Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (11.1%) to scientific vocabulary
Repository
iree-learning
Basic Info
- Host: GitHub
- Owner: LiqinWeng
- License: apache-2.0
- Language: C++
- Default Branch: main
- Size: 60.8 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
IREE: Intermediate Representation Execution Environment
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.
Project Status
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!
Communication Channels
- GitHub issues: Feature requests, bugs, and other work tracking
- IREE Discord server: Daily development discussions with the core team and collaborators
- iree-discuss email list: Announcements, general and low-priority discussion
Related Project Channels
- MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.
Architecture Overview
See our website for more information.
Presentations and Talks
- 2021-06-09: IREE Runtime Design Tech Talk (recording and slides)
- 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation (recording and slides)
- 2020-03-18: Interactive HAL IR Walkthrough (recording)
- 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation (recording and slides)
License
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.
Owner
- Name: LiqinWeng
- Login: LiqinWeng
- Kind: user
- Location: 杭州滨江
- Company: Stream Computing
- Repositories: 1
- Profile: https://github.com/LiqinWeng
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you want to cite IREE, feel free to use this"
title: "IREE"
abstract: >-
An MLIR-based compiler and runtime for ML models from multiple frameworks.
date-released: 2019-09-18
authors:
- name: "The IREE Authors"
contact:
- family-names: Vanik
given-names: Ben
email: benvanik@google.com
affiliation: Google
- family-names: Laurenzo
given-names: Stella
email: laurenzo@google.com
affiliation: Google
license: "Apache-2.0 WITH LLVM-exception"
url: "https://openxla.github.io/iree/"
repository-code: "https://github.com/openxla/iree"
keywords:
- compiler
- "machine learning"
- "deep learning"
- "artificial intelligence"