• Dive into Deep Learning Compiler
• Machine Learning Compilation
• Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale Production
• https://github.com/shrutisaxena51/Artificial-Intelligence-in-Compiler-Optimization
• https://github.com/BBuf/tvm_mlir_learn

Polyhedral Compilation

• Polyhedral Compilation及ISL学习资料

• 编译器领域的多面体模型（Polyhderal Model）

• MindSpore 图算融合加速引擎介绍

• [特性分析] 【转载】MindSpore大V博文之架构系列（七）--为什么MindSpore这样设计图算融合架构

• Polyhedral Model—AI芯片软硬件优化利器（一）

• 多面体模型在深度学习编译器的应用

• https://www.cse.iitk.ac.in/users/swarnendu/courses/autumn2020-cs610/intro-to-polyhedral-model.pdf

• Effectively Scheduling Computational Graphs of Deep Neural Networks toward Their Domain-Specific Accelerators

• https://web.cs.ucla.edu/~pouchet/index.html#lectures

• 《多面体编译理论》找茬计划（持续更新中。。。）

• MLIR中的多面体编译之我见

• https://zhuanlan.zhihu.com/p/704317757

• 假如加速卡上能跑python，能解决pytorch动态图转静态图的问题吗？

• 复杂性的那些事

Polyhedral compiler

• https://github.com/Meinersbur/ppcg

TVM

• https://tvm.apache.org/docs/
• https://tvm.hyper.ai/docs/
• https://xinetzone.github.io/tvm-book/index.html

tir transform

• TVM 源码阅读PASS — VectorizeLoop

Relax / Unity

• Relax: Co-Designing High-Level Abstraction Towards TVM Unity

• Relax: TVM 的下一代图层级 IR

• 冯思远：Apache TVM 与机器学习编译发展

• BYOC：加速器硬件接入深度学习编译器的统一框架

FFI

• https://github.com/apache/tvm-ffi

TensorFlow XLA

• 聊一聊TensorFlow编译优化技术XLA的实现
• Tensorflow 编译加速器 XLA 源码深入解读

JAX

• Advanced JAX: Performance, Optimization, and Scale

MLIR

https://mlir.llvm.org/

• Hands-On Practical MLIR Tutorial

• MLIR原理与应用技术杂谈

• 编译器与中间表示: LLVM IR, SPIR-V, 以及 MLIR

• 机器学习编译器代码生成相关 MLIR Dialect

• MLIR — Using Tablegen for Passes

MPK (Mirage Persistent Kernel): Compiling LLMs into a MegaKernel

• https://github.com/mirage-project/mirage/tree/mpk

Hidet

• Introducing Hidet: A Deep Learning Compiler for Efficient Model Serving