Update README.md

Author: lwinckers

README.md

@@ -1,98 +1,3 @@
 # NVIDIA Driver container for CoreOS
 
-## Based on https://gitlab.com/nvidia/container-images/driver/-/tree/main/coreos?ref_type=heads
-
-### Prerequisites
-
-##### Enable required modules
-```sh
-sudo modprobe -a loop ipmi_msghandler
-echo -e "loop\nipmi_msghandler" | sudo tee /etc/modules-load.d/driver.conf
-```
-
-#### Add nvidia-runtime
-```bash
-sudo mkdir -p /etc/systemd/system/docker.service.d
-
-sudo tee /etc/systemd/system/docker.service.d/override.conf <<EOF
-[Service]
-Environment=PATH=$PATH:/run/nvidia/driver/usr/bin
-ExecStart=
-ExecStart=/usr/bin/dockerd --host=fd:// --add-runtime=nvidia=/run/nvidia/driver/usr/bin/nvidia-container-runtime
-EOF
-
-sudo systemctl daemon-reload
-sudo systemctl restart docker
-
-# Make sure the runtime is added
-docker info | grep -i "runtime"
-```
-
-#### CoreOS AWS image
-```sh
-# Run driver container in detached mode
-
-docker run -d --privileged --pid=host --restart=unless-stopped -v /run/nvidia:/run/nvidia:shared --name nvidia-driver nvidia/driver:410.72-4.14.81-coreos
-
-# Check logs to make sure driver container ran properly
-
-docker logs -f nvidia-driver
-
-# Test nvidia-smi with official CUDA image
-
-docker run --runtime=nvidia --rm nvidia/cuda:9.2-base sh -c 'uname -r && nvidia-smi --query-gpu=driver_version --format=csv,noheader'
-```
-
-#### In Kubernetes
-```sh
-# Set up the cluster for Container Linux (https://kubernetes.io/docs/setup/independent/install-kubeadm/#installing-kubeadm-kubelet-and-kubectl)
-
-# Run driver container 
-
-docker run -d --privileged --pid=host --restart=unless-stopped -v /run/nvidia:/run/nvidia:shared --name nvidia-driver nvidia/driver:410.72-4.14.81-coreos
-
-# Make sure the driver container is running before moving on to next steps
-docker ps -a | grep -i driver
-
-# Set default runtime to nvidia by editing /etc/systemd/system/docker.service.d
-
-sudo sed -i "s|nvidia=/run/nvidia/driver/usr/bin/nvidia-container-runtime|nvidia=/run/nvidia/driver/usr/bin/nvidia-container-runtime default-runtime=nvidia|" /etc/systemd/system/docker.service.d/override.conf
-
-sudo systemctl daemon-reload
-sudo systemctl restart docker
-
-# Deploy nvidia k8s-device-plugin (https://github.com/NVIDIA/k8s-device-plugin#enabling-gpu-support-in-kubernetes)
-
-# Deploy GPU pods
-
-# Set up monitoring
-
-# Install helm (https://docs.helm.sh/using_helm/#installing-the-helm-client) to /opt/bin
-
-# Initialize helm
-
-kubectl create serviceaccount tiller --namespace kube-system
-kubectl create clusterrolebinding tiller-cluster-rule --clusterrole=cluster-admin --serviceaccount=kube-system:tiller	 
-helm init --service-account tiller
-
-# Label GPU nodes
-
-kubectl label nodes <coreos-gpu-node> hardware-type=NVIDIAGPU
-
-# Install the monitoring charts
-
-helm repo add gpu-helm-charts https://nvidia.github.io/gpu-monitoring-tools/helm-charts
-helm repo update
-helm install gpu-helm-charts/prometheus-operator --name prometheus-operator --namespace monitoring
-helm install gpu-helm-charts/kube-prometheus --name kube-prometheus --namespace monitoring
-
-# Check the status of the pods
-
-kubectl get pods -n monitoring
-
-# Forward the port for Grafana
-
-kubectl -n monitoring port-forward $(kubectl get pods -n monitoring -lapp=kube-prometheus-grafana -ojsonpath='{range .items[*]}{.metadata.name}{"\n"}{end}') 3000 &
-
-# Open a browser window and type http://localhost:3000 to view the Nodes Dashboard in Grafana
-```
+Based on https://gitlab.com/nvidia/container-images/driver/-/tree/main/coreos?ref_type=heads & https://github.com/NVIDIA/gpu-driver-container/tree/main/fedora