[HAL] Reject buffer view size overflows (#24992) Rejects dense buffer views when shape multiplication or packed byte-size calculation exceeds `iree_device_size_t`. Previously, overflowing dimensions could wrap to a small value and produce an undersized allocation request. The size calculation now uses checked multiplication and addition while preserving zero-dimension behavior and sub-byte element packing. Dense view creation also verifies that the logical byte length fits within the backing buffer, and reshape validates element counts before updating metadata. Tests cover: - Shape products that wrap to zero or one. - Packed-byte multiplication and addition overflow. - Maximum-size byte and sub-byte element counts. - Zero dimensions following otherwise overflowing dimensions. - Dense views larger than their backing buffers. - Overflowing reshape attempts. - Native and forced 32-bit `iree_device_size_t` configurations. Tested with: - `iree/hal/buffer_view_util_test` - `iree/hal/string_util_test` - `iree/tooling/buffer_view_matchers_test` - `iree/tooling/function_io_test` - `iree/tooling/numpy_io_test` - Repository pre-commit hooks for all changed files The original `iree-run-module` reproducer was not rerun because the validation build was configured as runtime-only without compiler tools. This addresses the concrete buffer-view overflow case tracked in #3844. The broader size-arithmetic audit remains open. AI agents assisted with understanding the codebase, writing tests, and reviewing the solution. --------- Signed-off-by: goutamadwant <workwithgoutam@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 |
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.