A self-learning tutorail for CUDA High Performance Programing.
☆1,066Jan 14, 2026Updated 6 months ago
Alternatives and similar repositories for CUDATutorial
Users that are interested in CUDATutorial are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Modern CUDA Learn Notes with PyTorch for Beginners, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.☆11,735Updated this week
- CUDA 算子手撕与面试指南☆1,074Aug 23, 2025Updated 11 months ago
- how to optimize some algorithm in cuda.☆3,189Updated this week
- Material for gpu-mode lectures☆6,413Jun 15, 2026Updated last month
- FlashInfer: Kernel Library for LLM Serving☆6,133Updated this week
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- My learning notes for ML SYS.☆6,842Updated this week
- learning how CUDA works☆399Mar 3, 2025Updated last year
- This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several…☆1,339Jul 29, 2023Updated 3 years ago
- ☆2,788Jan 16, 2024Updated 2 years ago
- Nano vLLM☆14,923Apr 26, 2026Updated 3 months ago
- Fast and Memory-Efficient Exact Attention for Large Headdim, 1.5x~6x speedup over PyTorch SDPA.☆321Updated this week
- 校招、秋招、春招、实习好项目！带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library st…☆3,488Jun 22, 2025Updated last year
- 📚A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.🎉☆5,448Jul 26, 2026Updated 2 weeks ago
- 校招、秋招、春招、实习好项目，带你从零动手实现支持LLama2/3和Qwen2.5的大模型推理框架。☆557Oct 28, 2025Updated 9 months ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.☆6,208Updated this week
- Distributed Compiler based on Triton for Parallel Systems☆1,512Updated this week
- flash attention tutorial written in python, triton, cuda, cutlass☆532Jan 20, 2026Updated 6 months ago
- High Performance LLM Inference Operator Library☆1,094Updated this week
- 分享AI Infra知识&代码练习：PyTorch、vLLM/SGLang、slime/vime框架入门⚡️、性能加速🚀、大模型基础🧠、AI软硬件🔧等☆3,411Updated this week
- A compact implementation of SGLang, designed to demystify the complexities of modern LLM serving systems.☆4,716May 17, 2026Updated 2 months ago
- This is a Chinese translation of the CUDA programming guide☆2,033Nov 13, 2024Updated last year
- NVSHMEM‑Tutorial: Build a DeepEP‑like GPU Buffer☆195Feb 11, 2026Updated 5 months ago
- Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels☆7,167Updated this week
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Examples of CUDA implementations by Cutlass CuTe☆281Jul 1, 2025Updated last year
- ☆122May 16, 2025Updated last year
- Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruct…☆562Sep 8, 2024Updated last year
- A fast communication-overlapping library for tensor/expert parallelism on GPUs.☆1,352Aug 28, 2025Updated 11 months ago
- A CUDA tutorial to make people learn CUDA program from 0☆280Jul 9, 2024Updated 2 years ago
- Flash Attention in ~100 lines of CUDA (forward pass only)☆1,174Dec 30, 2024Updated last year
- From Minimal GEMM to Everything☆232Jul 9, 2026Updated last month
- A lightweight design for computation-communication overlap.☆243Jan 20, 2026Updated 6 months ago
- CUDA Templates and Python DSLs for High-Performance Linear Algebra☆10,217Updated this week
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- compiler learning resources collect.☆2,764May 20, 2026Updated 2 months ago
- AIInfra（AI 基础设施）指AI系统从底层芯片等硬件，到上层软件栈支持AI大模型训练和推理。☆7,887Dec 22, 2025Updated 7 months ago
- NVIDIA cuTile learn☆169Dec 9, 2025Updated 8 months ago
- Materials for learning SGLang☆869Jan 5, 2026Updated 7 months ago
- SGLang is a high-performance serving framework for large language models and multimodal models.☆31,578Updated this week
- Optimizing SGEMM kernel functions on NVIDIA GPUs to a close-to-cuBLAS performance.☆421Jan 2, 2025Updated last year
- how to learn PyTorch and OneFlow☆501May 20, 2026Updated 2 months ago