From Zero to GPU: A Guide to Building and Scaling Production-Ready CUDA Kernels

This guide explains how to build and scale production-ready CUDA kernels using the `kernel-builder` library. It details the entire process, from setting up the project structure and build manifests to writing the actual GPU code. A key step involves registering the custom function as a native PyTorch operator, which ensures compatibility with `torch.compile` and enables hardware-specific backends. The tutorial uses an image-to-grayscale conversion as a practical example to demonstrate how to create, build, and share these high-performance components.