It's a very different algorithm, but FBCGS is a flexible method that supports preconditioned norm (though I don't how meaningful it is since the preconditioner is changing).
Nishant Nangia <[email protected]> writes: > Hi, > > I am solving a saddle point system using a shell preconditioner (which > itself uses Krylov solvers, hence the use of FGMRES). I had added the > option to re-scale parts of the saddle point system to minimize loss of > floating point precision for cases where there are varying orders of > magnitude in the system/unknowns. > > I wanted to show that re-scaling can alleviate large differences between > the preconditioned and unpreconditioned residual norms. However, I notice > that FGMRES only supports right preconditioning, meaning the preconditioned > residual is never formed/used (I think). > > Is there any way to form the preconditioned norm for FGMRES, or does it > just not make sense in the context of right-preconditioned iterative > solvers? Is there any way to show that the re-scaling is improving the > solver convergence (i.e. showing that it ensures that the true and relative > residual are close to each other)? > > *Nishant Nangia* > Northwestern University > Ph.D. Candidate | Engineering Sciences and Applied Mathematics > Tech L386
