Trim README.md and link to our website more prominently. (#5803)
* Remove "Getting Started" section entirely, since the new website covers that from a few different angles
* Remove "Architecture and Goals" section entirely. The new homepage covers these at a high level. The "Demonstrate MLIR's ability" and "Embrace standard-based ML via Vulkan" paragraphs are nice, but they need a better home :)
* Remove "Roadmap and Milestones" section entirely. It has been moved to https://google.github.io/iree/#roadmap (which then links back to GitHub... open to better ideas there)
* Reorder "Presentations and Talks"
diff --git a/README.md b/README.md
index 38a6c30..555acd8 100644
--- a/README.md
+++ b/README.md
@@ -1,10 +1,14 @@
# IREE: Intermediate Representation Execution Environment
IREE (**I**ntermediate **R**epresentation **E**xecution **E**nvironment,
-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.
+pronounced as "eerie") is an [MLIR](https://mlir.llvm.org/)-based end-to-end
+compiler that lowers Machine Learning (ML) models to a unified IR optimized for
+real-time inference on mobile/edge devices against heterogeneous hardware
+accelerators. IREE also provides flexible deployment solutions for its compiled
+ML models.
+
+See [our website](https://google.github.io/iree/) for project details, user
+guides, and instructions on building from source.
#### Project Status
@@ -16,13 +20,12 @@
## Communication Channels
-* [GitHub Issues](https://github.com/google/iree/issues): Preferred for
- specific technical issues and coordination on upcoming features.
-* [Google IREE Discord Server](https://discord.gg/26P4xW4): The core team and
- collaborators coordinate daily development here; good for low-latency
- communication.
-* [Google Groups Email List](https://groups.google.com/forum/#!forum/iree-discuss):
- Good for general and low-priority discussion.
+* [GitHub issues](https://github.com/google/iree/issues): Feature requests,
+ bugs, and other work tracking
+* [IREE Discord server](https://discord.gg/26P4xW4): Daily development
+ discussions with the core team and collaborators
+* [iree-discuss email list](https://groups.google.com/forum/#!forum/iree-discuss):
+ Announcements, general and low-priority discussion
#### Related Project Channels
@@ -31,98 +34,6 @@
sometimes is referred to in certain MLIR discussions. Useful if you are also
interested in MLIR evolution.
-## Getting Started
-
-### Quick Start using Python
-
-Python packages are published on the
-[releases](https://github.com/google/iree/releases) page. See the
-[colab/](https://github.com/google/iree/tree/main/colab) directory for examples.
-
-### Building from Source
-
-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](https://google.github.io/iree/get-started)
-pages on IREE's [documentation hub](https://google.github.io/iree) to configure,
-compile, and run IREE in your favorite development environment!
-
-## Documentation and Talks
-
-IREE hosts all its documentation and project status dashboards on
-[GitHub Pages](https://google.github.io/iree). We are still building up the
-website; please feel free to
-[create issues](https://github.com/google/iree/issues) for the documentation
-you'd like to see!
-
-We also have some public talks that explain IREE's concepts and architecture:
-
-* 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation
- ([recording](https://drive.google.com/file/d/1325zKXnNIXGw3cdWrDWJ1-bp952wvC6W/view?usp=sharing)
- and
- [slides](https://docs.google.com/presentation/d/1NetHjKAOYg49KixY5tELqFp6Zr2v8_ujGzWZ_3xvqC8/edit))
-* 2020-03-18: Interactive HAL IR Walkthrough (Ben Vanik and core team)
- ([recording](https://drive.google.com/file/d/1_sWDgAPDfrGQZdxAapSA90AD1jVfhp-f/view?usp=sharing))
-* 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation
- ([recording](https://drive.google.com/open?id=1os9FaPodPI59uj7JJI3aXnTzkuttuVkR)
- and
- [slides](https://drive.google.com/open?id=1RCQ4ZPQFK9cVgu3IH1e5xbrBcqy7d_cEZ578j84OvYI))
-
-## Architecture and Goals
-
-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 (**H**ardware **A**bstraction **L**ayer) 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
-
-* Support advanced models on mobile/edge devices. Dynamic shapes, dynamic flow
- control, dynamic multi-model dispatch, streaming models, tree-based search
- algorithms, and other are all good examples of exciting ML evolution. We are
- trying to build IREE from the ground-up to enable these models and run them
- efficiently on modern hardware, especially on mobile/edge devices.
-* Demonstrate MLIR's ability to develop non-traditional ML compiler backends
- and runtimes. MLIR enables IREE's holistic approach of focusing on the math
- being performed and how that math is scheduled rather than graphs of "ops".
-* Embrace standard-based ML via Vulkan. The graphics world is shifting towards
- favoring modern explicit APIs for performance and predictability and Vulkan
- is emerging as the "compatibility" layer. We would love to allow hardware
- vendors to be able to make ML efficient on their hardware without the need
- for bespoke runtimes and special access. We also would love to let
- developers and users utilize all the hardware available on as many platforms
- as possible.
-
-## Roadmap and Milestones
-
-IREE is in the early stages of development and not yet ready for broad adoption.
-Check out the [long-term design roadmap](./docs/developers/design_roadmap.md) to
-get a sense of where we're headed.
-
-We plan on a quarterly basis using [OKRs](https://en.wikipedia.org/wiki/OKR).
-Review our latest [objectives](./docs/developers/objectives.md) to get a sense
-of what we're up to in the near term.
-
-We use [GitHub Projects](https://github.com/google/iree/projects) to track
-progress on IREE components and specific efforts. We use
-[GitHub Milestones](https://github.com/google/iree/milestones) to track the
-work associated with plans for each quarter.
-
## Build Status
CI System | Build System | Platform | Architecture | Component | Status
@@ -136,6 +47,19 @@
Kokoro | CMake | Android | arm64-v8a | Runtime (build only) | [](https://storage.googleapis.com/iree-oss-build-badges/cmake/android/arm64-v8a/main_result.html)
BuildKite | CMake | Android | arm64-v8a | Runtime | [](https://buildkite.com/iree/iree-android-arm64-v8a/builds?branch=main)
+## Presentations and Talks
+
+* 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation
+ ([recording](https://drive.google.com/file/d/1325zKXnNIXGw3cdWrDWJ1-bp952wvC6W/view?usp=sharing)
+ and
+ [slides](https://docs.google.com/presentation/d/1NetHjKAOYg49KixY5tELqFp6Zr2v8_ujGzWZ_3xvqC8/edit))
+* 2020-03-18: Interactive HAL IR Walkthrough
+ ([recording](https://drive.google.com/file/d/1_sWDgAPDfrGQZdxAapSA90AD1jVfhp-f/view?usp=sharing))
+* 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation
+ ([recording](https://drive.google.com/open?id=1os9FaPodPI59uj7JJI3aXnTzkuttuVkR)
+ and
+ [slides](https://drive.google.com/open?id=1RCQ4ZPQFK9cVgu3IH1e5xbrBcqy7d_cEZ578j84OvYI))
+
## License
IREE is licensed under the terms of the Apache license. See [LICENSE](LICENSE)
