So, you are a new user wondering where to start. In general, there are two primary starting points. Most users will want to start by evaluating the toolchain and running a few examples. AMD recommends that all users start by downloading and running examples on a supported target platform, and then move on to installation and evaluation of the tools.
The two workflows are as follows:
In either case, we recommend that you review the entirety of the Vitis AI Github.IO documentation as a first step on your journey with Vitis AI. On these pages, you will find vital information that will augment the PDF User and Product Guides Vitis AI User Guides / DPU Product Guides.
In the early stages of evaluation, it is recommended that developers obtain and leverage a supported Vitis AI target platform. Several AMD evaluation platforms are directly supported with pre-built SD card images that enable the developer to evaluate the Vitis AI workflow. Because these images are ready-to-use, there is no immediate need for the developer to master the integration of the DPU IP. This path provides an excellent starting point for software or data science-centric developers.
If you are not familiar with AMD’s Adaptable SoC offerings, you may need better understand the features and performance of AMD Adaptable SoCs before selecting a platform. Users can review Versal™, Zynq™ Ultrascale+™ and Alveo datasheets and documentation, as well as the DPU product guides. Also important is to review the Vitis AI Model Zoo performance metrics which will allow you to contrast the relative performance of each target family. If required, users may also wish to consult with a local FAE or ML Specialist to determine the ideal target product family or device for a given application.
Supported Evaluation Targets¶
Vitis™ AI 3.0 supports the following targets for evaluation.
Versal AI Edge
Zynq Ultrascale+ Embedded
Alveo Data Center Acceleration Cards
Vitis AI support for the U200 16nm DDR, U250 16 nm DDR, U280 16 nm HBM, U55C 16 nm HBM, U50 16 nm HBM, and U50LV 16 nm HBM has been discontinued. Please leverage a previous release for these targets or contact your local sales team for additional guidance.
When you are ready to start with one of these pre-built platforms, you should refer to the Quickstart documentation for the respective target. The Quickstart instructions guide users to download a pre-built board image to launch deployment examples that leverage Vitis AI Model Zoo, Vitis AI Library, and Vitis AI Quantizer and Compiler. This is a crucial first step to becoming familiar with Vitis AI.
In addition, developers with access to suitable available hardware platforms can experience pre-built demonstrations available for download through the Vitis AI Developer page. Contact your local FAE to arrange a live demonstration.
Last but not least, embedded in the Vitis AI Github repo, there is a folder that in which we may publish demonstrations from time-to-time. You can access the demos here.