# caomaolufei/AIInfraGuide

AI Infra 全栈从0入门学习资料：https://caomaolufei.github.io/AIInfraGuide/

Repository: https://github.com/caomaolufei/AIInfraGuide
Canonical: https://ross.abutalabs.com/products/aiinfraguide
Language: Astro
License Family: other
Last push: 2026-08-20T11:51:10+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 35, longevity 10
- inputs: {"age_days": 141, "days_push": 13, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1806, forks 140 (observed 2026-08-28T04:05:39.109491+00:00)

## What it is
An open-source Chinese-language knowledge base and learning guide covering the full AI infrastructure stack, from GPU hardware and CUDA programming to distributed training and LLM inference optimization. It is published as an Astro-based documentation site and includes an interview question bank with 180+ real interview questions from 60+ companies.

## Use cases
- learn AI infrastructure from scratch
- learn CUDA programming and kernel optimization
- understand distributed training like DDP, FSDP, and 3D parallelism
- study LLM inference optimization techniques like quantization and speculative decoding
- prepare for AI infra engineer interviews
- find a structured learning roadmap for GPU and training systems
- learn performance profiling with Nsight tools

## When to choose
- you want a systematic, Chinese-language curriculum for AI infrastructure engineering
- you are preparing for AI infra or GPU kernel engineering interviews
- you need a guided path from prerequisites through CUDA, distributed training, and inference optimization

## When to avoid
- you need official API documentation for a specific framework like vLLM or PyTorch
- you prefer English-language or video-based learning materials
- you need a hands-on tool or library rather than a study guide

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools, gpu-computing, llm-training, llm-inference
- domain: tutorials, gpu-computing, large-language-models, deep-learning, developer-tools
- platform: cross-platform
- tags: ai-infrastructure, cuda-programming, distributed-training, inference-optimization, interview-preparation, chinese-language, astro-site, web-server

## Member repositories
- caomaolufei/AIInfraGuide (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.109491+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:21:29.129680+00:00, confidence not recorded.
  - readme: https://github.com/caomaolufei/AIInfraGuide (fetched 2026-08-28T04:05:39.109491+00:00, sha 65043eab0192)
- Data as of 2026-08-30T08:39:29.467469+00:00.