You can obtain a basic information on the NVIDA GPU and its current usage
using NVIDIA’s “System Management Interface” program
nvidia-smi. Look at its man page for details man nvidia-smi.
See Checking Device Capability to find out detailed inforamtion on the card.
You need to be logged into a GPU node to run this command.
Here is an example of its output.
GPUNode $
$ nvidia-smi
Tue Aug 11 09:46:51 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.05 Driver Version: 450.51.05 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| 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 61C P0 155W / 250W | 17289MiB / 32510MiB | 91% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 Tesla V100-PCIE... Off | 00000000:D8:00.0 Off | 0 |
| N/A 62C P0 152W / 250W | 17289MiB / 32510MiB | 89% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 57573 C python 17283MiB |
| 1 N/A N/A 57573 C python 17283MiB |
+-----------------------------------------------------------------------------+
$
You can see that this node has two Tesla V100 GPUs installed. Both are running at about 50% memory usage and 90% GPU utilisation.