v1.0 - Initial release

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.​

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

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Utilizes:

• llvm-aie@b2a279c1 : wheel
• xdna-driver@deceb06

v0.9 - Incremental Alpha Release

Incremental alpha release of IRON and mlir-aie compiler!

Utilizes:

• llvm-aie@fd6a2c4 : wheel
• xdna-driver@deceb06

dev-wheels

enable aievec python bindings

mlir-distro

Add aietools container job (#807)

latest-wheels

Bump cmakeModules (#624)