openmlsys/openmlsys resource

Health v2 · maintenance only

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Adoption not part of the score

4845 stars · 478 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

An open-source bilingual (Chinese/English) textbook, 'Machine Learning Systems: Design and Implementation', covering the full ML systems stack from programming interfaces and computational graphs to AI compilers, distributed training, and GPU cluster management. The source is written in TeX/Markdown and built into an online book with mdBook.

Use cases

• learn how machine learning systems are designed and implemented
• understand AI compiler internals and IR design
• study distributed training and parallelism strategies
• learn GPU programming with CUDA, Triton, and CUTLASS
• understand model serving and inference optimization
• learn how large-scale GPU clusters are scheduled and managed
• prepare for ML infrastructure engineering roles

When to choose

• you want a free, comprehensive, open-source introduction to ML systems design
• you are a student, researcher, or engineer building or customizing ML infrastructure
• you need to understand the full stack from tensors and autodiff to compilers and cluster management

When to avoid

• you need hands-on code for a specific framework rather than conceptual system design
• you want an introductory machine learning algorithms course rather than systems content
• you need a formally licensed, citable publication (the repo has no license file)

Facets

learning-resource · maturity active

machine-learning compiler gpu-computing documentation developer-tools machine-learning deep-learning gpu-computing microservices tutorials education cross-platform open-source-textbook ml-systems ai-compilers distributed-training mdbook tex web

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