Blimey, that's a lot of waffle in there, but I suppose that's to be
expected from a published paper.
I think the gist of it is, that you highlight specific Python functions
that you need to be fast (add a decorator), then it tries to translate
those into actual C++ by inferring types. All done transparently at
runtime (although I imagine it would be hard to hide the huge machinery
of a C++ compiler in action).
The benchmarks seem to be individual functions which it presumably
successfully translated fully into C++, so it is effectively comparing
CPython to C++.
It also puts in a good dig at PyPy by including one benchmark where it
is 6 times as slow as CPython!
It's not clear why it's particularly useful for astrophysics.
HOPE: A Python just-in-time compiler for astrophysical computations
In a message of Sun, 21 Jun 2015 10:29:32 +0100, BartC writes:
>It also puts in a good dig at PyPy by including one benchmark where it
>is 6 times as slow as CPython!
>It's not clear why it's particularly useful for astrophysics.
It's not that good a dig, as they say that it took less than 1 second
to run most of their benchmarks, which mostly means that the PyPy JIT
won't have started to run anyway. One can argue that HOPE isn't
actually a method JIT at all -- or if it is one, then so is Cython.