I'm doing a computer science masters and am looking for an appropriate project to take on for a dissertation related to Polyhedral optimisations. Talking to my professor, we both think trying to implement the model and it's loop transformations in PyPy's JIT optimiser could be a good project to pursue, but before committing to anything I wanted to run this idea by the devs here who might be able to point out any hurdles I'd be likely to quickly come across that could prove difficult to solve at just a masters level, or whether or not these optimisations are actually already implemented in the first place (I have tried to google if this is the case and hadn't found anything, but can't be sure). I think this could have some good real world impact too as a lot of scientific code is written in Python and run on PyPy, and the Polyhedral model can offer substantial performance improvements in the form of auto-parallelization for these types of codes, which is why I'm interested in working on this for PyPy rather than CPython, although if anyone has good reason that I might want to look at CPython for this over PyPy please let me know. Appreciate any and all advice, thanks.