Mark: I'm just wondering what you wanted to do with NumPy from Cython -- a 
stopgap solution for SIMD, iterator support, or something else?

SIMD using NumPy really isn't the best idea long-term because of all the 
temporaries needed in compound expressions, which is really bad on the memory 
bus for anything but tiny arrays. For that I'd rather look at finding a nogil 
core of numexpr or similar.

Of course, there is a number of convenient NumPy utility functions which would 
be cool to have in nogil mode... But given that the GIL is a problem in so many 
cases, I wonder how far it is really possible to go even given the refactored 
numpy core.
-- 
Sent from my Android phone with K-9 Mail. Please excuse my brevity.

Pauli Virtanen <[email protected]> wrote:

31.10.2011 09:44, mark florisson kirjoitti: [clip] > Ah, that's too bad. Is it 
anywhere near ready, or was it abandoned for > ironclad? Could you point me to 
the code? It's quite ready and working, and as far as I understand, Enthought 
is shipping it. I haven't used it, though. The code is here: 
https://github.com/numpy/numpy-refactor        
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