Ryzen™ AI Software

Introduction

AMD Ryzen™ AI Software includes the tools and runtime libraries for optimizing and deploying AI inference on your AMD Ryzen™ AI based PC. It enables developers to quickly build and run a variety of AI applications for Ryzen™ AI. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Ryzen™ AI.

This repository contains the demos, examples and tutorials, demonstrating usage and capabilities of the Ryzen™ AI Software. It is a subset of the Ryzen™ AI Software release.

Follow the instructions at Ryzen™ AI Software for installation.

Git LFS and Instructions to clone:

Due to the presence of large files in some examples/tutorials, Git Large File Storage (LFS) has been configured in this repository. Follow the instructions below to ensure Git LFS is properly set up:

• Install Git LFS by downloading it from the official website
• After installation, run the following command in your terminal to set up Git LFS on your machine:

  git lfs install

• Clone the repository (or a fork of it):

  git clone https://github.com/amd/RyzenAI-SW.git

  • Pull the actual LFS files:

    git lfs pull

To run the demos and examples in this repository, please follow the instructions of README.md in each directory.

Getting Started Tutorials

• A Getting Started Tutorial with a fine-tuned ResNet model
• Hello World Jupyter Notebook Tutorial
• Getting Started ResNet50 Tutorial on iGPU

LLM Flow

• LLMs on RyzenAI with Pytorch

Examples

• Run Vitis AI ONNX Quantizer example
• Real-time object detection with Yolov8
• Run multiple concurrent AI applications with ONNXRuntime
• Run Ryzen AI Library example
• Run ONNX end-to-end examples with custom pre/post-processing nodes running on IPU
• RAG LLM Sample

Demos

• Cloud-to-Client demo on Ryzen AI
• Multiple model concurrency demo on Ryzen AI
• NPU-GPU Pipeline on RyzenAI

Other Tutorials

• End-to-end Object Detection
• Quantization for Ryzen AI

Benchmarking

• ONNX Benchmarking utilities

Reference

• Ryzen™ AI Developer Guide
• ONNXRuntime Vitis-AI EP
• AMD AI Developer Forum