Hi, I'm a student at the technical university of Vienna and currently looking for a topic to complete my master thesis.
I stumbled over PEP 484 that currently is discussed on the mailing list. It seems to me that this is going to become reality pretty soon. I had the idea that this additional type annotations could beneficial for JIT compilation. Two weeks ago someone already mentioned pretty much the same idea (https://mail.python.org/pipermail/pypy-dev/2015-January/013037.html). In this thread it was mentioned that to improve the compiled code more detailed information (such as an integer stays in range [0-50], ...) would be necessary to remove guards of a trace. I read the document "Tracing the Meta-Level: PyPy's Tracing JIT Compiler" that was published 2009 to understand the basics of how PyPy currently works. I assume that PyPy is still a trace JIT compiler. By using the PEP 484 proposal I think this opens up new possibilities. Using trace compilation as it is done in PyPy or SpiderMonkey makes a lot of sense because most of the time type information is not present prior the first execution. PEP 484 changes the game. After type inference has completed e.g. on a function it should not occur often that a variable's type is unknown. The document "Tracing the Meta-Level" already mentioned that when RPython is provided as input to PyPy it already infers the type. Is that true for not RPython programs as well? I think there are two possibilities to improve the generated machine code for PyPy: * Find a sensible sub set of optimizations that rely on the available type information and further improve the trace compilation * Evaluate other possibilities of inter procedural methods to compile good machine code or completely move to method based jit compilation. I could imagine to evaluate and implement this for my master thesis. What do you think? Would it benefit PyPy? Has anybody else started to implement something similar? Best, Richard
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