[gmx-users] 2018 performance question

Michael Brunsteiner mbx0009 at yahoo.com
Fri Feb 16 12:42:53 CET 2018


hi
just installed gmx-2018 on a x86_64 PC with a Geforce GTX 780 and the cudasoftware directly from the nvidia webpage (didn't work using the debian nvidia packages)
output of lscpu is included below.
i find that:
1) 2018 is slightly faster (~5%) than 2016.2) both 2016 and 2018 use the GPU, but 2018 seems to use less CPU.
With 2016 using the "top" command i usually see that the CPU load is close to 1200%(i have 6 cores, each two threads) while with 2018 this number is closer to around 400%(I guess this is because 2018 does PME on the GPU)
my question is: can i possibly further improve the performance of 2018 by1) somehow convincing gmx to use more CPU, or
2) run two instances of gmx on this one computer simultaneously??
thanks in advance for any feedback!
cheers,Michael



prompt> lscpuArchitecture:          x86_64
CPU op-mode(s):        32-bit, 64-bit
Byte Order:            Little Endian
CPU(s):                12
On-line CPU(s) list:   0-11
Thread(s) per core:    2
Core(s) per socket:    6
Socket(s):             1
NUMA node(s):          1
Vendor ID:             GenuineIntel
CPU family:            6
Model:                 62
Model name:            Intel(R) Core(TM) i7-4930K CPU @ 3.40GHz
Stepping:              4
CPU MHz:               3399.898
CPU max MHz:           3900.0000
CPU min MHz:           1200.0000
BogoMIPS:              6799.79
Virtualization:        VT-x
L1d cache:             32K
L1i cache:             32K
L2 cache:              256K
L3 cache:              12288K
NUMA node0 CPU(s):     0-11
Flags:                 fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm epb kaiser tpr_shadow vnmi flexpriority ept vpid fsgsbase smep erms xsaveopt dtherm ida arat pln pts




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