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27 changes: 14 additions & 13 deletions admin/workspace-management/gpu-acceleration.md
Original file line number Diff line number Diff line change
Expand Up @@ -3,22 +3,23 @@ title: "GPU acceleration"
description: Learn how to use GPUs with workspaces.
---

GPUs can be used for performing tasks such as machine learning within
workspaces.
Graphical processing units (GPUs) are useful with compute-intensive workloads,
such as those involved with data science/machine learning projects.

By default, users cannot create workspaces with GPUs until a site manager
configures and enables this feature.
You can allocate GPUs to workspaces once a site manager configures and enables
this feature. Enabling GPU acceleration requires that you've configured your
Kubernetes cluster and
[scheduled GPUs](https://kubernetes.io/docs/tasks/manage-gpus/scheduling-gpus/).
For instructions on how to schedule GPUs with your specific cloud vendor, see:

### Step 1: Configure your Kubernetes cluster
- [Amazon Elastic Container Service](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/ecs-gpu.html)
- [Azure Kubernetes Service](https://docs.microsoft.com/en-us/azure/aks/gpu-cluster)
- [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine/docs/how-to/gpus)

<a href="https://kubernetes.io/docs/tasks/manage-gpus/scheduling-gpus/"
target="_blank" rel="noreferrer noopener">Configure</a> your Kubernetes cluster
with the available GPUs and all necessary device plugins and drivers.
Once your Kubernetes cluster has been configured, you can enable GPUs in Coder.

### Step 2: Enable GPU vendor in Coder

Go to **Manage** > **Admin**. On the **Infrastructure** tab, find the **GPU
Vendor** setting, and change it to the GPU vendor of choice (either **AMD** or
**Nvidia**). Click **Save Vendor**.
To do so, go to **Manage** > **Admin**. On the **Infrastructure** tab, find the
**GPU Vendor** setting, and change it to the GPU vendor of choice (either
**AMD** or **Nvidia**). Click **Save Vendor**.

![Enable GPU vendor](../../assets/admin/gpu.png)