To list information about the GPU:
[kjetba@mimi ~]$ nvidia-smi
Thu Aug 3 11:40:29 2023
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 530.30.02 Driver Version: 530.30.02 CUDA Version: 12.1 |
|-----------------------------------------+----------------------+----------------------+
| 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 Quadro RTX 6000 On | 00000000:25:00.0 Off | 0 |
| N/A 25C P8 13W / 250W| 3MiB / 23040MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
| No running processes found |
+---------------------------------------------------------------------------------------+
To see GPU usage:
[kjetba@mimi ~]$ nvtop
Device 0 [Quadro RTX 6000] PCIe GEN 1@16x RX: 0.000 KiB/s TX: 0.000 KiB/s
GPU 300MHz MEM 405MHz TEMP 24°C FAN N/A% POW 13 / 250 W
GPU[ 0%] MEM[ 0.344Gi/22.500Gi]
┌──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
100│GPU0 % │
│GPU0 mem% │
│ │
│ │
│ │
75│ │
│ │
│ │
│ │
│ │
50│ │
│ │
│ │
│ │
│ │
25│ │
│ │
│ │
│ │
│ │
0│──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────│
└65s────────────────────────────48s──────────────────────────────32s─────────────────────────────16s─────────────────────────────0s┘
PID USER DEV TYPE GPU GPU MEM CPU HOST MEM Command TensorFlow and PyTorch are available as modules on mimi.uio.no:
$ module load TensorFlow/2.7.1-foss-2021b-CUDA-11.4.1
IMPORTANT: TensorFlow will allocate all the GPU memory by default. You should avoid this by adding the following in your code (sharing is caring):
import tensorflow as tf tf.config.experimental.set_memory_growth(gpu, True)
To run Jupyter Lab/Notebook on mimi.uio.no using you local browser, have a look here and here.
To use the GPU for rendering graphics on mimi, please see this page.
If you want to use the GPU for 3D applications, see here.