[LLVMCPU] Fix scalable vectorization fallback on SME-only (no `+sve`) targets (#24693) **Stacked** on #24656. Follow-up to #24661 / #24660. This PR aims to removes the TODO introduced in #24656. #24661 fixed the ArmSME lowering pipeline to not require classic `+sve` when SME tiling is used. This PR fixes the same underlying problem for the *fallback* path, which is what's used when the matmul falls back to it (e.g., `--iree-llvmcpu-disable-arm-sme-tiling`, or op types SME doesn't support): compiling a scalable-vectorized matmul on a `+sme`-only target with SME tiling disabled crashed LLVM instruction selection with `Cannot select: vscale`. The fix is scoped to a single function: `getMatmulVectorSizesUsingFillRegisterFileHeuristic` only checked `hasAnySVEFeature`, so on a `+sme`-only target it always fell back to non-scalable NEON tiles. It now also picks scalable tiles when `+sme` is present *and* the user has explicitly passed `--iree-llvmcpu-force-arm-streaming`. Net effect: 1. Non-matmul ops: always Peeling. 4. `linalg.matmul`, `+sme-only`, `disable-arm-sme-tiling=true`, and `force-arm-streaming=true`: still reaches SSVE (that's the actual fix), but now goes through `Peeling + masked tail` instead of masking-only (as in #24661). Unrelated to #24689 --------- Signed-off-by: Federico Bruzzone <federico.bruzzone.i@gmail.com>
IREE (Intermediate Representation Execution Environment, 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.