First ensure that all the the. GPUs are visible using docker-nvidia
root@gpu-server:/home/mano# docker run --gpus all nvidia/cuda:11.6.2-cudnn8-runtime-ubuntu20.04 nvidia-smi
==========
== CUDA ==
==========
CUDA Version 11.6.2
Container image Copyright (c) 2016-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
Fri Jan 6 00:36:05 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.161.03 Driver Version: 470.161.03 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
| 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 NVIDIA GeForce ... Off | 00000000:01:00.0 On | N/A |
| 0% 51C P8 11W / 230W | 100MiB / 8118MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:02:00.0 Off | N/A |
| 0% 52C P8 9W / 230W | 8MiB / 8119MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 NVIDIA GeForce ... Off | 00000000:04:00.0 Off | N/A |
| 0% 48C P8 10W / 230W | 8MiB / 8119MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 NVIDIA GeForce ... Off | 00000000:05:00.0 Off | N/A |
| 0% 44C P8 9W / 230W | 8MiB / 8119MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
root@gpu-server:/home/mano#
Then get the docker image with GPU enabled :
root@gpu-server:~# docker run --gpus all -d -it -p 8848:8888 -v $(pwd)/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes --user root cschranz/gpu-jupyter:v1.4_cuda-11.2_ubuntu-20.04_python-only