> On Jun 22, 2018, at 4:49 PM, Matthew Knepley <[email protected]> wrote:
> 
>> On Fri, Jun 22, 2018 at 1:47 PM Boyce Griffith <[email protected]> wrote:
>> Can you set up the preconditioner so that you can just use GMRES?
> 
> So I think what Boyce is saying is, can't you fix the number of iterates in 
> the inner Krylov solvers so that it becomes a linear
> operator and you can use GMRES?

Yes that is it.

I think we default to FGMRES for robustness, because the preconditioner can 
easily be configured to be nonlinear, but unless you have made some big changes 
to the algorithm that I think you are using, I think it should be possible to 
set it up as a stationary linear operator.

>   Thanks,
> 
>      Matt
>  
>>> On Jun 22, 2018, at 4:33 PM, Nishant Nangia <[email protected]> 
>>> wrote:
>>> 
>>> 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
> 
> 
> -- 
> What most experimenters take for granted before they begin their experiments 
> is infinitely more interesting than any results to which their experiments 
> lead.
> -- Norbert Wiener
> 
> https://www.cse.buffalo.edu/~knepley/

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