Hi Ben, That performance is not reasonable at all - neither for CPU only run on your quad-core Sandy Bridge, nor for the CPU+GPU run. For the latter you should be getting more like 50 ns/day or so.
What's strange about your run is that the CPU-GPU load balancing is picking a *very* long cut-off which means that your CPU is for some reason performing very badly. Check how is mdrun behaving while running in top/htop nad if you are not seeing ~400% CPU utilization, there is something wrong - perhaps threads getting locked to the same core (to check that try -pin off). Secondly, note that you are using OpenMM-specific settings from the old GROMACS-OpenMM comparison benchmarks in which the grid spacing is overly coarse (you could use something like a fourier-spacing=0.125 or even larger with rc=1.0). Cheers, -- Szilárd On Tue, Apr 9, 2013 at 10:27 PM, Benjamin Bobay <[email protected]> wrote: > Good afternoon - > > I recently installed gromacs-4.6 on CentOS6.3 and the installation went > just fine. > > I have a Tesla C2075 GPU. > > I then downloaded the benchmark directories and ran a bench mark on the > GPU/ dhfr-solv-PME.bench > > This is what I got: > > Using 1 MPI thread > Using 4 OpenMP threads > > 1 GPU detected: > #0: NVIDIA Tesla C2075, compute cap.: 2.0, ECC: yes, stat: compatible > > 1 GPU user-selected for this run: #0 > > > Back Off! I just backed up ener.edr to ./#ener.edr.1# > starting mdrun 'Protein in water' > -1 steps, infinite ps. > step 40: timed with pme grid 64 64 64, coulomb cutoff 1.000: 4122.9 > M-cycles > step 80: timed with pme grid 56 56 56, coulomb cutoff 1.143: 3685.9 > M-cycles > step 120: timed with pme grid 48 48 48, coulomb cutoff 1.333: 3110.8 > M-cycles > step 160: timed with pme grid 44 44 44, coulomb cutoff 1.455: 3365.1 > M-cycles > step 200: timed with pme grid 40 40 40, coulomb cutoff 1.600: 3499.0 > M-cycles > step 240: timed with pme grid 52 52 52, coulomb cutoff 1.231: 3982.2 > M-cycles > step 280: timed with pme grid 48 48 48, coulomb cutoff 1.333: 3129.2 > M-cycles > step 320: timed with pme grid 44 44 44, coulomb cutoff 1.455: 3425.4 > M-cycles > step 360: timed with pme grid 42 42 42, coulomb cutoff 1.524: 2979.1 > M-cycles > optimal pme grid 42 42 42, coulomb cutoff 1.524 > step 4300 performance: 1.8 ns/day > > and from the nvidia-smi output: > Tue Apr 9 10:13:46 2013 > +------------------------------------------------------+ > > | NVIDIA-SMI 4.304.37 Driver Version: 304.37 > | > > |-------------------------------+----------------------+----------------------+ > | GPU Name | Bus-Id Disp. | Volatile Uncorr. > ECC | > | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute > M. | > > |===============================+======================+======================| > | 0 Tesla C2075 | 0000:03:00.0 On | > 0 | > | 30% 67C P0 80W / 225W | 4% 200MB / 5375MB | 4% > Default | > > +-------------------------------+----------------------+----------------------+ > > > > +-----------------------------------------------------------------------------+ > | Compute processes: GPU > Memory | > | GPU PID Process name > Usage | > > |=============================================================================| > | 0 22568 mdrun > 59MB | > > +-----------------------------------------------------------------------------+ > > > So I am only getting 1.8ns/day !!!!! Is that right? It seems very very > small compared to the CPU test where I am getting the same: > > step 200 performance: 1.8 ns/day vol 0.79 imb F 14% > > >From the md.log of the GPU test: > Detecting CPU-specific acceleration. > Present hardware specification: > Vendor: GenuineIntel > Brand: Intel(R) Xeon(R) CPU E5-2603 0 @ 1.80GHz > Family: 6 Model: 45 Stepping: 7 > Features: aes apic avx clfsh cmov cx8 cx16 htt lahf_lm mmx msr nonstop_tsc > pcid pclmuldq pdcm pdpe1gb popcnt pse rdtscp sse2 sse3 sse4.1 sse4.2 ssse3 > tdt x2a > pic > Acceleration most likely to fit this hardware: AVX_256 > Acceleration selected at GROMACS compile time: AVX_256 > > > 1 GPU detected: > #0: NVIDIA Tesla C2075, compute cap.: 2.0, ECC: yes, stat: compatible > > 1 GPU user-selected for this run: #0 > > Will do PME sum in reciprocal space. > > Any thoughts as to why it is so slow? > > many thanks! > Ben > > -- > ____________________________________________ > Research Assistant Professor > North Carolina State University > Department of Molecular and Structural Biochemistry > 128 Polk Hall > Raleigh, NC 27695 > Phone: (919)-513-0698 > Fax: (919)-515-2047 > ____________________________________________ > -- > gmx-users mailing list [email protected] > http://lists.gromacs.org/mailman/listinfo/gmx-users > * Please search the archive at > http://www.gromacs.org/Support/Mailing_Lists/Search before posting! > * Please don't post (un)subscribe requests to the list. Use the > www interface or send it to [email protected]. > * Can't post? Read http://www.gromacs.org/Support/Mailing_Lists > -- gmx-users mailing list [email protected] http://lists.gromacs.org/mailman/listinfo/gmx-users * Please search the archive at http://www.gromacs.org/Support/Mailing_Lists/Search before posting! * Please don't post (un)subscribe requests to the list. Use the www interface or send it to [email protected]. * Can't post? Read http://www.gromacs.org/Support/Mailing_Lists
