Quick Start Guide#

NVIDIA AI Enterprise Quick Start Guide provides minimal instructions for a bare-metal, single-node deployment of NVIDIA AI Enterprise on a third-party NVIDIA-certified system and for using a Cloud License Service (CLS) instance to serve licenses.

If you need complete instructions for installing and configuring NVIDIA AI Enterprise, are using NVIDIA AI Enterprise in an NVIDIA vGPU deployment, or are using multiple nodes, refer to the NVIDIA AI Enterprise Deployment Guides.

Refer to the NVIDIA License System User Guide if you use Delegated License Service (DLS) instances to serve licenses.

Note

These instructions do not apply to NVIDIA DGX systems. For information about how to use these systems, refer to NVIDIA DGX Systems.

Activating the Accounts for Getting NVIDIA AI Enterprise#

After your order for NVIDIA AI Enterprise is processed, you will receive an order confirmation message. This message contains information that you need for getting NVIDIA AI Enterprise and technical support from NVIDIA. To get NVIDIA AI Enterprise and technical support from NVIDIA, you must have an NVIDIA Enterprise Account, which provides login access to the following NVIDIA web properties:

NVIDIA NGC, which provides access to all enterprise software, services, and management tools included in NVIDIA AI Enterprise
NVIDIA Licensing Portal, which provides access to your entitlements and options for managing your NVIDIA AI Enterprise license servers
NVIDIA Enterprise Support Portal, which provides access to NVIDIA AI Enterprise support services

These web properties can be reached from the NVIDIA Application Hub. To activate the accounts for getting NVIDIA AI Enterprise, create or link to an NVIDIA Enterprise Account:

Creating your NVIDIA Enterprise Account
Linking an Evaluation Account to an NVIDIA Enterprise Account for Purchased Licenses

Before You Begin#

Before following the procedures in this guide, ensure that the following prerequisites are met:

You have a third-party NVIDIA-certified server platform that supports NVIDIA AI Enterprise.
One or more NVIDIA GPUs that support NVIDIA AI Enterprise are installed in your server platform.
You have a valid NVIDIA software subscription.
If you are using a GPU that is supplied with NVIDIA AI Enterprise software, such as the NVIDIA H100 PCIe GPU, your NVIDIA AI Enterprise license for H100 has been activated.

For information about supported hardware and software, and any known issues for this release of NVIDIA AI Enterprise, refer to the NVIDIA AI Enterprise Release Notes.

Your Order Confirmation Message#

After your order for NVIDIA AI Enterprise is processed, you will receive an order confirmation message to which your NVIDIA Entitlement Certificate is attached. Your NVIDIA Entitlement Certificate contains your product activation keys and provides instructions for using the certificate.

If you are a data center administrator, follow the instructions in the NVIDIA Entitlement Certificate to use the certificate. Otherwise, forward your order confirmation message, including the attached NVIDIA Entitlement Certificate, to a data center administrator in your organization.

NVIDIA Enterprise Account Requirements#

To get NVIDIA AI Enterprise, you must have a suitable NVIDIA Enterprise Account for getting NVIDIA AI Enterprise and technical support from NVIDIA.

Whether or not you have a suitable NVIDIA Enterprise Account depends on whether you have previously purchased NVIDIA AI Enterprise.

If you have previously purchased NVIDIA AI Enterprise, you already have a suitable NVIDIA Enterprise Account.

To use this account to get NVIDIA AI Enterprise, download the software assets that you require from the NVIDIA AI Enterprise Infra Release 5 collection on NVIDIA NGC. For details, refer to Accessing the NVIDIA AI Enterprise Software Suite.

If you have obtained an evaluation license but have not previously purchased NVIDIA AI Enterprise, you do not have a suitable NVIDIA Enterprise Account. To create a suitable NVIDIA Enterprise Account, follow the Register link in the instructions for using the certificate to create an account for your purchased licenses. You can choose to create a separate account for your purchased licenses or link your existing account for an evaluation license to the account for your purchased licenses.
- To create a separate account for your purchased licenses, follow the instructions in Creating your NVIDIA Enterprise Account, specifying a different e-mail address than the address with which you created your existing account.
- To link your existing account for an evaluation license to the account for your purchased licenses, follow the instructions in Linking an Evaluation Account to an NVIDIA Enterprise Account for Purchased Licenses, specifying the e-mail address with which you created your existing account.
If you have not previously purchased NVIDIA AI Enterprise, you do not have a suitable NVIDIA Enterprise Account.

To create a suitable NVIDIA Enterprise Account, follow the Register link in the instructions for using the certificate to create your account. For details, refer to Creating your NVIDIA Enterprise Account.

Creating your NVIDIA Enterprise Account#

If you do not have an NVIDIA Enterprise Account, you must create an account to be able to log in to the web properties for getting NVIDIA AI Enterprise and technical support from NVIDIA. For details on these web properties, refer to Activating the Accounts for Getting NVIDIA AI Enterprise.

If you already have an account, skip this task and go to Installing Your NVIDIA AI Enterprise License Server and License Files. However, if you have an account that was created for an evaluation license and you want to access licenses that you purchased, you must repeat the registration process when you receive your purchased licenses. You can choose to create a separate account for your purchased licenses or link your existing account for an evaluation license to the account for your purchased licenses.

To create a separate account for your purchased licenses, perform this task, specifying a different e-mail address than the address with which you created your existing account.
To link your existing account for an evaluation license to the account for your purchased licenses, follow the instructions in Linking an Evaluation Account to an NVIDIA Enterprise Account for Purchased Licenses, specifying the e-mail address with which you created your existing account.

Before you begin, ensure that you have your order confirmation message.

In the instructions for using your NVIDIA Entitlement Certificate, follow the Register link.
Fill out the form on the NVIDIA Enterprise Account Registration page and click REGISTER. A message confirming that an account has been created appears. An e-mail instructing you to log in to your account on the NVIDIA Application Hub is sent to the e-mail address you provided.
Open the e-mail instructing you to log in to your account and click Log In.
On the NVIDIA Application Hub Login page that opens, in the text-entry field, type the e-mail address you provided and click Sign In.
On the Create Your Account page that opens, provide and confirm a password for the account and click Create Account. A message prompting you to verify your e-mail address appears. An e-mail instructing you to verify your e-mail address is sent to the e-mail address you provided.
Open the e-mail instructing you to verify your e-mail address and click Verify Email Address. A message confirming that your email address is confirmed appears.

From the NVIDIA Application Hub page, you can now log in to the web properties that are listed in Activating the Accounts for Getting NVIDIA AI Enterprise.

Linking an Evaluation Account to an NVIDIA Enterprise Account for Purchased Licenses#

If you have an account that was created for an evaluation license, you must repeat the registration process when you receive your purchased licenses. To link your existing account for an evaluation license to the account for your purchased licenses, register for an NVIDIA Enterprise Account with the e-mail address with which you created your existing account.

If you want to create a separate account for your purchased licenses, follow the instructions in Creating your NVIDIA Enterprise Account, specifying a different e-mail address than the address with which you created your existing account.

In the instructions for using the NVIDIA Entitlement Certificate for your purchased licenses, follow the Register link.
Fill out the form on the NVIDIA Enterprise Account Registration page, specifying the e-mail address with which you created your existing account, and click Register.

NVIDIA Enterprise Account Registration page

When a message stating that your e-mail address is already linked to an evaluation account is displayed, click LINK TO NEW ACCOUNT.

Log in to the NVIDIA Licensing Portal with the credentials for your existing account.

Installing Your NVIDIA AI Enterprise License Server and License Files#

The NVIDIA License System is used to serve a pool of floating licenses to licensed NVIDIA software products. The NVIDIA License System is configured with licenses obtained from the NVIDIA Licensing Portal.

Note

These instructions cover only the configuration of a Cloud License Service (CLS) instance. Refer to the NVIDIA License System User Guide if you need complete instructions or use Delegated License Service (DLS) instances to serve licenses.

Introduction to NVIDIA Software Licensing#

To activate licensed functionalities, a licensed client must obtain a software license when it is booted.

A client with a network connection obtains a license by leasing it from an NVIDIA License System service instance. The service instance serves the license to the client over the network from a pool of floating licenses obtained from the NVIDIA Licensing Portal. The license is returned to the service instance when the licensed client no longer requires the license.

Performing an Express CLS Installation#

Performing an express CLS installation creates a license server that the NVIDIA License System automatically binds to and installs on the default CLS instance. The license server that you create defines the set of licenses to be allotted to an NVIDIA License System instance.

If no default CLS instance exists, the NVIDIA License System creates a default instance for you. After you perform an express installation, no further action is required to complete the initial configuration of the CLS instance. The instance is ready to serve licenses to clients.

In the NVIDIA Licensing Portal, navigate to the organization or virtual group for which you want to perform an express CLS installation.
1. If you are not already logged in, log in to the NVIDIA Application Hub and click NVIDIA LICENSING PORTAL to go to the NVIDIA Licensing Portal.
2. Optional: If your assigned roles give you access to multiple virtual groups, click View settings at the top right of the page, and in the My Info window that opens, select the virtual group from the Virtual Group drop-down list, and close the My Info window.
If no license servers have been created for your organization or virtual group, the NVIDIA Licensing Portal dashboard displays a message asking if you want to create a license server.
In the left navigation pane of the NVIDIA Licensing Portal dashboard, expand LICENSE SERVER and click CREATE SERVER. The Create License Server wizard opens.
On the Step 1 - Identification page of the wizard, provide the details of your license server.
1. In the Name field, enter your choice of name for the license server.
2. In the Description field, enter a text description of the license server. This description is required and will be displayed on the details page for the license server that you are creating.
3. Click NEXT STEP.
On the Step 2 - Features page of the wizard, add the licenses for the products that you want to allot to this license server. For each product, add the licenses as follows:
1. In the list of products, select the product for which you want to add licenses.
2. In the text-entry field in the ADDED column, enter the number of licenses for the product that you want to add.
3. Click NEXT STEP.
On the Step 3 - Environment page, select Cloud (CLS), select the Express installation option that is added to the page, and click NEXT STEP.
On the Step 4 - Configuration page, select the leasing mode that you require. If the license server is to be used for networked licensing, you can simplify the management of licensed products on the server by selecting the Standard Networked Licensing mode.
Click CREATE SERVER.

Generating a Client Configuration Token for a CLS Instance#

Log in to the NVIDIA Application Hub and click NVIDIA LICENSING PORTAL to go to the NVIDIA Licensing Portal.
If your assigned roles give you access to multiple virtual groups, select the virtual group for which you are managing licenses from the list of virtual groups at the top right of the NVIDIA Licensing Portal dashboard.
In the left navigation pane, click SERVICE INSTANCES.

On the Service Instances page that opens, from the Actions menu for the CLS instance for which you want to generate a client configuration token, choose Generate client configuration token.
In the Generate Client Configuration Token pop-up window that opens, select the references that you want to include in the client configuration token.
1. From the list of scope references, select the scope references that you want to include.
You must select at least one scope reference.

Each scope reference specifies the license server that will fulfill a license request.
1. Optional: Click the Fulfillment class references tab, and from the list of fulfillment class references, select the fulfillment class references that you want to include.
  
  Including fulfillment class references is optional.
2. Optional: In the Expiration section, select an expiration date for the client configuration token. If you do not select a date, the default token expiration time is 12 years.
3. Click DOWNLOAD CLIENT CONFIGURATION TOKEN.
  
  A file named client_configuration_token_mm-dd-yyyy-hh-mm-ss.tok is saved to your default downloads folder.

Installing and Licensing NVIDIA AI Enterprise Software Components#

The NVIDIA NGC Catalog#

NVIDIA AI Enterprise components are distributed through the NVIDIA NGC Catalog. Infrastructure and workload management components are distributed as resources in the NVIDIA AI Enterprise Infra Release 5 collection. Tools for AI development and use cases are available from the NVIDIA AI Enterprise Software Suite.

Resources#

Infrastructure and workload management components of NVIDIA AI Enterprise are distributed as resources in the NVIDIA AI Enterprise Infra Release 5 collection. The NVIDIA AI Enterprise Infra Release 5 collection contains the following resources:

GPU Operator
Network Operator
NVIDIA Base Command Manager Essentials
vGPU Guest Driver, Ubuntu 22.04

Before downloading any NVIDIA AI Enterprise software assets, ensure that you have signed in to NVIDIA NGC from the NVIDIA NGC Sign In page.

Go to the NVIDIA AI Enterprise Infra Release 5 collection on NVIDIA NGC.
Click the Entities tab and select the resource that you are interested in.
Click Download and, from the menu that opens, choose to download the resource by using a direct download in the browser, the displayed wget command, or the CLI.

Accessing the NVIDIA AI Enterprise Software Suite#

Tools for AI development and use cases are available from the NVIDIA AI Enterprise Software Suite, which is distributed through the NVIDIA NGC Catalog.

Before downloading any NVIDIA AI Enterprise software assets, ensure that you have signed in to NVIDIA NGC from the NVIDIA NGC Sign In page.

View the NVIDIA AI Enterprise Software Suite on NVIDIA NGC.
- Go to the NVIDIA AI Enterprise Supported page on NVIDIA NGC.
- Visit the NVIDIA NGC site and set the NVIDIA AI Enterprise Support filter.
Browse the NVIDIA AI Enterprise Software Suite to find software assets that you are interested in.
For each software asset that you are interested in, click the asset to learn more about or download the asset.

Installing the NVIDIA AI Enterprise Graphics Driver on Ubuntu from a Debian Package#

The NVIDIA AI Enterprise graphics driver for Ubuntu is distributed as a Debian package file. This task requires sudo privileges.

Copy the NVIDIA AI Enterprise Linux driver package, for example, nvidia-linux-grid-550_550.90.07_amd64.deb, to the guest VM where you are installing the driver.
Log in to the guest VM as a user with sudo privileges.
Open a command shell and change to the directory that contains the NVIDIA AI Enterprise Linux driver package.

From the command shell, run the command to install the package.

$ sudo apt-get install ./nvidia-linux-grid-550_550.90.07_amd64.deb

Verify that the NVIDIA driver is operational.
1. Reboot the system and log in.
2. After the system has rebooted, confirm that you can see your NVIDIA vGPU device in the output from the nvidia-smi command.
  $ nvidia-smi

Configuring a Licensed Client#

A client with a network connection obtains a license by leasing it from an NVIDIA License System service instance. The service instance serves the license to the client over the network from a pool of floating licenses obtained from the NVIDIA Licensing Portal. The license is returned to the service instance when the licensed client no longer requires the license.

The graphics driver creates a default location in which to store the client configuration token on the client.

The process for configuring a licensed client is the same for CLS and DLS instances but depends on the OS that is running on the client.

Configuring a Licensed Client on Linux with Default Settings#

Perform this task from the client.

As root, open the file /etc/nvidia/gridd.conf in a plain-text editor, such as vi.
$ sudo vi /etc/nvidia/gridd.conf
Note

You can create the /etc/nvidia/gridd.conf file by copying the supplied template file /etc/nvidia/gridd.conf.template.

Add the FeatureType configuration parameter to the file /etc/nvidia/gridd.conf on a new line as FeatureType="value". value depends on the type of GPU assigned to the licensed client that you are configuring.

GPU Types and Values#

GPU Type

Value

NVIDIA vGPU

1: NVIDIA AI Enterprise automatically selects the correct type of license based on the vGPU type.

Physical GPU

The feature type of a GPU in pass-through mode or a bare-metal deployment:

0: NVIDIA Virtual Applications

2: NVIDIA RTX Virtual Workstation

4: NVIDIA Virtual Compute Server

This example shows how to configure a licensed Linux client for NVIDIA Virtual Compute Server.
# /etc/nvidia/gridd.conf.template - Configuration file for NVIDIA Grid Daemon
…
# Description: Set Feature to be enabled
# Data type: integer
# Possible values:
# 0 => for unlicensed state
# 1 => for NVIDIA vGPU
# 2 => for NVIDIA RTX Virtual Workstation
# 4 => for NVIDIA Virtual Compute Server
FeatureType=4
…

Copy the client configuration token to the /etc/nvidia/ClientConfigToken directory.
Ensure that the file access modes of the client configuration token allow the owner to read, write, and execute the token, and the group and others only to read the token.
1. Determine the current file access modes of the client configuration token.
  # ls -l client-configuration-token-directory
2. If necessary, change the mode of the client configuration token to 744.
  # chmod 744 client-configuration-token-directory/client_configuration_token_*.tok
client-configuration-token-directory - The directory to which you copied the client configuration token in the previous step.
Save your changes to the /etc/nvidia/gridd.conf file and close the file.
Restart the nvidia-gridd service.

The NVIDIA service on the client should now automatically obtain a license from the CLS or DLS instance.

Verifying the NVIDIA AI Enterprise License Status of a Licensed Client#

After configuring a client with an NVIDIA AI Enterprise license, verify the license status by displaying the licensed product name and status.

To verify the license status of a licensed client, run nvidia-smi with the -q or --query option from the licensed client, not the hypervisor host. If the product is licensed, the expiration date is shown in the license status.

nvidia-smi -q
==============NVSMI LOG==============

Timestamp                                 : Wed Nov 23 10:52:59 2022
Driver Version                            : 525.60.06
CUDA Version                              : 12.0

Attached GPUs                             : 2
GPU 00000000:02:03.0
    Product Name                          :
    Product Brand                         : NVIDIA Virtual Compute Server
    Product Architecture                  : Ampere
    Display Mode                          : Enabled
    Display Active                        : Disabled
    Persistence Mode                      : Enabled
    MIG Mode
        Current                           : Disabled
        Pending                           : Disabled
    Accounting Mode                       : Disabled
    Accounting Mode Buffer Size           : 4000
    Driver Model
        Current                           : N/A
        Pending                           : N/A
    Serial Number                         : N/A
    GPU UUID                              : GPU-ba5b1e9b-1dd3-11b2-be4f-98ef552f4216
    Minor Number                          : 0
    VBIOS Version                         : 00.00.00.00.00
    MultiGPU Board                        : No
    Board ID                              : 0x203
    Board Part Number                     : N/A
    GPU Part Number                       : 25B6-890-A1
    Module ID                             : N/A
    Inforom Version
        Image Version                     : N/A
        OEM Object                        : N/A
        ECC Object                        : N/A
        Power Management Object           : N/A
    GPU Operation Mode
        Current                           : N/A
        Pending                           : N/A
    GSP Firmware Version                  : N/A
    GPU Virtualization Mode
        Virtualization Mode               : VGPU
        Host VGPU Mode                    : N/A
    vGPU Software Licensed Product Product Name : NVIDIA Virtual Compute Server License Status : Licensed (Expiry: 2022-11-23 10:41:16 GMT)
    …
    …

Installing the NVIDIA Container Toolkit#

Use NVIDIA Container Toolkit to build and run GPU-accelerated Docker containers. The toolkit includes a container runtime library and utilities to configure containers to use NVIDIA GPUs automatically.

Ensure that the following software is installed in the guest VM:

Docker 20.10 for your Linux distribution. For instructions, refer to Install Docker Engine on Ubuntu in the Docker product manuals.
The NVIDIA AI Enterprise graphics driver. For instructions, refer to Installing the NVIDIA AI Enterprise Graphics Driver on Ubuntu from a Debian Package.

Note

You do not need to install the NVIDIA CUDA Toolkit on the hypervisor host.

Set up the GPG key and configure apt to use NVIDIA Container Toolkit packages in the file /etc/apt/sources.list.d/nvidia-docker.list.

$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

Download information from all configured sources about the latest versions of the packages and install the nvidia-container-toolkit package.
$ sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
Restart the Docker service.
$ sudo systemctl restart docker

Verifying the Installation of NVIDIA Container Toolkit#

Run the nvidia-smi command contained in the latest official NVIDIA CUDA Toolkit image that is compatible with the release of the NVIDIA CUDA Toolkit driver that is running on your machine.
Note

Do not use a release of the NVIDIA CUDA Toolkit image later than the release of the NVIDIA CUDA Toolkit driver that is running on your machine. For a list of all NVIDIA CUDA Toolkit images, refer to nvidia/cuda on Docker Hub.
$ docker run --gpus all nvidia/cuda:12.4.0-base-ubuntu22.04 nvidia-smi

Start a GPU-enabled container on any two available GPUs.

$ docker run --gpus 2 nvidia/cuda:12.4.0-base-ubuntu22.04 nvidia-smi

Start a GPU-enabled container on two specific GPUs identified by their index numbers.

$ docker run --gpus '"device=1,2"' nvidia/cuda:12.4.0-base-ubuntu22.04 nvidia-smi

Start a GPU-enabled container on two specific GPUs with one GPU identified by its UUID and the other GPU identified by its index number.
$ docker run --gpus '"device=UUID-ABCDEF,1"' nvidia/cuda:12.4.0-base-ubuntu22.04 nvidia-smi

Specify a GPU capability for the container.

$ docker run --gpus all,capabilities=utility nvidia/cuda:12.4.0-base-ubuntu22.04 nvidia-smi

Installing Software Distributed as Container Images#

The NGC container images accessed through the NVIDIA NGC Catalog include the AI and data science applications and frameworks. Each container image for an AI and data science application or framework contains the entire user-space software stack that is required to run the application or framework, namely, the CUDA libraries, cuDNN, any required Magnum IO components, TensorRT, and the framework.

Ensure that you have completed the following tasks in the NGC Private Registry User Guide:

Perform this task from the VM. Obtain the Docker pull command to download each of the following applications and deep learning framework components from the listing for the application or component in the NGC Public Catalog.

Applications
- NVIDIA Clara Parabricks
- NVIDIA DeepStream
- NVIDIA Riva
- MONAI - Medical Open Network for Artificial Intelligence
- RAPIDS
- RAPIDS Accelerator for Apache Spark
- TAO
Deep learning framework components
- NVIDIA TensorRT
- NVIDIA Triton Inference Server
- PyTorch
- TensorFlow 2

Running ResNet-50 with TensorRT#

Launch the NVIDIA TensorRT container image on all GPUs in interactive mode, specifying that the container will be deleted when stopped.
$ sudo docker run --gpus all -it --rm nvcr.io/nvidia/tensorrt:21.07-py3
From within the container runtime, change to the directory that contains test data for the ResNet-50 convolutional neural network.
# cd /workspace/tensorrt/data/resnet50

Run the ResNet-50 convolutional neural network with FP32, FP16, and INT8 precision and confirm that each test is completed with the result PASSED.

To run ResNet-50 with the default FP32 precision, run this command:
# trtexec --duration=90 --workspace=1024 --percentile=99 --avgRuns=100 \
--deploy=ResNet50_N2.prototxt --batch=1 --output=prob
To run ResNet-50 with FP16 precision, add the --fp16 option:
# trtexec --duration=90 --workspace=1024 --percentile=99 --avgRuns=100 \
--deploy=ResNet50_N2.prototxt --batch=1 --output=prob --fp16
To run ResNet-50 with INT8 precision, add the --int8 option:
# trtexec --duration=90 --workspace=1024 --percentile=99 --avgRuns=100 \
--deploy=ResNet50_N2.prototxt --batch=1 --output=prob --int8

Press Ctrl+P, Ctrl+Q to exit the container runtime and return to the Linux command shell.

Running ResNet-50 with TensorFlow#

Launch the TensorFlow 1 container image on all GPUs in interactive mode, specifying that the container will be deleted when stopped.
$ sudo docker run --gpus all -it --rm \ nvcr.io/nvidia/tensorflow:21.07-tf1-py3
From within the container runtime, change to the directory that contains test data for cnn example.
# cd /workspace/nvidia-examples/cnn

Run the ResNet-50 training test with FP16 precision.

# python resnet.py --layers 50 -b 64 -i 200 -u batch --precision fp16

Confirm that all operations on the application are performed correctly and that a set of results is reported when the test is completed.
Press Ctrl+P, Ctrl+Q to exit the container runtime and return to the Linux command shell.

Obtaining NVIDIA Base Command Manager Essentials#

NVIDIA Base Command Manager Essentials streamlines cluster provisioning, workload management, and infrastructure monitoring in the data center. In bare-metal deployments, NVIDIA Base Command Manager Essentials simplifies the installation of operating systems supported by NVIDIA Base Command Manager Essentials.

Before obtaining NVIDIA Base Command Manager Essentials, ensure that you have activated the accounts for getting NVIDIA AI Enterprise, as explained in Activating the Accounts for Getting NVIDIA AI Enterprise.

Request your NVIDIA Base Command Manager Essentials product keys by sending an email with your entitlement certificate to sw-bright-sales-ops@NVIDIA.onmicrosoft.com. After your entitlement certificate has been reviewed, you will receive a product key from which you can generate a license key for the number of licenses that you purchased.
Go to this page to download NVIDIA Base Command Manager Essentials for your operating system.

For detailed instructions on deploying and using Base Command Manager Essentials, refer to the Base Command Manager Essentials Product Manuals.

After obtaining NVIDIA Base Command Manager Essentials, follow the steps in the NVIDIA Base Command Manager Essentials Installation Manual to create and license your head node.

GPU Type	Value
NVIDIA vGPU	1: NVIDIA AI Enterprise automatically selects the correct type of license based on the vGPU type.
Physical GPU	The feature type of a GPU in pass-through mode or a bare-metal deployment: 0: NVIDIA Virtual Applications 2: NVIDIA RTX Virtual Workstation 4: NVIDIA Virtual Compute Server