commit | 40c19e36b4fb32f0ae59589328cbe10a0056bad2 | [log] [tgz] |
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author | Rob Suderman <rob.suderman@gmail.com> | Mon Jan 13 08:57:33 2025 -0800 |
committer | GitHub <noreply@github.com> | Mon Jan 13 08:57:33 2025 -0800 |
tree | 99afc96db7ff1d94e3ee2423ed7a1509b66c1311 | |
parent | 88d5f59c764c096d46a5ca0eaa1729aa87e1bc4b [diff] |
Better support multidevice placement with `stream.async.barrier` (#19651) Barriers / transfers should have semantics that attempt to parallelize partitioning. If a value has a barrier placed it should divide partitions to avoid spaning behavior with cross device dependencies. Intermediate and ending transfers we want to place on the producing partition so that any produced operator ends by producing the value at the needed desetination For incoming transfers we place in the destination partition as these will not add a dependency on the incoming data.
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.
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GitHub release (nightly) | |
Python iree-base-compiler | |
Python iree-base-runtime |
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macOS | |
macOS | |
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See our website for more information.
Community meeting recordings: IREE YouTube channel
Date | Title | Recording | Slides |
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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.