[scikit-learn] nmf with multiple cores

[Tom DLT]

Hi Roberto,

As answered previously, there is no multi-threading available for NMF in
scikit-learn.

However, if you want to compute *multiple* NMF in parallel, you can use
joblib with a threading backend,
as the 'cd' solver releases the GIL (through cython code) during a large
part of the time.
The other main computational cost goes with numpy dot product, which
depends on your BLAS configuration.

To help choose the best settings for your needs, here is also a quick
example for benchmarking multithreading
<https://gist.github.com/TomDLT/c1d560a510a41dd80ab6>.

Best,

Tom

2016-09-30 12:52 GMT+02:00 Roberto Pagliari <roberto.pagliari at asos.com>:

> I’m running nmf on a machine with 16 cores.
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> Is there an option to run nmf with multithreading? I know numpy does, but
> all I see is one single process with 100% CPU usage.
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> Thanks,
>
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>
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