[pypy-dev] Newcommer in pypy, numpy user

Michael Hudson mwh at python.net
Mon Dec 18 17:39:36 CET 2006

David Cournapeau <david at ar.media.kyoto-u.ac.jp> writes:

> Hi there,
>     I am a recently convert of python, which I started using for my 
> numerical computing needs (I am a PhD student in signal processing) to 
> replace matlab.
>     For those who do not know matlab, it is a big (and expensive) 
> software which implements a 'language' optimized for linear algebra, and 
> with time becomes one of the most used software for numerical 
> computation. In my field of research (signal processing), matlab is 
> almost a standard (by standard, I mean everybody knows it and uses it). 
> I think python with numpy/scipy is better in almost any way if you are 
> ready to invest some time.
>     Now, concerning pypy. The main idea of numpy is to give an array 
> class to python, so that most inner loops are not interpreted, but run 
> in Cpython or through highly optimized fortran libraries. In those 
> cases, python is fast enough for most cases. But there are some cases 
> where this paradigm of using linear algebra to speed things up does not 
> work really well (recursive algorithms); in those case, the loop + 
> function call cost of python makes any implementation for non toy 
> problems really slow. Right now, the only choice is to code the thing in 
> C, with a big loss on the flexibility side.
>     I was wondering if pypy has some solution/new approaches to this 
> problem. For example, when using numpy, I would suspect that many 
> functions calls are 'static', that is always expect the same type of 
> arguments; also, for simple loop on integers, my understanding is that 
> JIT compilation has some nice solution to give to have much better 
> performances (matlab has a JIT compiler to make loop faster for 
> interpreted code).

It may be that the JIT is good for this sort of code.  It's not yet
though :-)

> It looks like at some point, there was some work done in pypy
> relatively to numpy arrays, but I didn't find any documentation on
> that.

As far as I'm aware this was something else: teaching PyPy's annotator
to recognise code that uses Numeric arrays and the code generator how
to compile this to equivalent code that manipulates arrays at a lower
level.  This could be seen as an alternative to rewriting your code in
C.  I'm not sure what the state of this code is, but I don't think
it's very advanced.


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