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v1.0 - Initial release

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@jgmelber jgmelber released this 22 Apr 17:57
· 94 commits to main since this release
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Initial release of IRON and mlir-aie compiler

This project is primarily intended to support the open-source community with low-level access to AIE devices. We provide a Python-based programming flow: IRON supporting close-to-metal programming of AMD NPUs. This repository contains a programming guide and examples, however this project is not intended to represent an end-to-end compilation flow for all application designs. If you're looking for an out-of-the-box experience for highly efficient machine learning inference, check out AMD Ryzen™ AI Software.

🔧 Compiler and Toolchain Enhancements

  • IRON Python API: Introduced a logical IRON API with support for deferred tile placement and data tiling helpers (Tensor Access Pattern Library).
  • Just-In-Time (JIT) compilation: Added JIT compilation capabilities, enabling cleaner programming examples and simplified host code integration.
  • Support for all current Ryzen™ AI NPUs: Phoenix, Hawk, Strix, Krackan Point.

📚 Documentation and Community Engagement

  • Updated programming guides: The documentation has been updated to provide clearer documentation of IRON APIs including the logical deferred placement APIs.
  • New mini tutorial: The programming guide now includes a mini tutorial to efficiently introduce IRON concepts with hands on exercises.
  • Updated installation guides: The documentation has been updated to provide clearer instructions for installing the xdna-driver and setting up the development environment on various platforms.​

For a detailed view of all recent changes, you can explore the mlir-aie GitHub repository.


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