Sorry for the confusion. My fault... I saw my previous post and found that I missed something. In fact, I couldn't run "-pme gpu".
So, once again, I ran all the commands and uploaded the log files gmx mdrun -nobackup -nb cpu -pme cpu -deffnm md_0_1 https://pastebin.com/RNT4XJy8 gmx mdrun -nobackup -nb cpu -pme gpu -deffnm md_0_1 https://pastebin.com/7BQn8R7g This run shows an error on the screen which is not shown in the log file. So please also see https://pastebin.com/KHg6FkBz gmx mdrun -nobackup -nb gpu -pme cpu -deffnm md_0_1 https://pastebin.com/YXYj23tB gmx mdrun -nobackup -nb gpu -pme gpu -deffnm md_0_1 https://pastebin.com/P3X4mE5y From the results, it seems that running the pme on the cpu is better than gpu. The fastest command here is -nb gpu -pme cpu Still I have the question that while GPU is utilized, the CPU is also busy. So, I was thinking that the source code uses cudaDeviceSynchronize() where the CPU enters a busy loop. Regards, Mahmood On Friday, March 2, 2018, 3:24:41 PM GMT+3:30, Szilárd Páll <pall.szil...@gmail.com> wrote: Once again, full log files, please, not partial cut-and-paste, please. Also, you misread something because your previous logs show: -nb cpu -pme gpu: 56.4 ns/day -nb cpu -pme gpu -pmefft cpu 64.6 ns/day -nb cpu -pme cpu 67.5 ns/day So both mixed mode PME and PME on CPU are faster, the latter slightly faster than the former. This is about as much as you can do, I think. Your GPU is just too slow to get more performance out of it and the runs are GPU-bound. You might be able to get a bit more performance with some tweaks (compile mdrun with AVX2_256, use a newer fftw, use a newer gcc), but expect marginal gains. Cheers, -- Szilárd -- Gromacs Users mailing list * Please search the archive at http://www.gromacs.org/Support/Mailing_Lists/GMX-Users_List before posting! * Can't post? Read http://www.gromacs.org/Support/Mailing_Lists * For (un)subscribe requests visit https://maillist.sys.kth.se/mailman/listinfo/gromacs.org_gmx-users or send a mail to gmx-users-requ...@gromacs.org.