I was just running the bench script from your e-mail.

Does anybody have updated benchmarks compared to competing
implementations (you know which one I mean) against this branch? ;)

Vlad

On Sat, Dec 21, 2013 at 12:28 AM, Peter Prettenhofer
<peter.prettenho...@gmail.com> wrote:
> Actually, I'd propose to turn off multiprocessing at prediction time - this
> might backfire quite easily.
>
>
> 2013/12/20 Olivier Grisel <olivier.gri...@ensta.org>
>>
>> 2013/12/20 Vlad Niculae <zephy...@gmail.com>:
>> > Works exactly as you described on my machine (which doesn't mean much
>> > because it's relatively close to yours, but I am just too enthusiastic
>> > about this not to reply! \o/)
>> >
>> > Memory usage is as expected. I see a speedup in train time but a
>> > slight slowdown in test time (1.7 vs 1.0), is it expected or probably
>> > an artefact?
>>
>> Threading is not (yet) used at test time as the cython code backing
>> the predict method would need to be refactored to release the GIL to
>> make threading efficient.
>>
>> So the performance speed decrease you observe might be caused by the
>> new automated memmaping feature that dumps large arrays to use share
>> memory with with worker process when the multiprocessing backend is
>> used. Currently the threshold to trigger the automated memmaping is
>> set to 1MB arrays or larger. Maybe this is too small and we should
>> trigger it only for arrays larger than 100MB for instance.
>>
>> How big is the data array in your case, is this the covertype benchmark?
>>
>> --
>> Olivier
>>
>>
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>
>
>
> --
> Peter Prettenhofer
>
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