BBuf/tvm_mlir_learn resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

2768 stars · 370 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated collection of learning notes, examples, and experiments for deep learning compilers, covering TVM, MLIR, LLVM, Relay, TorchScript, and compiler-guided kernel optimization. It serves as a public archive of scheduler examples, code generation demos, and paper reading notes for AI compiler systems.

Use cases

• learn how TVM scheduling and code generation work
• understand MLIR and LLVM compiler infrastructure
• study deep learning compiler papers like Ansor and PET
• optimize GEMM kernels using compiler techniques
• experiment with Relay IR and custom compiler passes
• get started with deep learning compiler internals

When to choose

• you want hands-on examples for TVM, MLIR, or Relay
• you are studying AI compiler systems and kernel optimization
• you need paper reading notes on ML systems compilers

When to avoid

• you need production-ready compiler tooling or maintained libraries
• you expect a structured course or up-to-date documentation
• you need a licensed, redistributable codebase

Facets

learning-resource · maturity maintenance

compiler interpreter developer-tools compilers machine-learning tutorials gpu-computing python tvm mlir llvm deep-learning-compiler code-generation kernel-optimization learning-notes linux docker

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