Abstract: Highlights•Novel approach to parallelism in Fourier neural operators using domain decomposition.•Mathematical description of parallelism in the context of operator learning.•Distributed training of a learned surrogate for subsurface two-phase flow.•Largest forward inference and gradient computation of a Fourier neural operator.
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