[SciPy-Dev] Numba as a dependency for SciPy?

[Matthew Brett]

Hi,

On Thu, Mar 8, 2018 at 9:38 AM, Pauli Virtanen <pav at iki.fi> wrote:
> Ralf Gommers kirjoitti 08.03.2018 klo 08:04:
> [clip]
>>
>> Also, I don't think performance will necessarily be unacceptable. There
>> are
>> a bunch of places in the existing code base where we can throw in @jit and
>> get speedups basically for free. Performance in the noop case will then be
>> what it is today - not great, but apparently also not enough of a problem
>> that someone has attempted to go to Cython.
>
>
> I guess you agree that Numba would regardless be declared a dependency in
> setup.py? People on unsupported arches can edit it away manually.
>
> For computational tight loops operating on arrays when Numba is used as an
> alternative to Cython/C/Fortran, there probably will be a performance hit in
> the ballpark of 100x.
>
> If we are planning to use numba features more fully, e.g. numba.cfunc e.g.
> to write callback functions, that would also require Numba as a hard
> dependency.

If we were at the top of the stack, like pystatsmodels, then this
would be reasonable, but, if we make numba a dependency, that makes
numba a dependency for almost anyone doing scientific computing.  I
think we do have to care about people not running on Intel.   If we
make numba an optional dependency, it gives us an additional
maintenance burden, because we'd have to check for each numba segment,
whether it is going to be disabling for a user without numba.

Is there anything we have at the moment where Cython won't get us into
the ballpark?  If not, my preference would be to wait for a year or
so, to see how things turn out.

Cheers,

Matthew