Add GPU section to OCP docs

docs/openshift/gpus/intro-to-gpus-in-nerc-ocp.md

@@ -0,0 +1,44 @@
+# Introduction to GPUs in NERC OpenShift
+
+NERC OCP clusters leverage the [NVIDIA GPU Operator](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/index.html) as well as the [Node Feature Discovery Operator](https://docs.openshift.com/container-platform/4.15/hardware_enablement/psap-node-feature-discovery-operator.html) to manage and deploy GPU worker nodes to clusters.
+
+## NERC GPU Worker Node Arhitectures
+
+The NERC OpenShift environment currently supports two different NVIDIA GPU products: 
+1. NVIDIA-A100-SXM4-40GB (A100) 
+2. Tesla-V100-PCIE-32GB (V100)
+
+A100 worker nodes contain 4 individual gpus, each with 40GB of memory
+V100 worker nodes contain 1 gpu with 32 GB of memory
+
+## Accessing GPU Resources 
+
+Access to GPU nodes is handled via OCP project allocations through NERC ColdFront. By default, user projects in NERC OCP clusters do not have access to GPUs and access must be granted through the user's ColdFront allocation by a NERC admin. 
+
+## Deploying Workloads to GPUs
+
+There are two ways to deploy workloads on GPU nodes:
+
+1. Deploy directly in your OCP namespace:
+
+In your project namespace you can deploy a GPU workload by explicitely requesting a GPU in your manifest, like for instance:
+```
+apiVersion: v1
+kind: Pod
+metadata:
+  name: sample-gpu-request
+spec:
+  restartPolicy: Never
+  containers:
+  - name: sample-gpu-request
+    image: <your-image-url>
+    ...
+    ...
+    resources:
+      limits:
+        nvidia.com/gpu: 1
+```
+
+2. Deploy through RHOAI 
+
+See [Populate the data science project with a Workbench](https://github.com/nerc-project/nerc-docs/blob/main/docs/openshift-ai/data-science-project/using-projects-the-rhoai.md#populate-the-data-science-project-with-a-workbench) for selecting GPU options. 

docs/openshift/index.md

@@ -37,6 +37,10 @@ the list below.
 
 -   [Storage Overview](storage/storage-overview.md)
 
+## GPUs
+
+-   [Intro to GPUs in NERC OCP Clusters](gpus/intro-to-gpus-in-nerc-ocp.md)
+
 ## Deleting Applications
 
 -   [Deleting your applications](applications/deleting-applications.md)