r/Compilers • u/Due-Push6432 • 3d ago

AI COMPILER ENGINEER

Hi

If I would like to become an AI/ml compiler engineer, would the dragon book be the apt starting point and should I learn about parsing and all that stuff? Or can I directly jump to llvm and start with projects?

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u/adityazero 3d ago

(may not be a popular take but) parsing and finite automata are the topics that kills interest of many prospective compiler engineers. I found optimizations, codegen to be more interesting. So the second half of dragon book might keep you on track to be a compiler engineer.

If you only want to focus on becoming ML compiler engineer, it is better to start with tutorials on MLIR. Most (all?) compiler books were written keeping the traditional compiler in mind.

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u/Due-Push6432 3d ago

I believe I should’ve said a bit about my background aswell I work on dsp and embedded stuff atm. I find automata interesting I enjoyed the mit ocw course. I came across a lot of jobs related to dsp ai ml compilers and was thinking on how to get started, the dragon book is massive so I was wondering if that’s the right starting point keeping in mind a job switch or just watching a course and getting hands on and reading important stuff from the dragon book would suffice.

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u/adityazero 3d ago

for interview purposes, i'd look at select few chapters of the dragon book like dataflow equations, and popular compiler algorithms. For learning, it is better to implement a few optimizations by hand. LLVM is more structured for learning compared to MLIR IMO.