NVIDIA AI Enterprise#

About NVIDIA AI Enterprise and Supported Platforms#

NVIDIA AI Enterprise is an end-to-end, cloud-native suite of AI and data analytics software, optimized, certified, and supported by NVIDIA with NVIDIA-Certified Systems.

Deploying the GPU Operator with NVIDIA AI Enterprise offers two installation options.

vGPU Guest Driver

Data Center Driver

Uses a a prebuilt vGPU driver image that is only available to NVIDIA AI Enterprise customers.

It is configured to use the NVIDIA License System (NLS). Installations on virtualization platforms must use the vGPU driver installation.

Installation is performed by downloading a Bash script from NVIDIA NGC and running the script.

Uses the GPU Operator Helm chart that is publicly available and GPU driver containers that are publicly available.

You must determine the supported driver branch, such as 550, for your NVIDIA AI Enterprise release.

Installation is performed by running the helm command.

For information about supported platforms, hypervisors, and operating systems, refer to the Product Support Matrix in the NVIDIA AI Enterprise documentation.

For information about using vGPU with Red Hat OpenShift, refer to NVIDIA AI Enterprise with OpenShift.

Installing GPU Operator Using the vGPU Driver#

Prerequisites#

  • A client configuration token has been generated for the client on which the script will install the vGPU guest driver. Refer to Generating a Client Configuration Token in the NVIDIA License System User Guide for more information.

  • An NGC CLI API key that is used to create an image pull secret. The secret is used to pull the prebuilt vGPU driver image from NVIDIA NGC. Refer to Generating Your NGC API Key in the NVIDIA NGC Private Registry User Guide for more information.

Procedure#

  1. Export the NGC CLI API key and your email address as environment variables:

    $ export NGC_API_KEY="M2Vub3QxYmgyZ..."
$ export NGC_USER_EMAIL="user@example.com"

  2. Go to the NVIDIA GPU Operator - Deploy Installer Script web page on NVIDIA NGC.

    Click the File Browser tab, identify your NVIDIA AI Enterprise release, click Actions button, and select Download File.

    Copy the downloaded script to the same directory as the client configuration token.

  3. Rename the client configuration token that you downloaded to client_configuration_token.tok. Originally, the client configuration token is named to match the pattern: client_configuration_token_mm-dd-yyyy-hh-mm-ss.tok.

  4. From the directory that contains the downloaded script and the client configuration token, run the script:

    $ bash gpu-operator-nvaie.sh install

Updating NLS Client License Token#

When the NLS client license token needs to be updated, use the procedure that matches the Kubernetes resource type that your licensing-config deployment uses:

Updating NLS Client License Token in Secret#

Secret-based licensing is supported starting with GPU Operator v25.10.0 and is recommended for all new deployments. Use the following procedure for deployments that use a Secret for the licensing-config:

  1. Create an empty vGPU license configuration file:

    $ sudo touch gridd.conf

  2. Generate and download a new NLS client license token, then rename the downloaded file to client_configuration_token.tok. For instructions, refer to Section 4.6 of the NLS User Guide.

  3. Create a new licensing-config-new Secret object in the gpu-operator namespace (make sure the name of the Secret is not already used in the Kubernetes cluster). Both the vGPU license configuration file and the NLS client license token are added to this Secret:

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

  4. Edit the ClusterPolicy resource:

    $ kubectl edit clusterpolicies.nvidia.com

  5. In the driver section, replace:

    licensingConfig:
    secretName: licensing-config

    with

    licensingConfig:
    secretName: licensing-config-new

  6. Save your changes and exit the editor (for example, :wq in vi).

    After you save, the GPU Operator sequentially redeploys all the driver pods with the new licensing information.

Updating NLS Client License Token in ConfigMap (deprecated)#

Warning

The configMap (configMapName) is deprecated and will be removed in a future release. It is strongly recommended that you migrate to use Secret-based licensing. Follow Updating NLS Client License Token in Secret for migration details.

Use the following procedure for deployments that use a ConfigMap for the licensing-config:

  1. Create an empty vGPU license configuration file:

    $ sudo touch gridd.conf

  2. Generate and download a new NLS client license token, then rename the downloaded file to client_configuration_token.tok. For instructions, refer to Section 4.6 of the NLS User Guide.

  3. Create a new licensing-config-new ConfigMap object in the gpu-operator namespace (make sure the name of the ConfigMap is not already used in the Kubernetes cluster). Both the vGPU license configuration file and the NLS client license token are added to this ConfigMap:

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

  4. Edit the ClusterPolicy resource:

    $ kubectl edit clusterpolicies.nvidia.com

  5. In the driver section, replace:

    licensingConfig:
    configMapName: licensing-config

    with

    licensingConfig:
    configMapName: licensing-config-new

  6. Save your changes and exit the editor (for example, :wq in vi).

    After you save, the GPU Operator sequentially redeploys all the driver pods with the new licensing information.

Installing GPU Operator Using the Data Center Driver#

This installation method is available for bare metal clusters or any cluster that does not use virtualization.

You must install the driver that matches the supported driver branch for your NVIDIA AI Enterprise release.

To identify the correct driver branch:

  1. Refer to the NVIDIA AI Enterprise Infra Release Branches table to determine the driver branch for your release.

    For example, NVIDIA AI Enterprise Infra 7.x uses the R580 driver branch.

  2. Refer to GPU Operator Component Matrix to identify the recommended GPU Operator version and driver version that uses the same driver branch.

After identifying the correct driver version, refer to Installing the NVIDIA GPU Operator for installation instructions. Use the --version=<supported-version> argument when installing with Helm.