The takeaway is that GPU literacy for AI engineers can be structured as one coherent hierarchy — threads, memory and hardware map onto each other layer by layer — rather than scattered vendor docs. Practitioners writing or tuning CUDA kernels for inference and training workloads can use it as both a reference and a linear course. It is a free web resource from Modal, an infrastructure provider, and reads more accessibly than the CUDA C++ Programming Guide.
#GPU编程
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Stories, products and papers tagged "GPU编程", newest first.
Sep 28
Modal GPU Glossary Maps the Full GPU Stack in Four Chapters
Sep 10
NVIDIA CUDA Toolkit 13.4
This update enables Windows on Arm64 developers to compile CUDA applications directly, preparing for RTX Spark PC launch in October with integrated Grace CPU and Blackwell GPU.
Aug 19
Aug 5
Jul 26
Chinese content用TileLang设计高性能GPU内核:Tensor-Core GEMM、融合Softmax与FlashAttention教程
想写GPU内核但被CUDA细节劝退?TileLang用Python帮你搞定Tensor-Core GEMM和FlashAttention,自动处理线程映射和调优,省心。
Jul 12
Chinese contentNVIDIA 基于块的 GPU 编程教程:从 cuTile 和 Triton 内核到 Flash Attention
手把手教你用 TileGym 在 Colab 上跑 cuTile 和 Triton,从向量加法到 Flash Attention,每个步骤都和 PyTorch 对照,适合想深入 GPU 编程的人。