add gpu

README.md

@@ -64,3 +64,44 @@ docker buildx build -t hotwa/notebook:latest . -f Dockerfile
   A tool for building artifacts from source code and injecting them into docker images
 - [jupyter-on-openshift/jupyter-notebooks](https://github.com/jupyter-on-openshift/jupyter-notebooks) -
   OpenShift compatible S2I builder for basic notebook images
+
+## nvidia-container-toolkit add
+
+参考了 llama [容器部署](https://hub.docker.com/r/ollama/ollama)
+
+```shell
+curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
+    | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
+curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
+    | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
+    | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
+sudo apt-get update
+sudo apt-get install -y nvidia-container-toolkit
+```
+
+Configure Docker to use Nvidia driver
+
+```shell
+sudo nvidia-ctk runtime configure --runtime=docker
+sudo systemctl restart docker
+```
+
+配置完成之后：
+
+```shell
+docker-compose up -d
+```
+
+在jupyterhub_config.py中添加：这样jupyterhub的容器启动镜像就可以使用宿主机的显卡了
+
+```python
+# GPU 和网络配置
+c.DockerSpawner.extra_host_config = {
+    #'network_mode': 'host',
+    'runtime': 'nvidia'
+}
+c.DockerSpawner.environment = {
+    'NVIDIA_DRIVER_CAPABILITIES': 'compute,utility',
+    'NVIDIA_VISIBLE_DEVICES': 'all'
+}
+```

jupyterhub_config.py

@@ -56,3 +56,12 @@ c.NativeAuthenticator.open_signup = True
 admin = os.environ.get("JUPYTERHUB_ADMIN")
 if admin:
     c.Authenticator.admin_users = [admin]
+
+# GPU 和网络配置
+c.DockerSpawner.extra_host_config = {
+    'runtime': 'nvidia'
+}
+c.DockerSpawner.environment = {
+    'NVIDIA_DRIVER_CAPABILITIES': 'compute,utility',
+    'NVIDIA_VISIBLE_DEVICES': 'all'
+}