Add GPU subsection to OCP docs

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

@@ -0,0 +1,52 @@
+# 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
+```
+
+1. 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)