Ok, this is my first post to this list and don't know if it's the right one. I'm currently making sort of a scientific application. Most data structures and algorithmic knots are in C++, and from there I have a set of extension modules to Python. So, users of the app don't have to compile or ever see C++ code to personalize the app to their ends, except for the inner mathematical part. Regarding the last statement, I saw a few messages in this list about Psyco, a JIT for Python and things like that. Well, I need all the speed the machine can deliver in the mathematica l spot (I know by profiling that it's is criticall), so, nothing of that can do the work. Recently I read something about generating mathematical kernels in Python for this kind of problems (can't locate the paper right now), the idea is to just generate machine code and have it to do the work, but it wasn't for x86 based architectures (yes, portability is always a nightmare regarding tools which generate native code). Do somebody know about a parallel effort for x86? If there isn't such a thing out there, could it be of some interest to people which is working numbers in Python?
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