Recycling BiCGSTAB with an Application to Parametric Model Order Reduction
TLDR
In this article, the recycling BiCG algorithm is extended to BiCGSTAB, which uses a recycle space, which is built from left and right approximate invariant subspaces.Abstract:
Krylov subspace recycling is a process for accelerating the convergence of sequences of linear systems. Based on this technique, the recycling BiCG algorithm has been developed recently. Here, we now generalize and extend this recycling theory to BiCGSTAB. Recycling BiCG focuses on efficiently solving sequences of dual linear systems, while the focus here is on efficiently solving sequences of single linear systems (assuming nonsymmetric matrices for recycling BiCG and recycling BiCGSTAB). As compared with other methods for solving sequences of single linear systems with nonsymmetric matrices (e.g., recycling variants of GMRES), BiCG-based recycling algorithms, like recycling BiCGSTAB, have the advantage that they involve a short-term recurrence and hence do not suffer from storage issues and are also cheaper with respect to the orthogonalizations. We modify the BiCGSTAB algorithm to use a recycle space, which is built from left and right approximate invariant subspaces. Using our algorithm for a parametr...read more
Citations
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Recycling Krylov subspaces for CFD applications and a new hybrid recycling solver
TL;DR: A new, hybrid approach is proposed that combines the cheap iterations of BiCGStab with the robustness of rGCROT, and is evaluated on a turbulent channel flow problem and on a porous medium flow problem.
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A survey of subspace recycling iterative methods
TL;DR: This survey concerns subspace recycling methods, a popular class of iterative methods that enable effective reuse of subspace information in order to speed up convergence and find good initial vectors over a sequence of linear systems with slowly changing coefficient matrices, multiple right‐hand sides, or both.
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References
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GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems
Youcef Saad,Martin H. Schultz +1 more
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