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Install AI Workbench on Ubuntu Server and Jetson#

Downloading or installing AI Workbench implies consent to the NVIDIA AI Product Agreement.

By downloading or installing the NVIDIA AI Workbench software, you agree to the terms of the NVIDIA AI Product Agreement (EULA). If you do not agree to the terms of the EULA, you are not authorized to download, install, or use NVIDIA AI Workbench.

Overview#

Remote install supports Ubuntu 22.04 and 24.04, as well as NVIDIA Jetson Linux.

Installation on Ubuntu is straightforward, but Jetson Linux requires a few more steps to address how SSH and Docker work.

You install AI Workbench on a remote by SSHing into the machine and running a shell command.

The Destkop App is not involved. You just SSH into the machine, copy a command from the user guide, and run the command. This starts a TUI and a dialog in the terminal.

Remote install offers the same choices as the full local install.

You need to pick Docker or Podman as the container runtime. In addition, if the machine has an NVIDIA GPU but no NVIDIA drivers, the installer will offer to install them for you.

Remote install has a non-interactive mode where you declare options in advance.

This feature is useful if you want to script the remote install.

Key Concepts#

TUI (text-based user interface)

An interactive, text based interface that runs in a terminal. Provides features like drop downs and selections through selector keys.

AI Workbench Application Folder

The destination folder on the remote machine for binaries and program files. The name is fixed as .nvwb, and the default location is in the home directory, ~/.nvwb.

Remote Ubuntu Install#

Prerequisites: Verify the following prior to installation.

  • A remote Ubuntu 24.04 or 22.04 system

  • SSH access as a non-root user with sudo privileges

  • 500 MB of disk space for the application

  • 40 GB of disk space for project containers

Step One: SSH into the remote machine as non-root user.
For password based access run:
ssh <non-root-username>@<remote-host>
For key based access run:
ssh -i <local-path-to-private-key> <non-root-username>@<remote-host>
Step Two: Copy and paste the installation command in the terminal.
mkdir -p $HOME/.nvwb/bin && \
curl -L https://workbench.download.nvidia.com/stable/workbench-cli/$(curl -L -s https://workbench.download.nvidia.com/stable/workbench-cli/LATEST)/nvwb-cli-$(uname)-$(uname -m) --output $HOME/.nvwb/bin/nvwb-cli && \
chmod +x $HOME/.nvwb/bin/nvwb-cli && \
sudo -E $HOME/.nvwb/bin/nvwb-cli install

to change the application folder path, replace $HOME with the desired path in the above commands.

Step Three: Follow the prompts in the TUI using the arrow keys and Enter to confirm choices.

  1. If prompted, select to install the NVIDIA GPU drivers (will require a reboot)

  2. Choose between Docker or Podman as the container runtime

Next Steps: Once AI Workbench is installed on the remote, add it to your Desktop App.

Follow the steps in the Remote Locations Guide.

Non-Interactive Install#

Prerequisites: Verify the following before the non-interactive install.

  • Same system requirements as the interactive install

  • Passwordless sudo configured on the remote machine

Step One: SSH into the remote as a non-root user and curl the AI Workbench CLI.
We skip explaining the SSH step here but the curl and mod command is below.
mkdir -p $HOME/.nvwb/bin && \
curl -L https://workbench.download.nvidia.com/stable/workbench-cli/$(curl -L -s https://workbench.download.nvidia.com/stable/workbench-cli/LATEST)/nvwb-cli-$(uname)-$(uname -m) --output $HOME/.nvwb/bin/nvwb-cli && \
chmod +x $HOME/.nvwb/bin/nvwb-cli
Step Two: Run the non-interactive installer with required flags.
See the command for an example configuration below.
sudo $HOME/.nvwb/bin/nvwb-cli install \
--noninteractive \
--accept \
--docker \
--drivers \
--uid 1000 \
--gid 1000

The arguments in this command assume that machine has an NVIDIA GPU with no drivers installed. It also selects Podman as the runtime.

The non-interactive install will automatically reboot the remote machine if you elect to have the drivers installed.

Next Steps: Once AI Workbench is installed on the remote, add it to your Desktop App.

Follow the steps in the Remote Locations Guide.

Jetson Install#

Prerequisites: Your Jetson system should satisfy the following.

  1. 500 MB of disk space for the application

  2. 40 GB of disk space for the containers

You will also need:

  1. Your username on the device: <jetson-user-name>

  2. Your password for that user on the device: <jetson-user-name-password>

Step One: Configure SSH access to the Jetson device.

  1. Open a terminal on the Jetson device

  2. Install openssh-server on the device

    sudo apt update && sudo apt install openssh-server

  3. Open ports 10000 and 10001 on the device

    sudo ufw enable && sudo ufw allow 10000 && sudo ufw allow 10001
Step Two: Find the Jetson device’s IP address.

  1. In the terminal on the device, run

    ifconfig

  2. In the output find the interface that includes the following.

    flags=4163<UP,BROADCAST,RUNNING,MULTICAST>

  3. Find the inet address, <jetson-ip>, for that interface and write it down.

Step Three: Test the SSH connection from your local machine.

  1. Verify you have password based SSH access to the Jetson device.

    ssh <jetson-user-name>@<jetson-ip>

  2. If you have a private/public SSH key pair, transfer the public key to the Jetson device.

    ssh-copy-id jetson-username@jetson-ip-address

  3. Otherwise, follow the instructions here here to create a key-pair. Then transfer the public key to the Jetson device.

  4. Test SSH access to the device using the private key from the pair.

    ssh -i <path-to-private-key> jetson-username@jetson-ip-address
Step Four: Install AI Workbench on the Jetson device.

  1. Paste and execute the following command in a terminal on the Jetson device.

    mkdir -p $HOME/.nvwb/bin && \
curl -L https://workbench.download.nvidia.com/stable/workbench-cli/$(curl -L -s https://workbench.download.nvidia.com/stable/workbench-cli/LATEST)/nvwb-cli-Linux-arm64 --output $HOME/.nvwb/bin/nvwb-cli && \
chmod +x $HOME/.nvwb/bin/nvwb-cli && \
sudo -E $HOME/.nvwb/bin/nvwb-cli install

  2. Follow the guidance in the TUI. Select Docker as the container runtime.

Step Five: Resolve Docker compatibility issues.

Jetson has a known compatibility issue with newer Docker versions. You can fix the issue with a configuration file.

  1. Create the configuration file

    sudo mkdir -p /etc/systemd/system/docker.service.d
sudo nano /etc/systemd/system/docker.service.d/jetson-docker.conf

  2. Add the following content to the file

    [Service]
Environment="DOCKER_INSECURE_NO_IPTABLES_RAW=1"

  3. Reload and restart Docker:

    sudo systemctl daemon-reload
sudo systemctl restart docker.service
Next Steps: Once AI Workbench is installed on the device, add it to your Desktop App.

Follow the steps in the Remote Locations Guide.