[pypy-dev] array performace?

Maciej Fijalkowski fijall at gmail.com
Thu Jul 1 17:35:17 CEST 2010


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).



More information about the Pypy-dev mailing list