Introducing Multi Node Launcher (R1setup) - GPU Deployment at Scale Made Simple
For Node Operators
Education
Deploying multi-machine GPU clusters can be complex and time-consuming. R1setup (Multi-Node Launcher) streamlines this process with an easy-to-use CLI. This free, open-source tool from Ratio1 automates the provisioning of GPU nodes (installing Docker, NVIDIA drivers, and more) using just SSH access and a few prompts. In the latest release, R1setup introduces powerful new features for node management and monitoring:
One-line installer: Quick setup of the R1setup CLI via a simple shell script.
Interactive configuration: Guided prompts define your cluster (node addresses, credentials, network).
Automated GPU setup: Installs Docker, NVIDIA drivers & CUDA, and GPU container tooling on each node.
Scalable deployment: Configure and deploy to dozens of nodes in one go.
Redesigned menu: A clear, categorized menu (Configuration, Deployment, Operations, Monitoring, Advanced) for intuitive navigation.
Individual node control: Start, stop, or restart each node’s service directly from the menu.
Advanced utilities: SSH into any node, stream or export logs, and export private keys for migrations.
Enhanced status reporting: Offline or unreachable nodes are flagged, and container health is clearly shown.
Automatic updates: R1setup now checks for and applies the latest version when you run it.
Graceful offline handling: Unreachable nodes are detected and skipped without blocking the process.
Below we walk through R1setup’s workflow and highlight these capabilities.
Step 1: Installing R1setup
Begin by installing R1setup on your control machine (e.g., your PC or a master server). The GitHub repo provides a one-line installer script. Run it locally (you do not need to execute it on each node):
Note: The Multi Node Launcher (R1setup) CLI can be run from Linux, macOS, or Windows Subsystem for Linux (WSL). Native Windows environments are not supported for running R1setup.
Important: Run this script from your configuration machine (your local computer). You do not need to run this script directly on your remote machines - the script will configure and deploy to your remote nodes for you.
This script sets up R1setup in a Python virtual environment and installs all prerequisites (Python, Ansible, etc.). When it finishes, you should see a message like “Installation complete!”, and the r1setup command will be available system-wide.
Step 2: Creating a Configuration
After installing, you're ready to launch the tool. Running r1setup for the first time will bring up an interactive prompt to create a new configuration. A configuration in R1setup is a file that stores your deployment settings: which nodes (machines) you want to set up, how to access them, and which network environment they will join.
When you execute r1setup, it detects that you have no configuration yet and asks to create one. Just follow the prompts:
Name your configuration: e.g.
gpu-cluster-prod.Choose a network: mainnet, testnet, or devnet (for Ratio1 nodes).
Specify number of GPU nodes: Enter how many servers you want to set up.
Enter node details: For each node, provide a friendly alias (name), IP address or hostname, SSH username, and authentication (password or key). You can also specify a sudo password if needed.
Creating a new configuration in R1setup is straightforward. In the screenshot above, we start a configuration named "my-super-configuration" and choose the mainnet network. We then configure 2 GPU nodes, providing its aliases ("mysmart-node" and "my-super-node"), IP addresses (192.168.0.110 and 192.168.0.110), SSH username, and password. R1setup summarizes the info for confirmation (host, user, auth method) and saves the configuration file. The configuration is now active and ready for deployment.
Notably, you can add as many nodes as you need in a single configuration. For instance, if you input "5" for the number of nodes, the tool will repeat the node detail prompts five times (one for each server). This makes it easy to set up a whole cluster in one go. (You can always manage configurations later to add or remove nodes, as we'll see.)
Step 3: Navigating the R1setup Main Menu
Once a configuration is created, R1setup drops you into its main menu interface. The updated main menu (shown below) displays the active configuration name, network, and a summary of node status. It is organized into sections like Configuration, Deployment, Operations, Monitoring & Info, and Advanced. In this example, the status line shows “Nodes (2): 1 unreachable, 1 running” (with a red X icon for the offline node). Under Operations, you’ll see new options to Start, Stop, or Restart each node’s service. The header also shows the last deployment time and performs an automatic update check when you launch the CLI.
R1setup’s updated main menu displays the configuration status and available actions. Here, one node is unreachable (red) and one is running (green). New menu sections (Operations and Advanced) give you quick access to start/stop nodes, SSH, and other utilities.
At this point, you can:
View configuration: Show details of all nodes (aliases, addresses, etc.) to double-check settings.
Test connectivity: Verify SSH access to each node (the tool will report any unreachable machines).
Add or edit nodes: Add new servers to the config or update existing entries without recreating the config.
Switch configurations: If you have multiple saved clusters (e.g. dev vs prod), switch between them easily.
For now, we’ll proceed with deploying the full software stack to the configured nodes.
Step 4: Deploying Docker, NVIDIA Drivers, and More (Full Deployment)
With your nodes configured, choose the Deploy full setup option. R1setup will install everything needed on each machine, including:
Docker Engine & Docker Compose: container runtime.
NVIDIA GPU drivers & CUDA: GPU acceleration support.
NVIDIA Container Toolkit: allow Docker to use GPUs.
Ratio1 Edge Node Service: the node software (for running on mainnet).
R1setup will first show you a summary of the planned actions and the target nodes. Review this and type y to proceed. The tool then connects to each node via Ansible and performs all the installation steps automatically. You will see status messages as packages install on each machine (the NVIDIA drivers can take several minutes).
Step 5: Deployment Complete - GPU Nodes Ready
When the deployment finishes, R1setup indicates success or failure for each node. A successful run shows all tasks completed (e.g. ok=<tasks> 0 failures) and a “Full Deployment completed successfully!” message with a green checkmark. The configuration is updated to record that a deployment has been run. Each remote machine now has Docker, NVIDIA software, and the edge-node container running.
You can extend your deployment at any time. For example, if you add more servers to the configuration and run Deploy full setup again, R1setup will automatically install the required software on just those new machines. This rinse-and-repeat process scales easily: whether you add one node or twenty, the tool handles them for you.
Step 6: Managing & Monitoring Deployed Nodes
After deployment, R1setup provides detailed status screens and controls for your nodes. For example, the Container Status view shows each node’s container state. In the example below, one node is marked Unreachable (red) and the other running (green). The list provides Start, Stop, and Restart buttons for each service, so you can control nodes on-demand without SSHing into them manually.
Container Status: Shows each node’s container state. In this example, one node is Unreachable (red) and the other is running (green). Buttons let you Start, Stop, or Restart each service.
Node Addresses: Displays each node’s blockchain address (skipping any offline hosts so they don’t cause errors).
Test Connectivity: Quickly re-checks SSH access to all nodes and reports how many are reachable.
In the Container Status screen above, “my-super-node” is unreachable (red) and “my-smart-node” is running (green). You can start or stop each node’s service right from this interface.
These monitoring tools help you spot offline nodes immediately and troubleshoot connectivity. They also mean you no longer need to juggle separate SSH sessions for basic node operations.
Step 7: Advanced Utilities (SSH, Logs, and Keys)
R1setup’s Advanced menu offers maintenance tools for expert users.
For example:
SSH into a node: Open an SSH session to any configured machine using the saved credentials.
Stream or export logs: Tail the node service’s logs in real time, or write them to a local file for analysis.
Import private keys: Collect each node’s wallet key file for safe backup or migration.
The new Advanced menu includes SSH and logging utilities (as well as security tools).
One particularly powerful feature is the Import Private Keys (expert mode) option. Selecting this will log into each node and copy the private key file that controls its blockchain wallet. As shown below, R1setup saves each key locally under node_keys/{node_name}_e2.pem. You can then transfer these keys to new hardware if you need to migrate a node - the node will keep its original wallet address.
The Import Private Keys process retrieves and saves the wallet key from each node. Each key is saved in node_keys/{alias}_e2.pem, allowing seamless node migration without changing addresses.
These advanced utilities give you full control. Need to debug a node? Just SSH in from the menu or fetch its logs. Want to safely move a node to another machine? Export its keys. The CLI keeps all these tasks in one place.
Why It Matters
Managing a GPU cluster or deploying blockchain-based AI nodes doesn't have to be a headache. R1setup simplifies the process to the point where anyone with basic SSH access can get a multi-node GPU environment up and running. This is especially useful for scalability - whether you're an individual setting up a few machines or an organization provisioning dozens of nodes, the same tool and process apply. No special DevOps knowledge is required; R1setup abstracts away the complexity of driver installations, Docker setup, and configuration management.
Another important aspect is that R1setup is free and open source. The project is available on GitHub, which means you can inspect the code, suggest improvements, or even tailor it to your own needs. Being open source also ensures transparency in what the tool is doing on your machines.
For the Ratio1 community, R1setup provides a fast path to becoming a node operator. If you want to join the Ratio1 network by running edge nodes, this launcher automates the entire bootstrap. And even beyond Ratio1, the ability to quickly equip servers with Docker and NVIDIA drivers has broad utility in AI and GPU computing projects.
Get Started Now: If you’re ready to try R1setup, head over to the r1setup repository for the latest instructions. The one-liner installation script in the mnl_factory directory makes setup a breeze. In just a few minutes, you can go from zero to a full GPU cluster - no more wrestling with individual server configs. Give R1setup a try and simplify your Edge Nodes deployments today!
Vitalii Toderian
May 21, 2025
