Extrapolation-accelerated Aggregation Multigrid with Block Relaxations for GeneRank Problems
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This paper proposes an aggregation multigrid method for computing the GeneRank problem. In this multigrid, the GeneRank transition matrix's formulation is well exploited, and a Block-Jacobi relaxation based on the aggregates, is employed. This block relaxation is well-defined in the multigrid hierarchy and expected to be more efficient than the point-wise version. Besides, the whole method is further accelerated by an extrapolation technique. Numerical experiments demonstrate the potential of this method for computing GeneRank problems. © 2017 ACM.