Overview

Overview#

AUP Learning Cloud is a tailored JupyterHub deployment designed to provide an intuitive and hands-on AI learning experience. It features a comprehensive suite of AI toolkits running on AMD hardware acceleration, enabling users to learn and experiment with ease.

Software Architecture

What is AUP Learning Cloud?#

AUP Learning Cloud provides a multi-user Jupyter notebook environment optimized for AI and machine learning education on AMD hardware platforms.

Key Features#

Hardware Acceleration#

  • AMD GPU: Leverage ROCm for high-performance deep learning and AI workloads

  • AMD NPU: Utilize Ryzen™ AI for efficient neural processing unit tasks

  • AMD CPU: Support for general-purpose CPU-based computations

Flexible Deployment#

Kubernetes provides a robust infrastructure for deploying and managing JupyterHub. We support both single-node and multi-node K3s cluster deployments.

Custom URL Launcher#

We provide a basic ROCm + PyTorch environment; you can clone your own Git repository into this environment at server start (via URL and branch or by selecting a repo from your GitHub account). Your code is then available in the workspace so you can run it immediately.

Authentication#

Seamless integration with GitHub Single Sign-On (SSO) and Native Authenticator for secure and efficient user authentication:

  • Auto-admin on install: Initial admin created automatically with random password

  • Dual login: GitHub OAuth + Native accounts on single login page

  • Batch user management: CSV/Excel-based bulk operations via scripts

Storage Management and Security#

Dynamic NFS provisioning ensures scalable and persistent storage for user data, while end-to-end TLS encryption with automated certificate management guarantees secure and reliable communication.

Learning Solutions#

AUP Learning Cloud offers the following Learning Toolkits:

  • Computer Vision - 10 hands-on labs covering common computer vision concepts and techniques

  • Deep Learning - 12 hands-on labs covering common deep learning concepts and techniques

  • Large Language Model from Scratch - 9 hands-on labs designed to teach LLM development from scratch

  • Physics Simulation - Hands-on labs for physics simulation with GPU acceleration

Available Notebook Environments#

Environment

Image

Hardware

Base CPU

ghcr.io/amdresearch/auplc-default

CPU

Basic GPU

ghcr.io/amdresearch/auplc-gpu

GPU

CV Course

ghcr.io/amdresearch/auplc-cv

GPU

DL Course

ghcr.io/amdresearch/auplc-dl

GPU

LLM Course

ghcr.io/amdresearch/auplc-llm

GPU

PhySim Course

ghcr.io/amdresearch/auplc-physim

GPU
Contents