Vitis AI Develovement Options


Develop Using Vitis AI Locally 

Step 1: Download and install Vitis AI from Github
The Vitis™ AI software is made available via Docker Hub. Vitis AI consists of the following two packages:
Vitis AI Tools Docker | Vitis AI runtime package for edge

Step 2: Hardware platform setup
Embedded SoC: ZCU102/ZCU104 set up
Alveo: U200/U250 set up | U50/U280 set up

Step 3: Run Vitis AI examples
Embedded SoC: ZCU102/ZCU104   
Alveo: U200/U250 | U50/U280

Develop Using Vitis AI in the Cloud 

Develop accelerated applications with Vitis AI in the Cloud – No local software installations or upfront purchase of hardware platforms necessary (pay-as-you-go). Log in and get started right away.

Nimbix Cloud
Evaluate Vitis AI with Alveo accelerator cards on Nimbix. Quickly evaluate the performance benefits Xilinx platforms can bring to your applications, with no upfront purchase of cards or local software setup required.
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Tutorials


In Depth Tutorials
Vitis AI Introduction Tutorial for the ZCU104
This tutorial puts in practice the concepts of FPGA acceleration of Machine Learning and illustrates how to quickly get started deploying both pre-optimized and customized ML models on Xilinx devices

Vitis AI Custom Embedded Platform Creation
In this module, we will create a custom Vitis embedded platform for ZCU104. It will be capable to run Vitis acceleration applications including Vitis-AI applications. Of course, general embedded software application can also run on this platform.

Intelligent Video Analytics ZCU104 ML Acceleration

This repository contains a reference design for the use of the Xilinx IVAS framework in a multi-channel machine learning system.

Documentation


Get technical resources for developers  as well as code samples for Vitis AI
Vitis AI Product Documentation 

Articles


Curated articles form industry experts for all things Vitis AI
View all Vitis AI Articles >

Training

Take a Vitis AI Training Course (On-Demand, Virtual, or Classroom)


Free Vitis AI Training Courses

Access free Vitis AI training course when you sign up for the Developer Program Secure site. 

Courses include: 
Introduction to the Vitis AI Development Environment 
Frameworks Supported by the Vitis AI Development Environment 
Setting Up the Vitis AI Development Environment

Paid Courses

You can also visit our Xilinx Customer Training Center for additional Paid Courses

Videos


Watch various videos such as quick-take product introductions, tutorial walk-throughs and demos.  

Vitis AI Videos

What's New in Vitis AI 1.3
Vitis AI 1.3 supports Pytorch and Tensorflow2 frameworks, unifies XIR-based compilation flow from cloud to edge, and includes additional ready-to-use AI models for a wider range of applications.

Vitis AI on Custom Platform
Focus on how to enable Vitis AI on a custom embedded platform by introducing the requirement and steps to build hardware components, customize software components and create Vitis and Vitis AI-ready platform.

Vitis AI End-to-End Workflow
Start with a brief introduction of Vitis AI, then walk through the end-to-end utilization of Vitis AI 1.3 tools.

DPU Integration Vitis Flow with Command-Line
Focus on how to integrate DPU as a HLS kernel with Vitis 2020.2 and Vitis AI 1.3 in command-line mode.

Explore all Vitis AI Videos >

Webinars


On-Demand Vitis AI Webinars

Adaptable AI Inference with Vitis AI 
In this webinar, go in-depth with the key components of Vitis AI and learn how to achieve adaptable and efficient AI inference on Xilinx hardware platforms.

Vitis AI Deep Dive
In this Webinar, learn to use Vitis AI to deploy and run your pre-trained DNN models to Xilinx’s embedded SoC and Alveo acceleration platforms. Then get started with using Vitis AI to run examples on the board.

Accelerating AI Camera Development with Xilinx Vitis
Learn how to leverage Xilinx MPSoCs with Vitis in order to implement AI Camera designs 

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Projects


Overview

Learn how developers are using Xilinx technologies to accelerate their work. Learn from the tutorials, articles, and projects from the community.

Share your work (Github repo, Hackster.io link etc) with us at developer@xilinx.com and every month we will select projects to be featured on our developer site. Projects with be based on design features, performance, creativity, and originality.

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