Aykanat, CevdetPınar, A.Çatalyürek Ü. V.2016-02-082016-02-0820041064-8275http://hdl.handle.net/11693/24145We investigate the problem of permuting a sparse rectangular matrix into block-diagonal form. Block-diagonal form of a matrix grants an inherent parallelism for solving the deriving problem, as recently investigated in the context of mathematical programming, LU factorization, and QR factorization. To represent the nonzero structure of a matrix, we propose bipartite graph and hypergraph models that reduce the permutation problem to those of graph partitioning by vertex separator and hypergraph partitioning, respectively. Our experiments on a wide range of matrices, using the state-of-the-art graph and hypergraph partitioning tools MeTiS and PaToH, revealed that the proposed methods yield very effective solutions both in terms of solution quality and runtime.EnglishCoarse-grain parallelismDoubly bordered block-diagonal formGraph partitioning by vertex separatorHypergraph partitioningSingly bordered block-diagonal formSparse rectangular matricesCoarse-grain parallelismDoubly bordered block-diagnol formGraph partitioning by vertex separatorsHypergraph partitioningSingly bordered block diagnol formSparse rectangular matricesAlgorithmsApproximation theoryGraph theoryMathematical modelsMathematical programmingProblem solvingMatrix algebraArticle10.1137/S1064827502401953