Corpus ID: 212675750

Learning Algebraic Multigrid Using Graph Neural Networks

@article{Luz2020LearningAM,
  title={Learning Algebraic Multigrid Using Graph Neural Networks},
  author={Ilay Luz and M. Galun and Haggai Maron and R. Basri and I. Yavneh},
  journal={ArXiv},
  year={2020},
  volume={abs/2003.05744}
}
Efficient numerical solvers for sparse linear systems are crucial in science and engineering. One of the fastest methods for solving large-scale sparse linear systems is algebraic multigrid (AMG). The main challenge in the construction of AMG algorithms is the selection of the prolongation operator -- a problem-dependent sparse matrix which governs the multiscale hierarchy of the solver and is critical to its efficiency. Over many years, numerous methods have been developed for this task, and… Expand

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