Updated GPU Operator docs version to 1.2.0 (#61)

Author: Farshad Ghodsian

README.md

@@ -1,6 +1,8 @@
 # AMD GPU Operator
 
-:book: GPU Operator Documentation Site: https://instinct.docs.amd.com/projects/gpu-operator
+## :book: GPU Operator Documentation Site
+
+For the most detailed and up-to-date documentation please visit our Instinct Documenation site: [https://instinct.docs.amd.com/projects/gpu-operator](https://instinct.docs.amd.com/projects/gpu-operator)
 
 ## Introduction
 
@@ -53,12 +55,13 @@ helm install cert-manager jetstack/cert-manager \
 ### 1. Add the AMD Helm Repository
 
 ```bash
-helm install amd-gpu-operator --namespace kube-amd-gpu --create-namespace https://github.com/ROCm/gpu-operator/releases/download/v1.0.0/gpu-operator-charts-v1.0.0.tgz
+helm repo add rocm https://rocm.github.io/gpu-operator
+helm repo update
 ```
 
 ### 2. Install the Operator
 
-Basic installation:
+#### Basic installation
 
 ```bash
 helm install amd-gpu-operator rocm/gpu-operator-charts \
@@ -67,19 +70,17 @@ helm install amd-gpu-operator rocm/gpu-operator-charts \
   --version=v1.2.0
 ```
 
-```{note}
-Installation Options
-  - Skip NFD installation: `--set node-feature-discovery.enabled=false`
-  - Skip KMM installation: `--set kmm.enabled=false`
-```
+#### Installation Options
 
-```{warning}
-  It is strongly recommended to use AMD-optimized KMM images included in the operator release.
-```
+* Skip NFD installation: `--set node-feature-discovery.enabled=false`
+* Skip KMM installation: `--set kmm.enabled=false`
+
+> [!WARNING]
+> It is strongly recommended to use AMD-optimized KMM images included in the operator release. This is not required when installing the GPU Operator on Red Hat OpenShift.
 
 ### 3. Install Custom Resource
 
-After the installation of AMD GPU Operator, you need to create the `DeviceConfig` custom resource in order to trigger the operator to start to work. By preparing the `DeviceConfig` in the YAML file, you can create the resouce by running ```kubectl apply -f deviceconfigs.yaml```. For custom resource definition and more detailed information, please refer to [Custom Resource Installation Guide](https://dcgpu.docs.amd.com/projects/gpu-operator/en/latest/installation/kubernetes-helm.html#install-custom-resource).
+After the installation of AMD GPU Operator, you need to create the `DeviceConfig` custom resource in order to trigger the operator to start to work. By preparing the `DeviceConfig` in the YAML file, you can create the resouce by running ```kubectl apply -f deviceconfigs.yaml```. For custom resource definition and more detailed information, please refer to [Custom Resource Installation Guide](https://instinct.docs.amd.com/projects/gpu-operator/en/latest/installation/kubernetes-helm.html#install-custom-resource).
 
 ### Grafana Dashboards
 

docs/_static/amd-gpu-operator-diagram.png

@@ -6,7 +6,7 @@
 external_projects_current_project = "amd-gpu-operator"
 
 project = "AMD Instinct Documentation"
-version = "1.1.0"
+version = "1.2.0"
 release = version
 html_title = f"AMD GPU Operator {version}"
 author = "Advanced Micro Devices, Inc."

docs/conf.py

@@ -95,7 +95,8 @@ Below is an example of a full DeviceConfig CR that can be used to install the AM
         # (Optional) Specifying metrics exporter image is optional. Default imagename shown here if not specified.
         image: rocm/device-metrics-exporter:v1.2.0 # Change this to trigger metrics exporter upgrade on CR update
         config:
-          name: exporter-configmap # Name of the ConfigMap that contains the metrics exporter configuration
+          # Name of the ConfigMap that contains the metrics exporter configuration.
+          name: gpu-config # (Optional) If the configmap does not exist the DeviceConfig will show a validation error and not start any plugin pods
         upgradePolicy:
           #(Optional) If no UpgradePolicy is mentioned for any of the components but their image is changed, the daemonset will
           # get upgraded according to the defaults, which is `upgradeStrategy` set to `RollingUpdate` and `maxUnavailable` set to 1.
@@ -132,8 +133,6 @@ The below is an example of the minimal DeviceConfig CR that can be used to insta
     metricsExporter:
       enable: true # To enable/disable the metrics exporter, disabled by default
       serviceType: "NodePort" # Node port for metrics exporter service
-      config:
-        name: exporter-configmap
       nodePort: 32500
     selector:
       feature.node.kubernetes.io/amd-gpu: "true"

docs/fulldeviceconfig.rst

@@ -1,7 +1,7 @@
 # OpenShift (Helm)
 
 ```{warning}
-Installing via Helm is not a recommended method for Red Hat OpenShift. Users wishing to use the AMD GPU with OpenShift should consider using the OLM method instead.
+Installing via Helm is not a recommended method for Red Hat OpenShift. Users wishing to use the AMD GPU with OpenShift should consider using the OLM method instead. This method is not supported in the latest version. As a result, this page will be removed in the next release.
 ```
 
 This guide walks through installing the AMD GPU Operator on an OpenShift cluster using Helm.

docs/installation/openshift-helm.md

@@ -84,9 +84,9 @@ spec:
     #  name: exporterimagesecret
 
     # metrics config in configmap
-    config:
+    # config:
       # configmap name, example config in example/metricsExporter/config.json
-      name: configmap-name
+    #  name: gpu-config
 
   # Specify the testrunner config
   testRunner: