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03/03/2023
Generalizing Lloyd's algorithm for graph clustering
Clustering is a commonplace problem in many areas of data science, with ...
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01/26/2023
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods
Domain decomposition methods (DDMs) are popular solvers for discretized ...
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12/16/2022
Generalizing Reduction-Based Algebraic Multigrid
Algebraic Multigrid (AMG) methods are often robust and effective solvers...
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08/05/2022
Parallel Energy-Minimization Prolongation for Algebraic Multigrid
Algebraic multigrid (AMG) is one of the most widely used solution techni...
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05/19/2022
Learning Interface Conditions in Domain Decomposition Solvers
Domain decomposition methods are widely used and effective in the approx...
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03/11/2022
Performance Analysis and Optimal Node-Aware Communication for Enlarged Conjugate Gradient Methods
Krylov methods are a key way of solving large sparse linear systems of e...
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06/03/2021
Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning
Large sparse linear systems of equations are ubiquitous in science and e...
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04/11/2019
Reducing Communication in Algebraic Multigrid with Multi-step Node Aware Communication
Algebraic multigrid (AMG) is often viewed as a scalable 𝒪(n) solver for ...
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10/28/2018
FFT, FMM, and Multigrid on the Road to Exascale: performance challenges and opportunities
FFT, FMM, and multigrid methods are widely used fast and highly scalable...
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10/28/2018
