Difference between revisions of "Edge AI SDK/AI Framework/AMD"

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= RyzenAI SDK =
 
= RyzenAI SDK =
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Introduction
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AMD Ryzen™ AI software includes the tools and runtime libraries for optimizing and deploying AI inference on AMD Ryzen AI powered PCs1. Ryzen AI software enables applications to run on the neural processing unit (NPU) built
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in the AMD XDNA™ architecture, the first dedicated AI processing silicon on a Windows x86 processor2, and supports an integrated GPU (iGPU).
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Overview
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Ryzen™ AI software enables developers to efficiently port their pre-trained PyTorch or TensorFlow models to run on the integrated GPU (iGPU) or Neural Processing Unit (NPU) available in select Ryzen AI-powered laptops. 
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Applications are deployed using ONNX Runtime, giving the user easy inferencing across the different hardware.
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Build AI Applications Easily
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Get started within minutes with a straightforward installation process, growing pre-trained model zoo, and optimized LLMs using ONNX runtime.
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Addressing Various AI Workloads 
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-Large Language Models
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-Image and Video Generation
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-Recommendation
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-Computer Vision
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= Application =
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= Benchmark =
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= System Monitoring =

Revision as of 03:51, 4 September 2025

RyzenAI SDK

Introduction 

AMD Ryzen™ AI software includes the tools and runtime libraries for optimizing and deploying AI inference on AMD Ryzen AI powered PCs1. Ryzen AI software enables applications to run on the neural processing unit (NPU) built 
in the AMD XDNA™ architecture, the first dedicated AI processing silicon on a Windows x86 processor2, and supports an integrated GPU (iGPU).

Overview 

Ryzen™ AI software enables developers to efficiently port their pre-trained PyTorch or TensorFlow models to run on the integrated GPU (iGPU) or Neural Processing Unit (NPU) available in select Ryzen AI-powered laptops.   
Applications are deployed using ONNX Runtime, giving the user easy inferencing across the different hardware.

Build AI Applications Easily 

Get started within minutes with a straightforward installation process, growing pre-trained model zoo, and optimized LLMs using ONNX runtime.

Addressing Various AI Workloads  

-Large Language Models 
-Image and Video Generation 
-Recommendation 
-Computer Vision



Application

Benchmark

System Monitoring

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