- IREE / Google: Intermediate Representation Execution Environment. An MLIR-based end-to-end compiler and runtime.
- MLIR / LLVM: Multi-Level IR Compiler Framework. A novel approach to building reusable and extensible compiler infrastructure.
- TC / Facebook: Tensor Comprehensions. A fully-functional C++ library to automatically synthesize high-performance machine learning kernels.
- Tiramisu / MIT: Tiramisu. A polyhedral compiler for expressing image processing, DNN, and linear/tensor algebra applications.
- TVM / Apache: Tensor Virtual Machine. An End to End Machine Learning Compiler Framework for CPUs, GPUs and accelerators.
- XLA / Google: Accelerated Linear Algebra. A domain-specific compiler for linear algebra that can accelerate TensorFlow models with potentially no source code changes.
- OpenXLA / Google: XLA (Accelerated Linear Algebra) is an open-source machine learning (ML) compiler for GPUs, CPUs, and ML accelerators.
- Halide: a language for fast, portable computation on images and tensors
- merrymercy/awesome-tensor-compilers
- zwang4/awesome-machine-learning-in-compilers
- BirenResearch/AIChip_Paper_List
- 2020 / MLIR: A Compiler Infrastructure for the End of Moore's Law
- 2020 / The Deep Learning Compiler: A Comprehensive Survey
- 2019 / An In-depth Comparison of Compilers for DeepNeural Networks on Hardware
- 2018 / TVM: An Automated End-to-End Optimizing Compiler for Deep Learning
- 2022-02 / 深度学习编译器整理 / 王钧
- 2021-09 / AI与传统编译器 / 吴建明
- 2021-08 / AI框架中图层IR的分析 / 金雪峰
- 2021-07 / tvm or mlir ？ / dxq
- 2021-04 / 深度学习编译技术的一些思考（五） / 蓝色
- 2019-05 / 深度学习编译技术的现状和未来 / 陈天奇
- 2015-07 / 计算机组成与设计 - 硬件/软件接口（第5版）
- 2015-05 / 并行算法设计与性能优化
- 2014-03 / 算法心得：高效算法的奥秘（第2版）
- 2012-12 / 编译器设计（第2版）
- 2012-01 / 计算机体系结构 - 量化研究方法（第5版） / 视频
- 2011-03 / flex与bison（中文版） / 阅读
- 2008-12 / 编译原理 - 原理、技术与工具
- 2005-01 / 高级编译器与实现