[HAL/AMDGPU] Add queue-range counter profiling Add a separate counter-ranges profiling data family and CLI mode for low-disturbance AMDGPU PMC capture. The existing counters mode remains dispatch-scoped and continues to require retained command-buffer metadata, while counter-ranges avoids dispatch metadata, dispatch event storage, and command-buffer profiling sidecars. AMDGPU counter sessions now distinguish dispatch samples from queue-carried physical-device ranges. Dispatch sample resources are still enabled on every host queue when requested. Range resources are materialized only on the first host queue for each physical device so device-global PMCs are not started and stopped by overlapping queues. Each range queue owns two pre-created banks, stops the active bank on flush/end, optionally restarts the alternate bank in the same queue-ordered reservation, and writes device-time-range counter samples after the cold flush wait completes. Range-only profiles now emit begin/end clock correlations so one-shot captures have a real device-clock fit. The Perfetto renderer projects device_time_range counter samples onto separate range-counter tracks, keeping them distinct from dispatch-scoped attribution counters.
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.