Dear all,
Here is a new Amber user, who has been doing MD simulations on GTX 1080 Ti using pmemd.cuda in Amber 16 and have encountered considerable reduction in performance.
First I ran the benchmark sets of AMBER 16 GPU acceleration. For NPT simulation of Factor IX with 90,906 atoms, I have got ~89 ns/day on single GPU, slightly less than the benchmark performance (92.08 ns/day), which is acceptable. Since the benchmark results were OK, I was not suspecting any problem with the GPU.
When it came to my membrane protein system, which contains a GPCR dimer protein (ffSB14), POPC lipids (lipid 14), waters (TIP3P) and ions, and has a fairly similar atom number of 95,096, I was getting ~65 ns/day on single GPU. This was not what I was expecting, seeing that 95,096 was not THAT larger than 90,906.
My input file for the NPT simulation is as follows. I have tried to get as close as possible to the benchmark input.
NPT Production Run
&cntrl
nstlim=250000000, dt=0.002, ntx=5, irest=1, ntpr=50000, ntwr=50000000, ntwx=50000,
temp0=300.0, ntt=1, tautp=10.0,
ntb=2, ntp=1, barostat=2,
ntc=2, ntf=2,
ioutfm=1,
&end
/
1/ I have even cut down the writing of output and trajectories for better performance by raising ntpr and ntwx values, at the cost of inadequate trajectory snapshots. Is this necessary?
2/ Also, currently I am running an aMD simulation with similar input settings, which resulted in ~42 ns/day. Is aMD performance destined to drop compared to conventional MD?
Production Run with Accelerated MD
&cntrl
nstlim=250000000, dt=0.002, ntx=5, irest=1, ntpr=1000, ntwr=50000000, ntwx=1000, ntwprt=8873,
temp0=300.0, ntt=1, tautp=10.0,
ntb=2, ntp=1, barostat=2, cut=10.0,
ntc=2, ntf=2,
ioutfm=1,
iamd=3,
ethreshd=23916, alphad=1104,
ethreshp=-187677, alphap=19011,
&end
/
3/ Does the performance of pmemd.cuda differ among systems, or does it simply depend on the atom number?
I am hoping to get tips for improving the performance of my NPT runs.
Many thanks for any reply.
Best regards,
Ian
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Received on Sun Aug 02 2020 - 20:30:02 PDT
