A general interpolation strategy for algebraic multigrid using energy minimization

Luke N. Olson, Jacob B. Schroder, Raymond S. Tuminaro

Research output: Contribution to journalArticlepeer-review


Algebraic multigrid methods solve sparse linear systems Ax = b by automatic construction of a multilevel hierarchy. This hierarchy is defined by grid transfer operators that must accurately capture algebraically smooth error relative to the relaxation method. We propose a methodology to improve grid transfers through energy minimization. The proposed strategy is applicable to Hermitian, non-Hermitian, definite, and indefinite problems. Each column of the grid transfer operator P is minimized in an energy-based norm while enforcing two types of constraints: a defined sparsity pattern and preservation of specified modes in the range of P. A Krylov-based strategy is used to minimize energy, which is equivalent to solving APj = 0 for each column j of P, with the constraints ensuring a nontrivial solution. For the Hermitian positive definite case, a conjugate gradient (CG-)based method is utilized to construct grid transfers, while methods based on generalized minimum residual (GMRES) and CG on the normal equations (CGNR) are explored for the general case. The approach is flexible, allowing for arbitrary coarsenings, unrestricted sparsity patterns, straightforward long-distance interpolation, and general use of constraints, either user-defined or auto-generated. We conclude with numerical evidence in support of the proposed framework.

Original languageEnglish (US)
Pages (from-to)966-991
Number of pages26
JournalSIAM Journal on Scientific Computing
Issue number2
StatePublished - 2011


  • Algebraic multigrid
  • Interpolation
  • Non-Hermitian
  • Nonsymmetric
  • Smoothed aggregation

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics


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