Step #2: Create a VM Class

NVIDIA Docs Hub NVIDIA LaunchPad Optimize AI and Data Science Workloads (VMware Tanzu) Step #2: Create a VM Class

To size Tanzu Kubernetes cluster nodes, you specify the virtual machine class. A VM class is a request for resource reservations on the VM for processing power (CPU and GPU). For example, guaranteed-large with eight vCPU and NVIDIA A30 GPU. VMware vSphere with Tanzu provides default classes or creates your own. We create a new VM class that offers GPU acceleration using the steps below. DevOps admins will then create and scale Tanzu Kubernetes Clusters with the VM Classes associated with their namespace from the command line.

Note

The steps below illustrate creating a VM class using NVIDIA AI Enterprise software partitioning. But it is important to note a VM class can use either NVIDIA AI Enterprise software partitioning or Multi-Instance GPU (MIG). MIG is available to NVIDIA Ampere GPUs (such as NVIDIA A30, A100). VM Classes can also be used with NVIDIA Networking. The steps for creating these VM classes are the same, apart from GPU sharing and networking PCI device types.

From vCenter, navigate to Workload Management.
Select Services tab and click Manage under the VM Service card.
Select VM Classes and the Create VM Class card.
Enter a Name for the VM class, such as vm-class-t4-16gb.

Important

Users interacting with the VM class via the Kubernetes CLI will not easily see what GPU is attached to the associated node or the GPU memory made available. Therefore, a descriptive name that includes the GPU type and associated GPU memory should be used.
Select the ADD PCI DEVICE drop-down and select NVIDIA vGPU.
Select a GPU model from the drop-down.

Note

All GPUs within any host attached to the Tanzu cluster will be available. The GPU available for your lab may vary.
Using the information specified in the name of the VM class, populate the available options for the selected GPU type.
- GPU Sharing: Time Sharing
- GPU Mode: Compute
Note

There are two class reservation types: guaranteed and best effort. A guaranteed class fully reserves its configured resources. Best effort class allows resources to be overcommitted. Within a production environment, typically, the guaranteed class type is used.
Click Next.
Inspect the Review and Confirm page information and click Finish.

You have successfully created a VM class using VM Classes with NVIDIA AI Enterprise software partitioning.