How to check GPU utilization
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General
For Running Jobs
using SLURM
If you have a job that is running on a GPU node and that is expected to use a GPU on that node, you can check the GPU use by your code by running the following command on ARC's login node:
$ srun -s --jobid 12345678 --pty nvidia-smi
The number here is the job ID of the running job.
The output should look similar to the following:
Mon Aug 22 09:27:38 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla V100-PCIE... Off | 00000000:3B:00.0 Off | 0 |
| N/A 33C P0 36W / 250W | 848MiB / 16160MiB | 30% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 2232533 C .../Programs/OpenDBA/openDBA 338MiB |
+-----------------------------------------------------------------------------+
In this case there was 1 GPU allocated and its usage was 30%.
The code openDBA also uses 338 MB of the GPU memory.
For Past Jobs
Using Sampled Metrics
On the OOD portal, here https://ood-arc.rcs.ucalgary.ca login using your UofC credentials.
Once you log in,
- Select Help --> View my job metrics,
- this will open an interface to your past jobs that are available in the database.
- Find the job you want to check and there may be useful graphs for GPU usage.