step(ms) = 95.52
> > | ns/day = 0.45 seconds/ns = 191045.67
> >
> >
> > using 10 nodes i am getting a speed of:
> >
> > Average timings for last 200 steps:
> > | Elapsed(s) = 16.28 Per Step(ms) = 81.42
> > | ns/day = 0.53 seconds/ns = 162838.32
> > |
> > | Average timings for all steps:
> > | Elapsed(s) = 3224.53 Per Step(ms) = 80.61
> > | ns/day = 0.54 seconds/ns = 161226.62
> >
> >
> > On 25 June 2018 at 00:19, David A Case <david.case.rutgers.edu> wrote:
> >
> >> On Sun, Jun 24, 2018, Chhaya Singh wrote:
> >>
> >> > I am trying to perform a simulation having a protein using implicit
> >> solvent
> >> > model using force field ff14sbonlysc with igb = 8.
> >> > I am getting a very low speed using 2 nodes. the speed i get now is
> >> less a
> >> > ns/ day.
> >>
> >> It would help a lot to know how many atoms are in your protein. Less
> >> crucial, but still important, would be to know what cpu you are using.
> >> (Or is this actually a GPU simulation?) When you say "2 nodes", exactly
> >> what is meant? Can you provide the command line that you used to run
> >> the simulation?
> >>
> >> Some general hints (beyond the good advice that Carlos has already
> >> given.):
> >>
> >> a. be sure you are using pmemd.MPI, not sander.MPI (if pmemd is
> >> available)
> >> b. if possible, see if increasing the number of MPI threads helps
> >> c. you can run tests with a cutoff (cut and rgbmax) of 20 or 25: you
> >> will still have some artifacts from the cutoff, but they may be
> >> small enough to live with.
> >> d. if you system is indeed quite large, you may benefit from the
> >> hierarchical charge partitioning (GB-HCP) model. See the manual
> >> for details.
> >>
> >> ....dac
> >>
> >>
> >> _______________________________________________
> >> AMBER mailing list
> >> AMBER.ambermd.org
> >> http://lists.ambermd.org/mailman/listinfo/amber
> >>
> >
> >
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Received on Wed Jun 27 2018 - 11:30:03 PDT
