[HAL/AMDGPU] Model target feature support Extend the generated AMDGPU target map so exact target rows also carry XNACK/SRAMECC feature-support bits. The target-ID parser now uses that shared table to normalize known unsupported features to UNSUPPORTED while preserving supported but unspecified modes as ANY, which keeps the ROCr wildcard-vs-explicit compatibility distinction intact without adding another hand-written target database. Record the physical-device HSA ISA identity as one nested isa field instead of a loose processor buffer plus duplicated gfx IP version. Queue/profile policy now consumes isa.target_id.version, and system info caches HSA_AMD_SYSTEM_INFO_XNACK_ENABLED as the process-wide KFD-bound XNACK mode. That gives later topology and executable-load code a named cold-path place to ask about agent identity instead of rediscovering feature state. Tighten multi-GPU ISA commonality diagnostics by comparing parsed target IDs and reporting processor, generic-version, SRAMECC, and XNACK mismatches by name. Mixed feature modes were previously only visible as raw string differences, which was technically useful but not the invariant we need for day-0 CDNA/RDNA support.
IREE (Intermediate Representation Execution Eenvironment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
Releases notes are published on GitHub releases.
| Package | Release status |
|---|---|
| GitHub release (stable) | |
| GitHub release (nightly) | |
iree-base-compiler | |
iree-base-runtime |
For more details on the release process, see https://iree.dev/developers/general/release-management/.
| Operating system | Build status |
|---|---|
| Linux | |
| macOS | |
| macOS |
For the full list of workflows see https://iree.dev/developers/general/github-actions/.
See our website for more information.
Community meeting recordings: IREE YouTube channel
| Date | Title | Recording | Slides |
|---|---|---|---|
| 2025-06-10 | Data-Tiling in IREE: Achieving High Performance Through Compiler Design (AsiaLLVM) | recording | slides |
| 2025-05-17 | Introduction to GPU architecture and IREE's GPU CodeGen Pipeline | recording | slides |
| 2025-02-12 | The Long Tail of AI: SPIR-V in IREE and MLIR (Vulkanised) | recording | slides |
| 2024-10-01 | Unveiling the Inner Workings of IREE: An MLIR-Based Compiler for Diverse Hardware | recording | |
| 2021-06-09 | IREE Runtime Design Tech Talk | recording | slides |
| 2020-08-20 | IREE CodeGen (MLIR Open Design Meeting) | recording | slides |
| 2020-03-18 | Interactive HAL IR Walkthrough | recording | |
| 2020-01-31 | End-to-end MLIR Workflow in IREE (MLIR Open Design Meeting) | recording | slides |
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.