{"id":47087243,"url":"https://github.com/openmlsys/openmlsys","last_synced_at":"2026-03-12T12:01:16.319Z","repository":{"id":36950368,"uuid":"449205872","full_name":"openmlsys/openmlsys","owner":"openmlsys","description":"《Machine Learning Systems: Design and 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returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computer-systems","machine-learning","software-architecture","textbook"],"created_at":"2026-03-12T08:00:30.099Z","updated_at":"2026-03-12T12:01:16.301Z","avatar_url":"https://github.com/openmlsys.png","language":"TeX","funding_links":[],"categories":["TeX","📚 Project Purpose"],"sub_categories":["Machine Learning (Intermediate-Level"],"readme":"\u003cp align=\"center\"\u003e\n  \u003cimg src=\"static/logo-with-text.png\" alt=\"OpenMLSys Logo\" width=\"400\"/\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/openmlsys/openmlsys-zh/actions/workflows/main.yml\"\u003e\n    \u003cimg src=\"https://github.com/openmlsys/openmlsys-zh/actions/workflows/main.yml/badge.svg\" alt=\"CI\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://openmlsys.github.io/\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/book-online-blue\" alt=\"Book Online\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://github.com/openmlsys/openmlsys-zh/blob/main/LICENSE\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/license/openmlsys/openmlsys-zh\" alt=\"License\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://github.com/openmlsys/openmlsys-zh/stargazers\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/stars/openmlsys/openmlsys-zh?style=social\" alt=\"GitHub Stars\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e中文\u003c/b\u003e | \u003ca href=\"README_EN.md\"\u003eEnglish\u003c/a\u003e\n\u003c/p\u003e\n\n---\n\n# 机器学习系统：设计和实现\n\n本开源项目讲解现代机器学习系统的设计原理和实现经验，涵盖从编程接口、计算图、编译器到分布式训练的完整技术栈。\n\n**在线阅读：** [openmlsys.github.io](https://openmlsys.github.io/)\n\n## 目录\n\n- [适用读者](#适用读者)\n- [内容介绍](#内容介绍)\n- [构建指南](#构建指南)\n- [贡献指南](#贡献指南)\n- [社区](#社区)\n- [许可证](#许可证)\n\n## 适用读者\n\n- **学生**：掌握机器学习基础理论后，希望深入了解现代机器学习系统设计与实现的同学。\n- **科研人员**：需要开发自定义算子（Custom Operators）或利用分布式执行实现大模型的研究者。\n- **开发人员**：负责机器学习基础设施建设，需要对系统性能调优和深度定制的工程师。\n\n## 内容介绍\n\n本书分为基础篇、进阶篇和扩展篇三个部分：\n\n### 基础篇\n\n| 章节 | 内容 |\n|------|------|\n| [编程接口](chapter_programming_interface/) | 框架接口设计哲学、机器学习工作流、深度学习模型定义、C/C++ 框架开发 |\n| [计算图](chapter_computational_graph/) | 计算图基本构成、生成方法、调度策略、自动微分 |\n\n### 进阶篇\n\n| 章节 | 内容 |\n|------|------|\n| [编译器前端和中间表示](chapter_frontend_and_ir/) | 类型推导、中间表示（IR）、自动微分、常见优化 Pass |\n| [编译器后端和运行时](chapter_backend_and_runtime/) | 计算图优化、算子选择、内存分配、计算调度与执行 |\n| [硬件加速器](chapter_accelerator/) | GPU/Ascend 架构原理、高性能编程接口（CUDA/CANN） |\n| [数据处理框架](chapter_data_processing/) | 易用性、高效性、保序性、分布式数据处理 |\n| [模型部署](chapter_model_deployment/) | 模型转换、模型压缩、模型推理、安全保护 |\n| [分布式训练](chapter_distributed_training/) | 数据并行、模型并行、流水线并行、集合通讯、参数服务器 |\n\n### 扩展篇\n\n| 章节 | 内容 |\n|------|------|\n| [深度学习推荐系统](chapter_recommender_system/) | 推荐系统原理、大规模工业场景架构设计 |\n| [联邦学习系统](chapter_federated_learning/) | 联邦学习方法、隐私保护、系统实现 |\n| [强化学习系统](chapter_reinforcement_learning/) | 单智能体/多智能体强化学习系统 |\n| [可解释性 AI 系统](chapter_explainable_AI/) | 可解释 AI 方法与落地实践 |\n| [机器人学习系统](chapter_rl_sys/) | 机器人感知、规划、控制与系统安全 |\n\n## 更新日志\n\n| 日期 | 事件 |\n|------|------|\n| 2022-01 | 项目初始化，开始中文内容编写 |\n| 2022-05 | 完成扩展篇各章节（联邦学习、强化学习、可解释 AI） |\n| 2023-05 | 适配 MindSpore 2.0 |\n| 2026-03 | 中英文双语构建架构重构；启动英文版 |\n\n## 构建指南\n\n### 环境依赖\n\n- curl\n- git\n\n### 安装步骤\n\n```bash\n# 克隆仓库\ngit clone https://github.com/openmlsys/openmlsys-zh.git\ncd openmlsys-zh\n\n# 安装rust toolchain \ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n\n# 安装mdbook\ncargo install mdbook\n```\n\n### 编译HTML\n\n```bash\nsh build_mdbook_zh.sh\n# 生成结果位于 .mdbook-zh/book\n```\n\n更多细节请参考 [构建指南](info/info.md)。\n\n## 贡献指南\n\n我们欢迎任何形式的贡献，包括：\n\n- **勘误**：发现文字或图片错误，请创建 Issue 并 @ [章节编辑](info/editors.md)，或直接提交 PR。\n- **内容更新**：提交 PR 更新或添加 Markdown 文件。\n- **新章节**：欢迎社区对元学习系统、自动并行、集群调度、绿色 AI、图学习等主题贡献章节。\n\n提交前请阅读：\n- [写作风格指南](info/style.md)\n- [中英文术语对照](info/terminology.md)\n\n## 社区\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"info/mlsys_group.png\" alt=\"微信群二维码\" width=\"200\"/\u003e\n  \u003cbr/\u003e\n  扫码加入微信交流群\n\u003c/p\u003e\n\n## 引用\n\n如果本书对您的研究或工作有所帮助，请使用以下格式引用：\n\n**文本格式：**\n\n\u003e OpenMLSys Team. *机器学习系统：设计和实现*. 2022. https://openmlsys.github.io/\n\n**BibTeX：**\n\n```bibtex\n@book{openmlsys2022,\n  title     = {机器学习系统：设计和实现},\n  author    = {OpenMLSys Team},\n  year      = {2022},\n  url       = {https://openmlsys.github.io/},\n  note      = {开源教材，\\url{https://github.com/openmlsys/openmlsys-zh}}\n}\n```\n\n## 许可证\n\n本项目采用 [知识共享 署名-非商业性使用-相同方式共享 4.0 国际许可协议](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.zh) 授权。\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenmlsys%2Fopenmlsys","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopenmlsys%2Fopenmlsys","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenmlsys%2Fopenmlsys/lists"}