[Edu-sig] Properties use case

Laura Creighton lac at strakt.com
Wed Mar 22 10:57:29 CET 2006

In a message of Tue, 21 Mar 2006 13:58:52 CST, "Michael Tobis" writes:
>While PyPy is a most admirable endeavor, I can't imagine that it can
>resolve this problem.  I'll be most pleased to discover that I am
>wrong, so please correct me.
>Is scientific programming a target usage of PyPy?


>In particular, how could large arrays of numbers of homogeneous type
>be handled outside the Numeric-type libraries in such a way that
>efficient computation is possible and also provide a guarantee the
>memory mapping of the data to allow interoperation with compiled

This one is better discussed on pypy-dev at codespeak.net where you will
get better answers from people who are actually implementing this
stuff :-)

>Surely a reimplementation of BLAS, Atlas, Lapack, etc is not part of
>PyPy's mission. So how is the success of PyPy going to have great
>relevance to Numeric/numarray/numpy users?

We don't -- at least right now -- want to replace these cases where
you use numeric because you really need a lot of linear algebra.
(Though the goal is to make it easy for researchers to drop in
algorithms that can speed up their code, so who knows what people
will do with it, eventually).  But a lot of people are using numeric
simply for speed and more memory packing.  These people will find it
easier to write their programs in PyPy, just as some of them now find
it easier to write their programs in straightforward python and then
use Psyco.

I could be wrong, but I don't think it is the linear algebra that
Arthur wants, or needs.  He wants 'bloody fast arrays'.  And I think
he will like tens of thousands of threads, too, though if these
just means tens of thousands of chances to modify only part of your
complex number, when you wanted an atomic action guaranteed to
modify both parts as one, then he may hate it before he likes it. :-)



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