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.
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