NVIDIA GPU (Proprietary drivers)
Enabling NVIDIA GPU support on Talos is bound by NVIDIA EULA. The Talos published NVIDIA drivers are bound to a specific Talos release. The extensions versions also needs to be updated when upgrading Talos.
We will be using the following NVIDIA system extensions:
nonfree-kmod-nvidia
nvidia-container-toolkit
To build a NVIDIA driver version not published by SideroLabs follow the instructions here
Create the boot assets which includes the system extensions mentioned above (or create a custom installer and perform a machine upgrade if Talos is already installed).
Make sure the driver version matches for both the
nonfree-kmod-nvidia
andnvidia-container-toolkit
extensions. Thenonfree-kmod-nvidia
extension is versioned as<nvidia-driver-version>-<talos-release-version>
and thenvidia-container-toolkit
extension is versioned as<nvidia-driver-version>-<nvidia-container-toolkit-version>
.
Enabling the NVIDIA modules and the system extension
Patch Talos machine configuration using the patch gpu-worker-patch.yaml
:
machine:
kernel:
modules:
- name: nvidia
- name: nvidia_uvm
- name: nvidia_drm
- name: nvidia_modeset
sysctls:
net.core.bpf_jit_harden: 1
Now apply the patch to all Talos nodes in the cluster having NVIDIA GPU’s installed:
talosctl patch mc --patch @gpu-worker-patch.yaml
The NVIDIA modules should be loaded and the system extension should be installed.
This can be confirmed by running:
talosctl read /proc/modules
which should produce an output similar to below:
nvidia_uvm 1146880 - - Live 0xffffffffc2733000 (PO)
nvidia_drm 69632 - - Live 0xffffffffc2721000 (PO)
nvidia_modeset 1142784 - - Live 0xffffffffc25ea000 (PO)
nvidia 39047168 - - Live 0xffffffffc00ac000 (PO)
talosctl get extensions
which should produce an output similar to below:
NODE NAMESPACE TYPE ID VERSION NAME VERSION
172.31.41.27 runtime ExtensionStatus 000.ghcr.io-frezbo-nvidia-container-toolkit-510.60.02-v1.9.0 1 nvidia-container-toolkit 510.60.02-v1.9.0
talosctl read /proc/driver/nvidia/version
which should produce an output similar to below:
NVRM version: NVIDIA UNIX x86_64 Kernel Module 510.60.02 Wed Mar 16 11:24:05 UTC 2022
GCC version: gcc version 11.2.0 (GCC)
Deploying NVIDIA device plugin
First we need to create the RuntimeClass
Apply the following manifest to create a runtime class that uses the extension:
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: nvidia
handler: nvidia
Install the NVIDIA device plugin:
helm repo add nvdp https://nvidia.github.io/k8s-device-plugin
helm repo update
helm install nvidia-device-plugin nvdp/nvidia-device-plugin --version=0.13.0 --set=runtimeClassName=nvidia
(Optional) Setting the default runtime class as nvidia
Do note that this will set the default runtime class to
nvidia
for all pods scheduled on the node.
Create a patch yaml nvidia-default-runtimeclass.yaml
to update the machine config similar to below:
- op: add
path: /machine/files
value:
- content: |
[plugins]
[plugins."io.containerd.grpc.v1.cri"]
[plugins."io.containerd.grpc.v1.cri".containerd]
default_runtime_name = "nvidia"
path: /etc/cri/conf.d/20-customization.part
op: create
Now apply the patch to all Talos nodes in the cluster having NVIDIA GPU’s installed:
talosctl patch mc --patch @nvidia-default-runtimeclass.yaml
Testing the runtime class
Note the
spec.runtimeClassName
being explicitly set tonvidia
in the pod spec.
Run the following command to test the runtime class:
kubectl run \
nvidia-test \
--restart=Never \
-ti --rm \
--image nvcr.io/nvidia/cuda:12.1.0-base-ubuntu22.04 \
--overrides '{"spec": {"runtimeClassName": "nvidia"}}' \
nvidia-smi