[verditelabs]

I've done some similar LLM compiler work, obviously not on Meta's scale, teaching an LLM to do optimization by feeding an encoder/decoder pairs of -O0 and -O3 code and even on my small scale I managed to get the LLM to spit out the correct optimization every once and a while.

I think there's a lot of value in LLM compilers to specifically be used for superoptimization where you can generate many possible optimizations, verify the correctness, and pick the most optimal one. I'm excited to see where y'all go with this.

[viraptor]

Thank you for freeing me from one of my to-do projects. I wanted to do a similar autoencoder with optimisations. Did you write about it anywhere? I'd love to read the details.

[verditelabs]

No writeup, but the code is here:

https://github.com/SuperOptimizer/supercompiler

There's code there to generate unoptimized / optimized pairs via C generators like yarpgen and csmith, then compile, train, inference, and disassemble the results

[hughleat]

Yes! An AI building a compiler by learning from a super-optimiser is something I have wanted to do for a while now :-)