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 61 articles , 1 standard article )
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- Bu, Yiming; Carpentieri, Bruno; Shen, Zhaoli; Huang, Ting-Zhu: A hybrid recursive multilevel incomplete factorization preconditioner for solving general linear systems (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)
- Carpentieri, Bruno; Liao, Jia; Sosonkina, Masha: VBARMS: a variable block algebraic recursive multilevel solver for sparse linear systems (2014)
- Sousedík, Bedřich; Ghanem, Roger G.; Phipps, Eric T.: Hierarchical Schur complement preconditioner for the stochastic Galerkin finite element methods. (2014)
- van Slingerland, P.; Vuik, C.: Fast linear solver for diffusion problems with applications to pressure computation in layered domains (2014)
- Castillo, P. E.; Sequeira, F. A.: Computational aspects of the local discontinuous Galerkin method on unstructured grids in three dimensions (2013)
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