commit | 0f8c811957a158dbcbc84b51fb4c18ec1e3e8a5f | [log] [tgz] |
---|---|---|
author | Han-Chung Wang <hanchung@google.com> | Fri Jul 02 04:13:56 2021 +0800 |
committer | GitHub <noreply@github.com> | Fri Jul 02 04:13:56 2021 +0800 |
tree | 21df5c72d1c861a46d061383cc5ee6cd90230306 | |
parent | 46a779c7ce8ce1e5e52c54b1c20b3296bd1c7ad6 [diff] | |
parent | 22c8c90dad2faf0996d61b9fd9a55a5c542e8f88 [diff] |
Merge google -> main (#6383) * 22c8c90da Merge pull request #6382 from hanhanW:main-to-google * ee0d592b8 Synchronize submodules with LLVM at llvm/llvm-project@5b8ddd2ccceb * e6eae9136 Integrate LLVM at llvm/llvm-project@5b8ddd2ccceb * 904076644 Integrate LLVM at llvm/llvm-project@a601b308d91e * bbb415fe5 Integrate LLVM at llvm/llvm-project@804dc3dcf27d
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.
IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.