Quick Start

The simplest way to deploy AUP Learning Cloud on a single machine in a development or demo environment.

Prerequisites

  • Hardware: AMD Ryzen™ AI Halo Device (e.g., AI Max+ 395, AI Max 390)

  • Memory: 32GB+ RAM (64GB recommended)

  • Storage: 500GB+ SSD

  • OS: Ubuntu 24.04.3 LTS

  • Docker: Install Docker and configure for non-root access

Install Docker

# Install Docker
curl -fsSL https://get.docker.com | sh

# Add current user to docker group
sudo usermod -aG docker $USER

# Apply group changes without logout (or logout/login instead)
newgrp docker

# Install Build Tools
sudo apt install build-essential

See also

See Docker Post-installation Steps and Install Docker Engine on Ubuntu for details.

Installation

git clone https://github.com/AMDResearch/aup-learning-cloud.git
cd aup-learning-cloud/deploy/
sudo ./single-node.sh install

After installation completes, open http://localhost:30890 in your browser. No login credentials are required - you will be automatically logged in.

Script Commands

Command

Description

install

Full installation (K3s, tools, GPU plugin, images, JupyterHub)

uninstall

Complete removal of all components

upgrade-runtime

Upgrade JupyterHub deployment

build-images

Build and import container images

install-tools

Install Helm and K9s only

install-runtime

Deploy JupyterHub only

remove-runtime

Remove JupyterHub only

Examples

# Upgrade JupyterHub after configuration changes
sudo ./single-node.sh upgrade-runtime

# Rebuild images after modifying Dockerfiles
sudo ./single-node.sh build-images

Next Steps

After installation:

  1. Access JupyterHub at http://localhost:30890

  2. Review the JupyterHub Configuration guide

  3. Set up Authentication if needed

  4. Configure User Management for your environment

  5. Explore the available learning toolkits

Tip

For manual installation or more control, see the Single-Node Deployment guide.