| commit | f5b323e862cd689ff54aa6084e91d34d8387226d | [log] [tgz] |
|---|---|---|
| author | Geoffrey Martin-Noble <gcmn@google.com> | Tue Jan 12 18:32:08 2021 -0800 |
| committer | GitHub <noreply@github.com> | Tue Jan 12 18:32:08 2021 -0800 |
| tree | 50065a56ae0d1540c8e200991e5fe67d00dd26bf | |
| parent | 54680f1921fbe520ed79a80e46ca0dedda74fb90 [diff] |
Remove TF dependency from IREE core (#4450) This completely strips TensorFlow as a dependency of the core part of IREE (basically everything other than `integrations/`). TF integrations are in a separate workspace under `integrations/tensorflow`. We still depend on mlir-hlo, which is exported as part of the TF repo, but also available as the https://github.com/tensorflow/mlir-hlo repository, which we use here as a submodule. To avoid ODR issues, when built with integrations TensorFlow we define `@mlir-hlo` to contain aliases for the rules present in TF. Fixes https://github.com/google/iree/issues/4480 Fixes https://github.com/google/iree/issues/3312 Most of https://github.com/google/iree/issues/3311 (leaving open for cleanup work)
IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler that lowers ML models to a unified IR optimized for real-time mobile/edge inference against heterogeneous hardware accelerators. IREE also provides flexible deployment solutions for the compiled ML models.
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!
Python packages are published on the releases page. See the colab/ directory for examples.
IREE can be built from source using both Bazel and CMake on Windows and Linux. We also have experimental macOS support.
Please see the Getting Started pages on IREE's documentation hub to configure, compile, and run IREE in your favorite development environment!
IREE hosts all its documentation and project status dashboards on GitHub Pages. We are still building up the website; please feel free to create issues for the documentation you'd like to see!
We also have some public talks that explain IREE's concepts and architecture:
IREE adopts a holistic approach towards ML model compilation: the IR produced contains both the scheduling logic, required to communicate data dependencies to low-level parallel pipelined hardware/API like Vulkan, and the execution logic, encoding dense computation on the hardware in the form of hardware/API-specific binaries like SPIR-V.
The architecture of IREE is best illustrated by the following picture:
Being compilation-based means IREE does not have a traditional runtime that dispatches “ops” to their fat kernel implementations. What IREE provides is a toolbox for different deployment scenarios. It scales from running generated code on a particular API (such as emitting C code calling external DSP kernels), to a HAL (Hardware Abstraction Layer) that allows the same generated code to target multiple APIs (like Vulkan and Direct3D 12), to a full VM allowing runtime model loading for flexible deployment options and heterogeneous execution.
IREE aims to
IREE is in the early stages of development and not yet ready for broad adoption. Check out the long-term design roadmap to get a sense of where we're headed.
We plan on a quarterly basis using OKRs. Review our latest objectives to get a sense of what we're up to in the near term.
We use GitHub Projects to track progress on IREE components and specific efforts. We use GitHub Milestones to track the work associated with plans for each quarter.
| CI System | Build System | Platform | Architecture | Component | Status |
|---|---|---|---|---|---|
| Kokoro | Bazel | Linux | x86 | Core |  |
| Kokoro | CMake & Bazel | Linux | x86-swiftshader | Integrations |  |
| Kokoro | CMake & Bazel | Linux | x86-turing | Integrations |  |
| Kokoro | CMake | Linux | x86-swiftshader | Core + Bindings |  |
| Kokoro | CMake | Linux | x86-turing | Core + Bindings |  |
| Kokoro | CMake | Android | arm64-v8a | Runtime (build only) |  |
| BuildKite | CMake | Android | arm64-v8a | Runtime |  |
IREE is licensed under the terms of the Apache license. See LICENSE for more information.