ARMS
ARMS: an algebraic recursive multilevel solver for general sparse linear systems. The paper describes new recursive multilevel method for preconditioning of general sparse linear systems. This strategy is used in the new solver (ARMS) that generalize previous authors’ codes BILUM and BILUTM. All these methods are based on a block incomplete LU factorization. The ARMS is fully recursive and employs the nested dissection reordering and inner-level iterations. Assumptions, under which the new preconditioning is exact, are given together with the proof that eigenvalues of the preconditioned matrix are close to 1. par Extensive numerical tests are presented and cover various features of the method. They show that the solver ARMS is more robust, saves memory, but performs slower than ILUT and ILUTP (incomplete LU factorization with threshold and with threshold and pivoting).
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References in zbMATH (referenced in 56 articles , 1 standard article )
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Sorted by year (- Gupta, Anshul: Enhancing performance and robustness of ILU preconditioners by blocking and selective transposition (2017)
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- Estrin, R.; Greif, C.: Towards an optimal condition number of certain augmented Lagrangian-type saddle-point matrices. (2016)
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- van Slingerland, P.; Vuik, C.: Scalable two-level preconditioning and deflation based on a piecewise constant subspace for (SIP)DG systems for diffusion problems (2015)
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- van Slingerland, P.; Vuik, C.: Fast linear solver for diffusion problems with applications to pressure computation in layered domains (2014)
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- Vannieuwenhoven, Nick; Meerbergen, Karl: IMF: an incomplete multifrontal $LU$-factorization for element-structured sparse linear systems (2013)
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- Maclachlan, S.; Osei-Kuffuor, D.; Saad, Yousef: Modification and compensation strategies for threshold-based incomplete factorizations (2012)