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Reducing Complexity in Parallel Algebraic Multigrid Preconditioners
2006
SIAM Journal on Matrix Analysis and Applications
Algebraic multigrid (AMG) is a very efficient iterative solver and preconditioner for large unstructured linear systems. Traditional coarsening schemes for AMG can, however, lead to computational complexity growth as problem size increases, resulting in increased memory use and execution time, and diminished scalability. Two new parallel AMG coarsening schemes are proposed, that are based on solely enforcing a maximum independent set property, resulting in sparser coarse grids. The new
doi:10.1137/040615729
fatcat:jfkdhihsyvdzbmiwrxzstbwdje