issue_comments: 606228143

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https://github.com/pydata/xarray/issues/3232#issuecomment-606228143 https://api.github.com/repos/pydata/xarray/issues/3232 606228143 MDEyOklzc3VlQ29tbWVudDYwNjIyODE0Mw== 2448579 2020-03-30T20:24:08Z 2020-03-30T20:24:08Z MEMBER

Just chiming in quickly. I think there's definitely interest in doing this through NEP-18.

It looks like CUDA has implemented __array_function__ (https://docs-cupy.chainer.org/en/stable/reference/interoperability.html) so many things may "just work". There was some work earlier on plugging in pydata/sparse, and there is some ongoing work to plug in pint. With both these efforts, a lot of xarray's code should be "backend-agnostic" but its not perfect.

Have you tried creating DataArrays with cupy arrays yet? I would just try things and see what works vs what doesn't.

Practically, our approach so far has been to add a number of xfailed tests (test_sparse.py and test_units.py) and slowly start fixing them. So that's one way to proceed if you're up for it.

 
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