From 04884fa09daed5027fbabedb288be4c48a12d26b Mon Sep 17 00:00:00 2001
From: Fredrik Liv <fredrik.liv@elastisys.com>
Date: Mon, 16 Dec 2024 09:58:20 +0100
Subject: [PATCH] Added page for how to use GPU

---
 docs/user-guide/gpu.md | 48 ++++++++++++++++++++++++++++++++++++++++++
 mkdocs.yml             |  1 +
 2 files changed, 49 insertions(+)
 create mode 100644 docs/user-guide/gpu.md

diff --git a/docs/user-guide/gpu.md b/docs/user-guide/gpu.md
new file mode 100644
index 00000000000..d1a2ce3bbab
--- /dev/null
+++ b/docs/user-guide/gpu.md
@@ -0,0 +1,48 @@
+---
+search:
+  boost: 2
+---
+
+# Using GPU Workload in Welkin
+
+!!! elastisys "For Elastisys Managed Services Customers"
+    You can order a new Environment with GPU support by filing a [service ticket](https://elastisys.atlassian.net/servicedesk/).
+    Make sure to specify the need for GPU Nodes in "Additional information or comments".
+    If you are unsure, get in touch with your account manager.
+
+As the demand for AI, machine learning, and data science workloads grows, Kubernetes provides a flexible and scalable platform to manage these applications.
+In this guide, we'll focus on how to use GPU in the Welkin platform.
+
+> [!NOTE]
+> Not all infrastructure providers have support for GPU.
+> Check with the platform administrator to find out if your environment has support for GPU workload.
+
+## Deployment
+
+To use GPU resources in your cluster, you need to create a deployment that is using the resource `nvidia.com/gpu`.
+Here's an example of how to configure GPU resources for a Pod:
+
+```yaml
+apiVersion: v1
+kind: Pod
+metadata:
+  name: cuda-vectoradd
+spec:
+  restartPolicy: OnFailure
+  containers:
+  - name: cuda-vectoradd
+    image: "nvcr.io/nvidia/k8s/cuda-sample:vectoradd-cuda11.7.1-ubuntu20.04"
+    resources:
+      limits:
+        nvidia.com/gpu: 1
+```
+
+> [!NOTE]
+> If your cluster is using the cluster autoscaling feature and there's currently not enough resources, the autoscaler will create one for you.
+> It might take a couple of minutes for the new node to join the cluster and to install all the pre-requisites.
+
+### Further Reading
+
+- [Kubernetes Schedule GPU Documentation](https://kubernetes.io/docs/tasks/manage-gpus/scheduling-gpus/)
+- [Kubernetes Cluster Autoscaler Documentation](https://kubernetes.io/docs/concepts/cluster-administration/cluster-autoscaling/)
+- [Cluster Autoscaler FAQ](https://github.com/kubernetes/autoscaler/blob/master/cluster-autoscaler/FAQ.md)
diff --git a/mkdocs.yml b/mkdocs.yml
index 81cfb9ff1a9..c42c3d4d3e8 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -150,6 +150,7 @@ nav:
           - "Prepare Your Identity Provider (IdP)": "user-guide/prepare-idp.md"
           - "Container registry": "user-guide/registry.md"
           - "Continuous Development": "user-guide/continous-development.md"
+          - "GPU": "user-guide/gpu.md"
           - "Network Model": "user-guide/network-model.md"
           - "Kubernetes API": "user-guide/kubernetes-api.md"
           - "Kubernetes UI": "user-guide/kubernetes-ui.md"