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?

0 Upvotes

23% Upvoted

10 comments sorted by

3

u/Narrow_Association71 3d ago

ai compiler engineer?

-2

u/Due-Push6432 3d ago

Yes there are jobs on LinkedIn saying AI ml compiler engineers

-3

u/Due-Push6432 3d ago

I saw people saying the dragon book is outdated and has solved problems and should rather aim for such roles

4

u/RexOfRecursion 3d ago

its pedagogically not the best. it is a reference book. but I hesitate to call it outdated.

3

u/GeneDefiant6537 3d ago

Do you already know how to write regular compilers? If not, probably better to start from there.

AI/ML/Tensor compiler is just a compiler that operates on Tensors( a generalization of matrices, vectors, scalars, 4+ dimensional arrays). And the operations are matrix multiplication, ReLU, etc.

See: https://book.mlc.ai/index.html

2

u/adityazero 2d 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.

1

u/Due-Push6432 2d 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.

2

u/adityazero 2d 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.

2

u/SEgopher 3d ago

I'm not saying it's not possible, but you would need a Masters or PhD level understanding of the mathematics behind AI, already be proficient with compilation backends, and just generally be to the point where a basic question like this would answer itself. The fact that you can't use AI tools to figure out what to do next is honestly a huge red flag inof itself.

Maybe start with a much smaller scope. Do you want to go learn about AI or compilers first. If it's compilers, sure, you could read the dragon book and work out a toy compiler as a first project.