└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # hpc-learning 2 | 本库用来整理HPC及相关领域的学习资料，由于个人能力有限，且HPC相关内容浩如烟海，欢迎多多提Issue并且一起维护。 3 | 4 | 另外，推荐[CS自学指南](https://csdiy.wiki/)，这是一个北大老哥整理的很好的相关资源，我这里没有推荐到的，推荐去那边参考 5 | 6 | ## 内容包括 7 | - 基础课程 8 | - C/C++ 9 | - 计算机架构 10 | - 并行计算原理 11 | - GPGPU 12 | - 相关知识 13 | - 进阶方向 14 | - 深度学习系统 15 | - 深度学习编译 16 | - 量化金融开发(Quant dev) 17 | - 项目 18 | - 线性代数 19 | - 深度学习 20 | - 并行计算 21 | - 深度学习编译 22 | - 高性能算子 23 | - 量化金融开发 24 | 25 | 26 | 课程及相关分枝包括以下内容 27 | - 书籍 📚 28 | - 课程 🖥️ 29 | - 相关资料🗂️ 30 | 31 | # 基础课程 32 | ## C/C++ 33 | - 📚 34 | - [C++ Primer](https://zhjwpku.com/assets/pdf/books/C++.Primer.5th.Edition_2013.pdf) 35 | - [Effective Modern C++](https://www.amazon.com/Effective-Modern-Specific-Ways-Improve/dp/1491903996/ref=sr_1_1?crid=2YG6ECDD8JW5M&keywords=effective+modern+c%2B%2B&qid=1555244788&s=books&sprefix=effective+modern+%2Cstripbooks-intl-ship%2C214&sr=1-1) 36 | - [现代 C++ 教程：高速上手 C++ 11/14/17/20](https://changkun.de/modern-cpp/) 37 | - 🖥️ 38 | - [南科大计算机系:快速学习C和C++](https://www.bilibili.com/video/BV1Vf4y1P7pq/) 39 | - [现代C++中的高性能并行编程与优化](https://www.bilibili.com/video/BV1fa411r7zp/) 40 | 41 | - 🗂️ 42 | - [Hacking C++ 现代c++学习路线、Cheatsheet以及新feature](https://hackingcpp.com/index.html) 43 | - [Cpp官方参考指南](https://en.cppreference.com/w/) 44 | 45 | ## 计算机架构 46 | - 📚 47 | - [计算机系统架构](http://acs.pub.ro/~cpop/SMPA/Computer%20Architecture%20A%20Quantitative%20Approach%20(5th%20edition).pdf) 48 | - [深入理解计算机系统](https://github.com/Sorosliu1029/CSAPP-Labs/blob/master/Computer%20Systems%20A%20Programmers%20Perspective%20(3rd).pdf) 49 | - 🖥️ 50 | - [ETH:Computer Architecture](https://safari.ethz.ch/architecture/) 51 | 52 | - 🗂️ 53 | 54 | ## 并行计算 55 | - 📚 56 | - [High Performance Parallel Runtimes](https://www.degruyter.com/document/doi/10.1515/9783110632729/html) 57 | - [C++ Concurrency In Action, C++并发编程实践](https://github.com/xiaoweiChen/CPP-Concurrency-In-Action-2ed-2019) 58 | 59 | - 🖥️ 60 | - [伯克利CS267：并行计算应用](https://sites.google.com/lbl.gov/cs267-spr2021) 61 | - [CMU 15-418/618:并行计算架构及编程](http://15418.courses.cs.cmu.edu/spring2016/home) 62 | - [MIT:软件系统性能优化](https://ocw.mit.edu/courses/6-172-performance-engineering-of-software-systems-fall-2018/) 63 | - [MIT:软件系统性能优化, 中翻](https://b23.tv/5vXhKWL) 64 | - 🗂️ 65 | 66 | ## GPGPU 67 | - 📚 68 | - [通用图形处理器架构](https://link.springer.com/book/10.1007/978-3-031-01759-9) 69 | - [CUDA C++编程指南](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#programming-model) 70 | 71 | - 🖥️ 72 | - [NVIDIA, CUDA Training Series](https://www.youtube.com/playlist?list=PL6RdenZrxrw-zNX7uuGppWETdxt_JxdMj) 73 | - 🗂️ 74 | - [如何开发机器学习系统：高性能GPU矩阵乘法](https://zhuanlan.zhihu.com/p/531498210) 75 | - [CUDA Training Series, Exercises](https://github.com/olcf/cuda-training-series?tab=readme-ov-file) 76 | 77 | # 进阶方向 78 | ## 深度学习系统 79 | - 📚 80 | - [机器学习系统：设计和实现](https://github.com/openmlsys/openmlsys-zh) 81 | 82 | - 🖥️ 83 | - [CMU10-414/714:深度学习系统](https://dlsyscourse.org/lectures/) 84 | 85 | - 🗂️ 86 | 87 | ## 深度学习编译 88 | - 📚 89 | 90 | - 🖥️ 91 | - [陈天奇:MLC-机器学习编译](https://space.bilibili.com/1663273796/channel/collectiondetail?sid=499979) 92 | 93 | - 🗂️ 94 | - [tvm_mlir_learn](https://github.com/BBuf/tvm_mlir_learn) 95 | 96 | ## 量化金融开发(Quant dev) 97 | - 📚 98 | 99 | - 🖥️ 100 | 101 | - 🗂️ 102 | 103 | ## 项目 104 | - 线性代数 105 | - [OpenBLAS](https://www.openblas.net/) 106 | - [Eigen Core](https://eigen.tuxfamily.org/index.php?title=Main_Page) 107 | - [CUTLASS3.0](https://github.com/NVIDIA/cutlass) 108 | 109 | - 深度学习框架 110 | - [TensorRT](https://github.com/NVIDIA/cutlass) 111 | - [tensorflow](https://github.com/tensorflow/tensorflow) 112 | - [PyTorch](https://github.com/pytorch/pytorch) 113 | - [MindSpore](https://github.com/mindspore-ai/mindspore) 114 | 115 | 116 | - 并行计算 117 | - [OpenMP](https://github.com/llvm/llvm-project/tree/main/openmp) 118 | 119 | - 深度学习编译 120 | - [MLIR](https://mlir.llvm.org/) 121 | - [TVM](https://github.com/apache/tvm) 122 | 123 | 124 | - 高性能算子库 125 | - [OpenPPL](https://openppl.ai/home) 126 | 127 | - Python加速库 128 | - [taichi](https://github.com/taichi-dev/taichi) 129 | - [numba](https://github.com/numba/numba) 130 | - [pybind11](https://github.com/pybind/pybind11) 131 | - [cython](https://github.com/cython/cython) 132 | 133 | - 量化金融开发 134 | - [backtrader](https://github.com/mementum/backtrader) 135 | - [qlib](https://github.com/microsoft/qlib) 136 | - [zipline](https://github.com/quantopian/zipline) 137 | - [TA-Lib](https://github.com/TA-Lib/ta-lib-python) 138 | --------------------------------------------------------------------------------