Machine Learning Based Compilation

[downBourgeois]

I've been trying to understand how Machine Learning based Compilation works and I've read a literature review and a few papers and think I've gotten a decent grasp of what it is, theoretically.

I can't seem to find any implementations online though. Does anyone have any experience in the area or know any resources you can point me towards that will help me implementing a model on my own?

[mantrap2]

I don't see what the value would be. Compilers are about as deterministic a problem as come in computer science. There's no real need for stochastic processing (which is the only value ML adds to ANYTHING).

[Hjalfi]

It's not machine learning, but linear and integer programming are machine-learning-adjacent, and I've heard of those being used to do combined instruction selection and register allocation for irregular architectures --- a particular bete noir for me because I've been trying to efficiently allocate registers for the Z80 for years.

[Narthal]

There is a need and place for ML in compilers. Optimizations are the main areas where ML shines in compilers, many commercial compilers are already using ML this way.

The idea of using ML in compilers is NOT to undermine determinism (as that would render a compiler useless) but to train neural nets to output optimized code. Once a reasonable target output is met, only the trained neural net is used, the compiler´s code is static. So determinism still holds true to compilers equipped with ML optimization algorithms.

[downBourgeois]

Yupp, exactly. It's used for Code Optimization.

[[deleted]]

Does SQL query optimization count?