[GPUHeuristics] Refactor MMA heuristic seeds to be architecture-specific (#23717) Each GPU architecture now defines a constexpr ArchSeedSet containing gemm, scaled gemm, and convolution seed arrays indexed by GemmSize. The architecture is determined from the target and the corresponding seed set is returned (e.g. RDNA4 uses tuned seeds from RX 9070 XT benchmarking, others use the default). GemmSize enum values are changed to start at 0 for direct array indexing. Add RDNA4 (gfx1201) config tests covering small, medium, and large matmul and convolution shapes. RDNA4 benchmark results (RX 9070 XT, vs default seeds): - GEMM shapes: ~40% of shapes improved, 15.9% geometric mean speedup. - Prod Conv shapes: ~25% of shapes improved, 6% geometric mean speedup. - Proxy Conv shapes: ~30% of shapes improved, 14.5% geometric mean speedup. --------- Signed-off-by: yzhang93 <zhyuhang88@gmail.com> Co-authored-by: Claude <noreply@anthropic.com>
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.