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Distributed Multigrid Neural Solvers on Megavoxel Domains
[article]
2021
arXiv
pre-print
We consider the distributed training of large-scale neural networks that serve as PDE solvers producing full field outputs. We specifically consider neural solvers for the generalized 3D Poisson equation over megavoxel domains. A scalable framework is presented that integrates two distinct advances. First, we accelerate training a large model via a method analogous to the multigrid technique used in numerical linear algebra. Here, the network is trained using a hierarchy of increasing
arXiv:2104.14538v1
fatcat:ctqujbs7sraidktqejuh33qonq