yanght27/GPU-Perf-Playground

This comprehensive learning repository is designed to transform software engineers into expert AI kernel developers, focusing on the cutting-edge technologies required for developing high-performance GPU kernels using NVIDIA's latest architectures and libraries.

A curated resource list for learning AI performance engineering, from GPU fundamentals to production inference.

🍎 One kernel a day keeps high latency away. A hands-on CUDA learning path featuring a rich collection of kernels, from the basics to peak performance, seamlessly integrated as PyTorch C++ extensions.

Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.

Hello GPU：从 AMD GPU 架构、ROCm 工具链到 HIP/Triton 算子优化与单卡推理性能分析的实战教程。

Helpful kernel tutorials, examples and SKILLs for tile-based GPU programming

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

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