It would be nice if there were comparable benchmark results available, or a discussion of what is different between both approaches/implementations.
EDIT: bb link didn't work, replaced it with ACM portal link.
It would be nice if there were comparable benchmark results available, or a discussion of what is different between both approaches/implementations.
EDIT: bb link didn't work, replaced it with ACM portal link.
They were using an old version of PyPy and did not use some of the advanced features of the JIT generator.
It's interesting that you mention the advanced features. I looked at Hippy and the most interesting JIT feature Hippy uses is _virtualizable2_, which virtualizes all function locals and unboxes them. We tried using it ourselves, but it forces each function to have a static list of variables and no dynamic variable accesses (like $$x). It looks like Hippy falls back to the regular implementation for dynamic variable accesses, where the entire list is stored in a dictionary. Now I'm wondering how much this happens in real-world code, we assumed it does happen enough times.
Also, I'm working on posting a publicly-available version of the paper. I'll post a link when I do that.