2009
DOI: 10.1007/s11075-009-9311-2
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Adaptive version of Simpler GMRES

Abstract: Abstract. In this paper we propose a stable variant of Simpler GM-RES by Walker and Zhou [15]. It is based on the adaptive choice of the Krylov subspace basis at given iteration step using the intermediate residual norm decrease criterion. The new direction vector is chosen as in the original implementation of Simpler GMRES or it is equal the normalized residual vector as in the GCR method. We show that such adaptive strategy leads to a well-conditioned basis of the Krylov subspace and we support our theoretic… Show more

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Cited by 16 publications
(38 citation statements)
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“…Of course, this strategy means that a flexible GMRES (FGMRES) algorithm with right preconditioning is used instead of GMRES as the outer solver [37]. The flexible GMRES implementation used is the one described in [31] based on the simple GMRES algorithm in [38]. The tolerance of the inner iterations is denoted by tol in .…”
Section: The Use Of Inexact Solversmentioning
confidence: 99%
“…Of course, this strategy means that a flexible GMRES (FGMRES) algorithm with right preconditioning is used instead of GMRES as the outer solver [37]. The flexible GMRES implementation used is the one described in [31] based on the simple GMRES algorithm in [38]. The tolerance of the inner iterations is denoted by tol in .…”
Section: The Use Of Inexact Solversmentioning
confidence: 99%
“…For the latter we use the implementation based on the simpler GMRES algorithm described in [19]. Here, to solve the linear systems with the velocity-pressure equation and the vorticityhelicity equation, instead of applying one action of the AL-type preconditioners, a few inner GMRES iterations with corresponding preconditioners are used.…”
Section: Preconditioners and Solvers For Steady Problemsmentioning
confidence: 99%
“…By Lemma , the block columns in Zm are linear independent, and it can be regarded as the basis of Kmfalse(A,R0false). Lemma also allows κF(scriptZm)=κ2normalΓmLm1normalΩm1, from which the assertion is true by lemma 2.4 in the work of JR …”
Section: Glsgmres Methodsmentioning
confidence: 94%
“…Proof Note that Vm is well defined under the assumption R0AKm1false(A,R0false). From we have ZmS=trueR˜m1,V1,,Vm1Ym, where, by , the block columns of false[trueR˜m1,V1,,Vm1false] are F ‐orthogonal and Y m takes the form Ym=ρm1false/ρ0ξ1false/ρ01ξm1false/ρ01double-struckRm×m. Then, by Lemma , κFfalse(scriptZmnormalSfalse)=κ2false(Ymfalse), and the lower and upper bounds in follow straightforward from lemma 2.3 in the work of JR …”
Section: Glsgmres Methodsmentioning
confidence: 97%
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