Hi Stefan, 2012/2/24 Stefan Behnel <stefan...@behnel.de>
> So, as a reply to the OP: seeing the current advances in getting Cython > code to run in PyPy (interfacing at the C-API level), another option would > be to do exactly as you would in CPython and implement the performance > critical parts of the code that heavily rely on gmp interaction in Cython > (to get plain C code out of it), and then import and use that from PyPy, > but at a much higher level than with direct individual calls to the gmp > functions. However much faster ctypes can be in PyPy than in CPython, you > just can't beat the performance of a straight block of C code when the goal > is to talk to C code. Cython will also allow you to run code in parallel > with OpenMP, in case you need that. > Cython won't be fast with PyPy. The C code it generates is too much specialized for CPython. For example, I've seen huge slowdowns in the Cython program itself (while compiling lxml, for example) when the various Cython extension modules (Nodes.c for example) started to compile and became available for pypy. I was about to write the list of operations that cpyext performs for PyTuple_GET_ITEM, but this macro is too large to fit in the margin :-) And PyDict_Next is a nightmare: https://bitbucket.org/pypy/pypy/src/9f0e8a37712b/pypy/module/cpyext/dictobject.py#cl-177 It's one thing to be able to run lxml and other Cython-based libraries with pypy. it's another thing to pretend that Cython is the way to write fast modules on pypy. You may win on the generated C code, but will loose when interfacing with the rest of the Python interpreter (which is also the reason why ctypes is so slow). This said, I've added all the functions you mentioned in a previous email. You may try your tests again with the nightly build. -- Amaury Forgeot d'Arc
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