现代 CUDA 工具链实践：逐步优化指南
原标题：The Modern CUDA Toolbox in Practice: A Step-by-Step Optimization Walkthrough
AI 摘要
NVIDIA 技术博客发布了一篇关于现代 CUDA 工具链的实践指南，通过六步增量优化示例代码，涵盖使用 CCCL API 和 Compute Sanitizer 查找索引错误、NVTX 改进基准测试、CUB 优化算法、池化容器管理 GPU 内存、固定容器加速主机到设备传输，以及多流异步并行化。文章旨在帮助开发者编写更安全、可维护且高性能的 CUDA 代码，并提供了配套代码和 Google Colab 运行选项。
正文节选
NVIDIA CUDA remains the foundation of GPU-accelerated computing, powering everything from scientific simulations to large-scale AI training. But writing correct, maintainable, and performant CUDA code can be challenging: memory bugs hide in plain sight, performance bottlenecks can be invisible without the right instrumentation, and hand-rolled GPU algorithms rarely match the efficiency of optimized libraries. Fortunately, the modern CUDA toolchain has matured significantly, and many of these cha