Hi Vivek,
I think I'm a bit lost now. We were originally talking about differences
in trajectories but from the mail you just sent I can see that you have
a segmentation fault, which is another problem.
I can only suggest that if you want to make use of 128 processors you
should download the CVS version of gromacs or wait until the 4.0
is out. Since in gromacs 3.3.x the protein has to reside as a whole
on one of the processors, this very likely limits your scaling.
Also, on 128 processors you will get a PME grid of 128x128xSomething
(since nx and ny have to be divisible by the number of CPUs) which is
probably way bigger than it needs to be (how big is it for a single
CPU?). Together with a PME order of 6 this leads to a large overlap
in the charge grid, which has to be communicated among the processors.
PME order 4 will be better suited for such a high parallelization, but
in general for Gromacs 3.x you should have at least a few thousand atoms
per processor, less than 1000 won't give you decent scaling at all.
Carsten
vivek sharma wrote:
Hi Carsten,
Thanks for your reply. Actually I am running MD simulation on a protein
molecule with 270 residues(2687 atoms), after adding water it is having
45599 atoms, and using the recent version of gromacs test available from
gromacs.org <http://gromacs.org> (gmxtest-3.3.3.tgz)
Following are the entries from the .mdp file I am using.....
**********md.mdp
title = trp_drg MD
cpp = /lib/cpp ; location of cpp on SGI
constraints = all-bonds
integrator = md
dt = 0.002 ; ps !
nsteps = 25000 ; total 50 ps.
nstcomm = 1
nstxout = 2500 ; output coordinates every 5.0 ps
nstvout = 0
nstfout = 0
nstlist = 5
ns_type = grid
rlist = 0.9
coulombtype = PME
rcoulomb = 0.9
rvdw = 1.4
fourierspacing = 0.12
fourier_nx = 0
fourier_ny = 0
fourier_nz = 0
pme_order = 6
ewald_rtol = 1e-5
optimize_fft = yes
; Berendsen temperature coupling is on in four groups
Tcoupl = berendsen
tau_t = 0.1 0.1 0.1
tc-grps = protein NDP sol
ref_t = 300 300 300
; Pressure coupling is on
Pcoupl = berendsen
pcoupltype = isotropic
tau_p = 0.5
compressibility = 4.5e-5
ref_p = 1.0
; Generate velocites is on at 300 K.
gen_vel = yes
gen_temp = 300.0
gen_seed = 173529
****************and Following are the commands I am using
grompp_d -np 128 -f md1.mdp -c 1XU9_A_b4em.gro -p 1XU9_A.top -o
1XU9_A_md1_np128.tpr
submit
mdrun_d
/////arguement for mdrun_d
-s 1XU9_A_md1_np128.tpr -o 1XU9_A_md1_np128.trr -c 1XU9_A_pmd1_np128.gro
-g md_np128.log -e md_np128.edr -np 128
***********Following is the error I am getting
Reading file 1XU9_A_md1_np128.tpr, VERSION 3.3.3 (double precision)
starting mdrun 'CORTICOSTEROID 11-BETA-DEHYDROGENASE, ISOZYME 1'
25000 steps, 50.0 ps.
srun: error: n141: task1: Segmentation fault
srun: Terminating job
****************************************************************
Is this information is helpfull in figuring out the problem.
Please, advice
With Thanks,
Vivek
2008/9/11 Carsten Kutzner <[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>>
vivek sharma wrote:
Hi There,
I am running gromacs parellal version on cluster, with different
-np options.
Hi,
which version of gromacs exactly are you using?
On analyzing the 5 nsec trajectory using ngmx, I am finding
difference in the trajectory of two similar runs (only thing
varying in two runs in -np i.e 20 and 64 ), where mdp file and
input files are same in two cases.
I am wondering why I am getting this difference in two
trajectories ?
I am looking for the advice whether I did something wrong or
what may be the probable reason for this difference.
There are many reasons why a parallel run does not yield binary
identical
results to a run with another number of processors, even if you
start from
the same tpr file. If you use PME, then the FFTW could pick a slightly
different algorithm (it will select the fastest for that number of
processors.
This feature you can turn off by passing --disable-fftw-measure to the
gromacs configure script). But still you can get results that are not
binary identical if you do FFTs on a varying number of CPUs. Also, for
limited accuracy which is inherent to any computer, additions need not
be associative, which can show up in parallel additions.
Generally, if you run in double precision, these effects will be way
smaller,
but nevertheless you won't get binary identical results. This will
in all
cases lead to trajectories which slowly diverge from each other.
However,
in the fist few hundred time steps, you should not see any difference in
the first couple of decimals of the variables (positions, velocities,
energies ...)
Also, I am not able to run gromacs faster by increasing the -np
issue,
Please provide the exact command line you used.
Is there any max limit for scaling gromacs on parellal cluster ?
Yes, depending on your MD system and on the cluster you use :)
Carsten
With Thanks,
Vivek
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Dr. Carsten Kutzner
Max Planck Institute for Biophysical Chemistry
Theoretical and Computational Biophysics Department
Am Fassberg 11
37077 Goettingen, Germany
Tel. +49-551-2012313, Fax: +49-551-2012302
http://www.mpibpc.mpg.de/research/dep/grubmueller/
http://www.gwdg.de/~ckutzne <http://www.gwdg.de/%7Eckutzne>
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--
Dr. Carsten Kutzner
Max Planck Institute for Biophysical Chemistry
Theoretical and Computational Biophysics Department
Am Fassberg 11
37077 Goettingen, Germany
Tel. +49-551-2012313, Fax: +49-551-2012302
http://www.mpibpc.mpg.de/research/dep/grubmueller/
http://www.gwdg.de/~ckutzne
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