issue_comments: 383817119

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https://github.com/pydata/xarray/issues/2074#issuecomment-383817119 https://api.github.com/repos/pydata/xarray/issues/2074 383817119 MDEyOklzc3VlQ29tbWVudDM4MzgxNzExOQ== 306380 2018-04-24T06:22:39Z 2018-04-24T06:22:39Z MEMBER

When doing benchmarks with things that might call BLAS operations in multiple threads I recommend setting the OMP_NUM_THREADS environment variable to 1. This will avoid oversubscription.

On Mon, Apr 23, 2018 at 7:32 PM, Keisuke Fujii notifications@github.com wrote:

@crusaderky https://github.com/crusaderky , Thanks for the detailed benchmarking. Further note:

  • xr.dot uses tensordot if possible, as when I implemented dask did not have einsum. In the other cases, we use dask.atop with np.einsum.

In your example, bench(100, False, ['t'], '...i,...i') uses dask.tensordot , bench(100, True, ['t'], '...i,...i') uses np.einsum.

bench(100, True, [], ...i,...i->...i) also uses np.einsum. But I have no idea yet why dot(a, b, dims=[]) is faster than a * b.

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