[pypy-dev] array performace?

[Hakan Ardo]

OK, so making an interpreter level implementation of array.array seams
like a good idea. Would it be possible to get the jit to remove the
wrapping/unwrapping in that case to get better performance than
_rawffi.Array('d'), which is already an interpreter level
implementation?

Are there some docs to get me started at writing interpreter level
objects? I've had a look at _rawffi/array.py and am a bit confused
about the W_Array.typedef = TypeDef('Array',...)  construction. Maybe
there is a easier example to start with?

On Thu, Jul 1, 2010 at 5:40 PM, Alex Gaynor <alex.gaynor at gmail.com> wrote:
> On Thu, Jul 1, 2010 at 10:35 AM, Maciej Fijalkowski <fijall at gmail.com> wrote:
>> On Thu, Jul 1, 2010 at 9:28 AM, Armin Rigo <arigo at tunes.org> wrote:
>>> Hi,
>>>
>>> On Thu, Jul 01, 2010 at 04:02:30PM +0200, Hakan Ardo wrote:
>>>> are there any python construct that the jit will be able to compile
>>>> into c-type array accesses? Consider the following test:
>>>>
>>>>     l=0.0
>>>>     for i in xrange(640,640*480):
>>>>         l+=img[i]
>>>>         intimg[i]=intimg[i-640]+l
>>>
>>> This is still implemented as a list of Python objects (as expected,
>>> because the JIT cannot prove that we won't suddenly try to put something
>>> else than a float in the same list).
>>>
>>> Using _rawffi.Array('d') directly is the best option right now.  I'm not
>>> sure why the array.array module is 400 times slower, but it's definitely
>>> slower given that it's implemented at app-level using a _rawffi.Array('c')
>>> and doing the conversion by itself (for some partially stupid reasons like
>>> doing the right kind of error checking).
>>>
>>>
>>> A bientot,
>>>
>>> Armin.
>>
>> The main reason why _rawffi.Array is slow is that JIT does not look
>> into that module, so there is wrapping and unwrapping going on.
>> Relatively easy to fix I suppose, but _rawffi.Array was not meant to
>> be used like that (array.array looks like a better candidate).
>> _______________________________________________
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>> http://codespeak.net/mailman/listinfo/pypy-dev
>
> If array.array performance is important to your work, the array.py
> module looks like a good target for writing at interp level, and it's
> not too much code.
>
> Alex
>
> --
> "I disapprove of what you say, but I will defend to the death your
> right to say it." -- Voltaire
> "The people's good is the highest law." -- Cicero
> "Code can always be simpler than you think, but never as simple as you
> want" -- Me
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-- 
Håkan Ardö