NVIDIA AI Enterprise

NVIDIA AI Enterprise customers have access to a pre-configured GPU Operator within the NVIDIA Enterprise Catalog. The GPU Operator is pre-configured to simplify the provisioning experience with NVIDIA AI Enterprise deployments.

The pre-configured GPU Operator differs from the GPU Operator in the public NGC catalog. The differences are:

  • It is configured to use a prebuilt vGPU driver image (Only available to NVIDIA AI Enterprise customers)

  • It is configured to use containerd as the container runtime

  • It is configured to use the NVIDIA License System (NLS)

Prerequisite Tasks

Prior to installing the GPU Operator with NVIDIA AI Enterprise, the following tasks need to be completed for your cluster.

Create the gpu-operator-resources namespace:

$ kubectl create namespace gpu-operator-resources

Create an empty vGPU license configuration file:

$ sudo touch gridd.conf

Generate and download a NLS client license token. Please refer to Section 4.6 of the NLS User Guide for instructions.

Rename the NLS client license token that you downloaded to client_configuration_token.tok.

Create the licensing-config ConfigMap object in the gpu-operator-resources namespace. Both the vGPU license configuration file and the NLS client license token will be added to this ConfigMap:

$ kubectl create configmap licensing-config \
    -n gpu-operator-resources --from-file=gridd.conf --from-file=<path>/client_configuration_token.tok

Create an image pull secret in the gpu-operator-resources namespace for the private registry that contains the containerized NVIDIA vGPU software graphics driver for Linux for use with NVIDIA GPU Operator:

  • Set the registry secret name:

$ export REGISTRY_SECRET_NAME=ngc-secret
  • Set the private registry name:

$ export PRIVATE_REGISTRY=nvcr.io/nvaie
  • Create an image pull secret in the gpu-operator-resources namespace with the registry secret name and the private registry name that you set. Replace user-name, password, and e-mail-address with your credentials for logging into the Docker server:

$ kubectl create secret docker-registry ${REGISTRY_SECRET_NAME} \
    --docker-server=${PRIVATE_REGISTRY} --docker-username=user-name \
    --docker-password=password \
    --docker-email=e-mail-address -n gpu-operator-resources

The GPU Operator is now ready to install. Please refer to Install NVIDIA GPU Operator section for installing the GPU Operator.