Not everyone will write their own optimizing compiler from scratch, but those who do sometimes roll into it during the course of ever-growing project scope creep. People like [Michael Moroz], who wrote up a long and detailed article on the why and how. Specifically, a ‘small library’ involving a few matrix operations for a Unity-based project turned into a static optimizing tensor compiler, called TensorFrost, with a Python front-end and a shader-like syntax, all of which is available on GitHub.
The Python-based front-end implements low-level NumPy-like operations, with development still ongoing. As for why Yet Another Tensor Library had be developed, the reasons were that most of existing libraries are heavily focused on machine learning tasks and scale poorly otherwise, dynamic control flow is hard to implement, and the requirement of writing custom kernels in e.g. CUDA.
Above all [Michael] wanted to use a high-level language instead of pure shader code, and have something that can output graphical data in real-time. Taking the gamble, and leaning on LLVM for some parts, there is now a functional implementation, albeit with still a lot of work ahead.
