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This guide walks you through installing GRID Enterprise on your own hardware.

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Requirements

Operating System

Ubuntu 22.04 or 24.04 (officially supported)

GPU

NVIDIA GPU with 8GB+ VRAM (16GB+ recommended), drivers 535+

Docker

Docker Engine with NVIDIA Container Toolkit

Python

Python 3.11 or higher

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Detailed Requirements

  • Operating System: Ubuntu 22.04 / 24.04. Other distributions may work but are not officially supported.
  • NVIDIA GPU + Drivers: Required for simulation and AI models. Minimum 8GB VRAM, ideally 16GB+. Install drivers version 535 or later.
  • Docker: Install Docker Engine to run GRID containers.
  • NVIDIA Container Runtime: Required for GPU-accelerated containers. Follow the NVIDIA Container Toolkit Installation Guide.
  • Python 3.11+: We recommend using Miniconda or a virtual environment manager.

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Installation

1

Create Python Environment

conda create -n grid python=3.11
conda activate grid
2

Install GRID Enterprise

pip install grid-enterprise
3

Configure GRID_DATA_DIR

Set the directory where GRID stores assets, credentials, and logs:
export GRID_DATA_DIR=$HOME/.grid
mkdir -p "$GRID_DATA_DIR"
Add the export line to your ~/.bashrc to persist across sessions.
4

Add License File

Place the license file from your onboarding package:
cp /path/to/license.json "$GRID_DATA_DIR/license.json"
The CLI reads registry credentials and other secrets from this file.
5

Configure Resources (Optional)

The CLI creates a default resource_config.json on first run. If you received a custom configuration:
cp /path/to/resource_config.json ~/.grid/resource_config.json
Default configuration:
{
  "serve": true,
  "servers": [
    {
      "id": "local",
      "ip": "127.0.0.1"
    }
  ]
}
Set "serve": true for host mode (runs containers locally) or "serve": false for client mode (orchestrates remote nodes only).

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Verify Installation

Launch the GRID CLI: 
grid

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General Robot Intelligence Development Platform - Enterprise version
General Robotics Technology, Inc.

Type help for list of commands.

GRID #

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Next Steps

Hello GRID Tutorial

Step-by-step guide to your first simulation session.

CLI Reference

Complete command reference for the GRID CLI.

Remote Nodes

Configure multi-machine deployments.

VS Code Integration

Develop inside GRID containers with VS Code.