Created
April 17, 2023 20:31
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RKE2/K3s Nvidia GPU-Operator installation
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prep: | |
helm repo add nvidia https://helm.ngc.nvidia.com/nvidia \ | |
&& helm repo update | |
install: | |
helm install --wait nvidiagpu \ | |
-n gpu-operator --create-namespace \ | |
--set toolkit.env[0].name=CONTAINERD_CONFIG \ | |
--set toolkit.env[0].value=/var/lib/rancher/k3s/agent/etc/containerd/config.toml \ | |
--set toolkit.env[1].name=CONTAINERD_SOCKET \ | |
--set toolkit.env[1].value=/run/k3s/containerd/containerd.sock \ | |
--set toolkit.env[2].name=CONTAINERD_RUNTIME_CLASS \ | |
--set toolkit.env[2].value=nvidia \ | |
--set toolkit.env[3].name=CONTAINERD_SET_AS_DEFAULT \ | |
--set-string toolkit.env[3].value=true \ | |
nvidia/gpu-operator | |
delete: | |
helm uninstall -n gpu-operator nvidiagpu | |
cluster-info: | |
kubectl get nodes -o wide |
you can either run kubectl run nvidia-smi --restart=Never --rm -i --tty --image nvidia/cuda:11.0.3-base-ubuntu20.04 -- nvidia-smi
or
find the driver pod kubectl get pod -n gpu-operator | grep driver
and run kubectl exec -it nvidia-driver-daemonset-qxtlz -n gpu-operator -- nvidia-smi
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.54.14 Driver Version: 550.54.14 CUDA Version: 12.4 |
|-----------------------------------------+------------------------+----------------------+
| 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 RTX A5000 On | 00000000:01:00.0 Off | Off |
| 30% 37C P8 28W / 230W | 1MiB / 24564MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+```
I want to run it on Jetson platform (arm), there is no nvidia-smi
, as I know. But anyway - thanks for the precise command.
probably you could try nvcr.io/nvidia/l4t-cuda:12.2.2-devel-arm64-ubuntu22.04
or images from https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-cuda/tags
note: I am particularly sure and didn't tried it out.
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Hello! It is great script. But how to check that gpu-operator is working well?