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CUDA-Beginner-Course-Python-Version\n# CUDA 12.1 并行编程入门(Python语言版)\n\n\n\n***Note that this repository is under active development.***\n\n\n\n## Progress\n| Section | Videos                                                       | Codes                                         |\n| :------ | :----------------------------------------------------------- | :-------------------------------------------- |\n| 01      | [第1集 基于CuPy的CUDA跨平台开发环境配置](https://www.bilibili.com/video/BV1db4y1P7iX/) | [course01_hello_cuda](./course01_hello_cuda/) |\n|         |                                                              |                                               |\n\n\n\n\n## Todo\n\n- [ ] ...\n- [ ] ...\n\n\n\n## Acknowledgements\n\nThanks for the following excellent public learning resources.\n\n- [codingonion/awesome-cuda-tensorrt-fpga](https://github.com/codingonion/awesome-cuda-tensorrt-fpga) \u003cimg src=\"https://img.shields.io/github/stars/codingonion/awesome-cuda-tensorrt-fpga?style=social\"/\u003e : A collection of some awesome public NVIDIA CUDA, TensorRT, AMD ROCm and FPGA projects.\n\n- [codingonion/cuda-beginner-course-cpp-version](https://github.com/codingonion/cuda-beginner-course-cpp-version) \u003cimg src=\"https://img.shields.io/github/stars/codingonion/cuda-beginner-course-cpp-version?style=social\"/\u003e : bilibili视频【CUDA 12.1 并行编程入门(C++语言版)】配套代码。\n\n- [codingonion/cuda-beginner-course-rust-version](https://github.com/codingonion/cuda-beginner-course-rust-version) \u003cimg src=\"https://img.shields.io/github/stars/codingonion/cuda-beginner-course-rust-version?style=social\"/\u003e : bilibili视频【CUDA 12.1 并行编程入门(Rust语言版)】配套代码。\n\n- [codingonion/cuda-beginner-course-python-version](https://github.com/codingonion/cuda-beginner-course-python-version) \u003cimg src=\"https://img.shields.io/github/stars/codingonion/cuda-beginner-course-python-version?style=social\"/\u003e : bilibili视频【CUDA 12.1 并行编程入门(Python语言版)】配套代码。\n\n- [NVIDIA CUDA Docs](https://docs.nvidia.com/cuda/) : CUDA Toolkit Documentation.\n\n- [NVIDIA/cuda-samples](https://github.com/NVIDIA/cuda-samples) \u003cimg src=\"https://img.shields.io/github/stars/NVIDIA/cuda-samples?style=social\"/\u003e : Samples for CUDA Developers which demonstrates features in CUDA Toolkit.\n\n- [NVIDIA/CUDALibrarySamples](https://github.com/NVIDIA/CUDALibrarySamples) \u003cimg src=\"https://img.shields.io/github/stars/NVIDIA/CUDALibrarySamples?style=social\"/\u003e : CUDA Library Samples.\n\n- [HeKun-NVIDIA/CUDA-Programming-Guide-in-Chinese](https://github.com/HeKun-NVIDIA/CUDA-Programming-Guide-in-Chinese) \u003cimg src=\"https://img.shields.io/github/stars/HeKun-NVIDIA/CUDA-Programming-Guide-in-Chinese?style=social\"/\u003e : This is a Chinese translation of the CUDA programming guide. 本项目为 CUDA C Programming Guide 的中文翻译版。\n\n- [brucefan1983/CUDA-Programming](https://github.com/brucefan1983/CUDA-Programming) \u003cimg src=\"https://img.shields.io/github/stars/brucefan1983/CUDA-Programming?style=social\"/\u003e : Sample codes for my CUDA programming book.\n\n- [YouQixiaowu/CUDA-Programming-with-Python](https://github.com/YouQixiaowu/CUDA-Programming-with-Python) \u003cimg src=\"https://img.shields.io/github/stars/YouQixiaowu/CUDA-Programming-with-Python?style=social\"/\u003e :  关于书籍CUDA Programming使用了pycuda模块的Python版本的示例代码。\n\n- [QINZHAOYU/CudaSteps](https://github.com/QINZHAOYU/CudaSteps) \u003cimg src=\"https://img.shields.io/github/stars/QINZHAOYU/CudaSteps?style=social\"/\u003e : 基于《cuda编程-基础与实践》（樊哲勇 著）的cuda学习之路。\n\n- [sangyc10/CUDA-code](https://github.com/sangyc10/CUDA-code) \u003cimg src=\"https://img.shields.io/github/stars/sangyc10/CUDA-code?style=social\"/\u003e : B站视频教程【CUDA编程基础入门系列（持续更新）】配套代码。\n\n- [RussWong/CUDATutorial](https://github.com/RussWong/CUDATutorial) \u003cimg src=\"https://img.shields.io/github/stars/RussWong/CUDATutorial?style=social\"/\u003e : A CUDA tutorial to make people learn CUDA program from 0.\n\n- [DefTruth/cuda-learn-note](https://github.com/DefTruth/cuda-learn-note) \u003cimg src=\"https://img.shields.io/github/stars/DefTruth/cuda-learn-note?style=social\"/\u003e : 🎉CUDA 笔记 / 高频面试题汇总 / C++笔记，个人笔记，更新随缘: sgemm、sgemv、warp reduce、block reduce、dot product、elementwise、softmax、layernorm、rmsnorm、hist etc.\n\n- [Liu-xiandong/How_to_optimize_in_GPU](https://github.com/Liu-xiandong/How_to_optimize_in_GPU) \u003cimg src=\"https://img.shields.io/github/stars/Liu-xiandong/How_to_optimize_in_GPU?style=social\"/\u003e : This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.\n\n- [enp1s0/ozIMMU](https://github.com/enp1s0/ozIMMU) \u003cimg src=\"https://img.shields.io/github/stars/enp1s0/ozIMMU?style=social\"/\u003e : FP64 equivalent GEMM via Int8 Tensor Cores using the Ozaki scheme. [arxiv.org/abs/2306.11975](https://arxiv.org/abs/2306.11975)\n\n- [Bruce-Lee-LY/matrix_multiply](https://github.com/Bruce-Lee-LY/matrix_multiply) \u003cimg src=\"https://img.shields.io/github/stars/Bruce-Lee-LY/matrix_multiply?style=social\"/\u003e : Several common methods of matrix multiplication are implemented on CPU and Nvidia GPU using C++11 and CUDA.\n\n- [Bruce-Lee-LY/cuda_hgemm](https://github.com/Bruce-Lee-LY/cuda_hgemm) \u003cimg src=\"https://img.shields.io/github/stars/Bruce-Lee-LY/cuda_hgemm?style=social\"/\u003e : Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.\n\n- [Bruce-Lee-LY/cuda_hgemv](https://github.com/Bruce-Lee-LY/cuda_hgemv) \u003cimg src=\"https://img.shields.io/github/stars/Bruce-Lee-LY/cuda_hgemv?style=social\"/\u003e : Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.\n\n- [Cjkkkk/CUDA_gemm](https://github.com/Cjkkkk/CUDA_gemm) \u003cimg src=\"https://img.shields.io/github/stars/Cjkkkk/CUDA_gemm?style=social\"/\u003e : A simple high performance CUDA GEMM implementation.\n\n- [AyakaGEMM/Hands-on-GEMM](https://github.com/AyakaGEMM/Hands-on-GEMM) \u003cimg src=\"https://img.shields.io/github/stars/AyakaGEMM/Hands-on-GEMM?style=social\"/\u003e : A GEMM tutorial.\n\n- [zpzim/MSplitGEMM](https://github.com/zpzim/MSplitGEMM) \u003cimg src=\"https://img.shields.io/github/stars/zpzim/MSplitGEMM?style=social\"/\u003e : Large matrix multiplication in CUDA.\n\n- [jundaf2/CUDA-INT8-GEMM](https://github.com/jundaf2/CUDA-INT8-GEMM) \u003cimg src=\"https://img.shields.io/github/stars/jundaf2/CUDA-INT8-GEMM?style=social\"/\u003e : CUDA 8-bit Tensor Core Matrix Multiplication based on m16n16k16 WMMA API.\n\n- [chanzhennan/cuda_gemm_benchmark](https://github.com/chanzhennan/cuda_gemm_benchmark) \u003cimg src=\"https://img.shields.io/github/stars/chanzhennan/cuda_gemm_benchmark?style=social\"/\u003e : Base on gtest/benchmark, refer to [https://github.com/Liu-xiandong/How_to_optimize_in_GPU](https://github.com/Liu-xiandong/How_to_optimize_in_GPU).\n\n- [YuxueYang1204/CudaDemo](https://github.com/YuxueYang1204/CudaDemo) \u003cimg src=\"https://img.shields.io/github/stars/YuxueYang1204/CudaDemo?style=social\"/\u003e : Implement custom operators in PyTorch with cuda/c++.\n\n- [CoffeeBeforeArch/cuda_programming](https://github.com/CoffeeBeforeArch/cuda_programming) \u003cimg src=\"https://img.shields.io/github/stars/CoffeeBeforeArch/cuda_programming?style=social\"/\u003e : Code from the \"CUDA Crash Course\" YouTube series by CoffeeBeforeArch.\n\n- [rbaygildin/learn-gpgpu](https://github.com/rbaygildin/learn-gpgpu) \u003cimg src=\"https://img.shields.io/github/stars/rbaygildin/learn-gpgpu?style=social\"/\u003e : Algorithms implemented in CUDA + resources about GPGPU.\n\n- [PacktPublishing/Learn-CUDA-Programming](https://github.com/PacktPublishing/Learn-CUDA-Programming) \u003cimg src=\"https://img.shields.io/github/stars/PacktPublishing/Learn-CUDA-Programming?style=social\"/\u003e : Learn CUDA Programming, published by Packt.\n\n- [PacktPublishing/Hands-On-GPU-Accelerated-Computer-Vision-with-OpenCV-and-CUDA](https://github.com/PacktPublishing/Hands-On-GPU-Accelerated-Computer-Vision-with-OpenCV-and-CUDA) \u003cimg src=\"https://img.shields.io/github/stars/PacktPublishing/Hands-On-GPU-Accelerated-Computer-Vision-with-OpenCV-and-CUDA?style=social\"/\u003e : Hands-On GPU Accelerated Computer Vision with OpenCV and CUDA, published by Packt.\n\n- [PacktPublishing/Hands-On-GPU-Programming-with-Python-and-CUDA](https://github.com/PacktPublishing/Hands-On-GPU-Programming-with-Python-and-CUDA) \u003cimg src=\"https://img.shields.io/github/stars/PacktPublishing/Hands-On-GPU-Programming-with-Python-and-CUDA?style=social\"/\u003e : Hands-On GPU Programming with Python and CUDA, published by Packt.\n\n","funding_links":[],"categories":["Learning Resources"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoderonion%2Fcuda-beginner-course-python-version","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcoderonion%2Fcuda-beginner-course-python-version","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcoderonion%2Fcuda-beginner-course-python-version/lists"}