Hi All, this is not a pure Amber question, I observe the same with my Lammps users, but I figured there may be gpu expertise on this list to give me some insights.
My K20 environment is running with exclusive/persistent enabled. Taking a look at the size of the jobs I was wondering going the disabled route and push more jobs through.
But how/why do these tiny jobs each push gpu %util to above 70% while consuming such little memory? If that's real then the gpu can only handle one such job at a time?
-Henk
Mon Jul 24 13:51:26 2017
+------------------------------------------------------+
| NVIDIA-SMI 4.304.54 Driver Version: 304.54 |
|-------------------------------+----------------------+----------------------+
| GPU Name | Bus-Id Disp. | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla K20m | 0000:02:00.0 Off | 0 |
| N/A 40C P0 98W / 225W | 4% 205MB / 4799MB | 77% E. Process |
+-------------------------------+----------------------+----------------------+
| 1 Tesla K20m | 0000:03:00.0 Off | 0 |
| N/A 41C P0 106W / 225W | 5% 253MB / 4799MB | 72% E. Process |
+-------------------------------+----------------------+----------------------+
| 2 Tesla K20m | 0000:83:00.0 Off | 0 |
| N/A 26C P8 16W / 225W | 0% 13MB / 4799MB | 0% E. Process |
+-------------------------------+----------------------+----------------------+
| 3 Tesla K20m | 0000:84:00.0 Off | 0 |
| N/A 27C P8 15W / 225W | 0% 13MB / 4799MB | 0% E. Process |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Compute processes: GPU Memory |
| GPU PID Process name Usage |
|=============================================================================|
| 0 16997 pmemd.cuda.MPI 190MB |
| 1 16998 pmemd.cuda.MPI 238MB |
+-----------------------------------------------------------------------------+
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Received on Mon Jul 24 2017 - 11:30:02 PDT
