[pypy-dev] Contributing to pypy [especially numpy]
arigo at tunes.org
Mon Oct 17 00:10:02 CEST 2011
On Sun, Oct 16, 2011 at 23:41, David Cournapeau <cournape at gmail.com> wrote:
> Interesting to know. But then, wouldn't this limit the speed gains to
> be expected from the JIT ?
Yes, to some extent. It cannot give you the last bit of performance
improvements you could expect from arithmetic optimizations, but (as
usual) you get already the several-times improvements of e.g. removing
the boxing and unboxing of float objects. Personally I'm wary of
going down that path, because it means that the results we get could
suddenly change their least significant digit(s) when the JIT kicks
in. At least there are multiple tests in the standard Python test
suite that would fail because of that.
> And I am not sure I understand how you can "not go there" if you want
> to vectorize code to use SIMD instruction sets ?
I'll leave fijal to answer this question in detail :-) I suppose that
the goal is first to use SIMD when explicitly requested in the RPython
source, in the numpy code that operate on matrices; and not do the
harder job of automatically unrolling and SIMD-ing loops containing
Python float operations. But even the later could be done without
giving up on the idea that all Python operations should be present in
a bit-exact way (e.g. by using SIMD on 64-bit floats, not on 32-bit
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