Hi guys, I'm new to Gromacs and seeking some input on my .mdp file for the
production run. I want to perform simulation to check protein stability over
time and the after that the stable protein will be used for protein-protein
docking/interactions. I'm using cubic box (with 1nm pbc) with water and Cl ions
to neutralize on a GPU accelerated system. my mdp file is as: title = Protein
in water ; Run parameters integrator = md ; leap-frog integrator nsteps =
2000 ; 2 * 500000 = 1000 ps, 1 ns dt = 0.002 ; 2 fs cutoff-scheme
= Verlet ; for GPU acceleration verlet-buffer-drift = -1 ; now use
nstlist ; Output control nstxout = 1000 ; save coordinates every 2 ps
nstvout = 1000 ; save velocities every 2 ps nstxtcout = 1000 ; xtc
compressed trajectory output every 2 ps nstenergy = 1000 ;
save energies every 2 ps nstlog = 1000 ; update log file every 2 ps ;
Bond parameters continuation = yes ; Restarting after NPT
constraint_algorithm = lincs ; holonomic constraints constraints
= all-bonds ; all bonds (even heavy atom-H bonds) constrained lincs_iter
= 1 ; accuracy of LINCS lincs_order = 4 ; also
related to accuracy ; Neighborsearching ns_type = grid ; search
neighboring grid cells nstlist = 30 ; 10 fs rlist
= 0.6 ; short-range neighborlist cutoff (in nm) rcoulomb = 0.6
; short-range electrostatic cutoff (in nm) rvdw = 0.6
; short-range van der Waals cutoff (in nm) ; Electrostatics coulombtype
= PME ; Particle Mesh Ewald for long-range electrostatics pme_order
= 4 ; cubic interpolation fourierspacing = 0.12 ; grid spacing for FFT
; Temperature coupling is on tcoupl = V-rescale ; modified Berendsen
thermostat tc-grps = Protein Non-Protein ; two coupling groups - more
accurate tau_t = 0.1 0.1 ; time constant, in ps ref_t = 300 300
; reference temperature, one for each group, in K ; Pressure coupling is on
pcoupl = Parrinello-Rahman ; Pressure coupling on in NPT pcoupltype
= isotropic ; uniform scaling of box vectors tau_p = 2.0 ; time
constant, in ps ref_p = 1.0 ; reference pressure, in bar compressibility =
4.5e-5 ; isothermal compressibility of water, bar^-1 ; Periodic boundary
conditions pbc = xyz ; 3-D PBC ; Dispersion correction DispCorr =
EnerPres ; account for cut-off vdW scheme ; Velocity generation gen_vel
= no ; Velocity generation is off By performing a test run with ff99SB force
field, I got an efficiency as follow: Reading file test11.tpr, VERSION 4.6.1
(single precision) Using 1 MPI thread Using 4 OpenMP threads 1 GPU detected:
#0: NVIDIA GeForce GT 630, compute cap.: 3.0, ECC: no, stat: compatible 1 GPU
auto-selected for this run: #0 starting mdrun 'Protein in water' 2000 steps,
4.0 ps. step 60: timed with pme grid 104 104 104, coulomb cutoff 0.600:
6760.6 M-cycles step 120: timed with pme grid 96 96 96, coulomb cutoff 0.643:
7826.0 M-cycles step 180: timed with pme grid 104 104 104, coulomb cutoff
0.600: 6716.3 M-cycles step 240: timed with pme grid 100 100 100, coulomb
cutoff 0.617: 7248.5 M-cycles optimal pme grid 104 104 104,
coulomb cutoff 0.600 step 1900, remaining runtime: 7 s Writing
final coordinates. step 2000, remaining runtime: 0 s NOTE: The
GPU has >20% more load than the CPU. This imbalance causes performance
loss, consider using a shorter cut-off and a finer PME grid.
Core t (s) Wall t (s) (%) Time: 427.620 144.021
296.9 (ns/day) (hour/ns) Performance: 2.401
9.996 By changing just the pme_order=6, I got this: Reading file test7.tpr,
VERSION 4.6.1 (single precision) Using 1 MPI thread Using 4 OpenMP threads 1
GPU detected: #0: NVIDIA GeForce GT 630, compute cap.: 3.0, ECC: no, stat:
compatible 1 GPU auto-selected for this run: #0 starting mdrun 'Protein in
water' 2000 steps, 4.0 ps. step 60: timed with pme grid 104 104 104,
coulomb cutoff 0.600: 6818.0 M-cycles step 120: timed with pme grid 96 96 96,
coulomb cutoff 0.643: 7821.2 M-cycles step 180: timed with pme grid 104 104
104, coulomb cutoff 0.600: 6718.4 M-cycles step 240: timed with pme grid 100
100 100, coulomb cutoff 0.617: 7257.1 M-cycles optimal pme grid
104 104 104, coulomb cutoff 0.600 step 1900, remaining runtime: 7 s
Writing final coordinates. step 2000, remaining runtime: 0 s
Core t (s) Wall t (s) (%) Time: 550.020
144.580 380.4 (ns/day) (hour/ns) Performance:
2.392 10.035 I have run many test simulations by changing rlist,
rcoulomb, rvdw, pme_order and fourierspacing (that I have concluded after
reading papers and gromacs user list), but in most of the time, I got
performance loss. I am a bit worry about using the very short rlist, rvdw and
rcoulomb (most of the papers used 1.0 for each for different proteins). If I
increase these cut-offs, there is performance loss, otherwise these cutoff are
short (i guess). can any body guide me where I should improve the mdp file or
the current one is reasonable. Thanks in advance. mayaz
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