A couple months ago I found myself unemployed, uncertain about what to do next. I wanted to learn more about deep learning, but from a systems prespective. Coming from Andrew's Ng course on supervised learning, I was eager to learn more about how deep learning frameworks (or deep learning compilers) like Pytorch or Tinygrad.<p>I started to poke around Tinygrad, learning from the tutorials I found online, and I found it fascinating because it was an actual compiler, it took conventional python code and translated them into an Abstract Syntax Tree that was parsed into UOps and ScheduleItems, to finally have a codegen layer. While the design was interesting, the code was hard to read.<p>That's when I stumbled across something completly unexpected, A deep learning compiler built on Common Lisp, maintained by a Japanese 18-year-old during his gap year. And currently we have acomplished something great, it can run gpt2!<p>For now, it just generates C-kernels, but in the future we would like to support cuda codegen as well as many other features, and serve as a learning tool for anyone who would like to get to work on deep learning compilers in Common Lisp.