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Parallel Unsmoothed Aggregation Algebraic Multigrid Algorithms on GPUs

  • James Brannick
  • Yao Chen
  • Xiaozhe Hu
  • Ludmil ZikatanovEmail author
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 45)

Abstract

We design and implement a parallel algebraic multigrid method for isotropic graph Laplacian problems on multicore graphical processing units (GPUs). The proposed AMG method is based on the aggregation framework. The setup phase of the algorithm uses a parallel maximal independent set algorithm in forming aggregates, and the resulting coarse-level hierarchy is then used in a K-cycle iteration solve phase with a 1-Jacobi smoother. Numerical tests of a parallel implementation of the method for graphics processors are presented to demonstrate its effectiveness.

Keywords

Multigrid methods Unsmoothed aggregation Adaptive aggregation 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • James Brannick
    • 1
  • Yao Chen
    • 2
  • Xiaozhe Hu
    • 1
  • Ludmil Zikatanov
    • 1
    Email author
  1. 1.Department of MathematicsThe Pennsylvania State UniversityUniversity ParkUSA
  2. 2.Microsoft CorporationMountain ViewUSA

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