AI Workbench Locations#


Diagram of the AI Workbench deployment options showing local installation of the Desktop App connected to remote deployments on a desktop, server or cloud instance.

Overview of Locations#

Work locally or remotely in the same UI/UX#

A ___location is a system with NVIDIA AI Workbench installed.

  • local: Your laptop with the Desktop App installed, often called local Workbench

  • remote: Remote system with the Workbench CLI installed, often called remote Workbench

Working in a ___location is straighforward#

  • Open the AI Workbench Desktop App and select the ___location where you want to work

  • When the ___location window opens, select a project to work on, or create/clone a new project

  • Start working!

Note

The ___location doesn’t need an NVIDIA GPU. You can work in a ___location that has a CPU only.

For example, your laptop can be a Mac.

Local and Remote#

One UI/UX for all your locations#

Local Workbench: The Desktop App installed on your laptop is the UI for all your locations. - Local Workbench is the Desktop App installed on your laptop - Your laptop can be CPU only, or can also have a GPU - It’s the primary ___location that provides the user-interface - You can develop and work entirely locally, even if the laptop is CPU-only

Remote Workbench: CLI installed on a remote system

  • The remote can be a desktop, server or VM. Main point is that it’s accessed via SSH

  • It’s accessed and managed from your local Workbench via SSH

  • Remotes provide more compute power, e.g. GPU, for workloads your laptop can’t handle

Note

You can have multiple remote locations but you should only have one local Workbench.

Transferring Projects#

Move projects between locations by syncing them through platforms like GitHub and GitLab.

  • Git in AI Workbench: Follows the typical collaboration and “right-sizing” workflow experienced developers, data scientists, and engineers use.

  • Workbench is explicitly designed to streamline this workflow, including handling of:

    • Runtime changes that need to be made, e.g. adjusting source directories for mounts

    • GPU-specific configuration, e.g. CUDA_VISIBLE_DEVICES

    • Underlying operating system differences, e.g. Windows vs Ubuntu vs MacOS

    • Architecture differences, e.g. x86 vs ARM

Managing Remote Locations#

Before you can work on a remote ___location, you must install AI Workbench on the system and then connect it to your local Workbench.

Setting Up a Remote Location#

There are two ways to setup a remote Workbench ___location:

  • Manually Connect: SSH into a remote system and run a command to install AI Workbench - then connect to your local Workbench using SSH information

  • Brev: Configure the Brev integration, create an instance on Brev, and click a button to connect to your local Workbench

Activating a Remote Location#

Once a remote ___location is added to your local Workbench, you just click on the ___location name to activate it and start working.

  • All connected locations are visible in the My Locations view

  • Activating a ___location may fail if the SSH connection has changed or the remote system is not running

Deleting a Remote Location#

Delete a remote ___location by clicking the option dots on the ___location entry.

  • Do this from Manage Locations (“My Locations”)

  • This does not delete the remote system or the projects on it

  • As long as the remote system is still running, you can re-add the remote ___location at any time

FAQs#

Can I use a remote Windows desktop as a remote ___location?#

Not directly. WSL made a recent change that supports this, but we’ve not yet implemented it by default.

You may be able to sort it out by yourself though.

Why do I need a remote ___location?#

Various reasons:

  • More compute power, i.e. GPUs

  • The data you want to use is on a remote system and is too large to transfer to your local system

  • You aren’t allowed to do work locally, i.e. your company’s IT policy

How does Workbench handle the connection to a remote ___location?#

When you connect a remote ___location to your local Workbench, the following is enabled:

  • AI Workbench establishes a secure SSH tunnel between your local machine and the remote AI Workbench service

    • Starting a remote Workbench session will automatically start the SSH tunnel

    • Stopping a remote Workbench session will automatically stop the SSH tunnel

  • Opening a project and starting an application in the project will automatically start another SSH tunnel

    • A proxy service is used to properly route the connection to the application

For more details, see Manually Connect.

What happens to the projects on a remote ___location when I delete the ___location?#

Nothing. Removing the ___location just removes the SSH connection. It doesn’t affect the actual remote system.

Can I connect to and manage remote locations with the CLI?#

Yes. You can connect to and manage remote locations with the CLI.

Consult the CLI help menu for more details: nvwb --help.