[petsc-users] Condition number of matrix

[Florian Lindner]

Thanks everybody, just to be sure, it's max/min of the last iteration?

Florian

Am 30.08.2016 um 16:10 schrieb Matthew Knepley:
> On Tue, Aug 30, 2016 at 9:03 AM, Florian Lindner <mailinglists at xgm.de <mailto:mailinglists at xgm.de>> wrote:
> 
>     Hi,
> 
>     Am 30.08.2016 um 14:05 schrieb Barry Smith:
>     >
>     >    The format of .petscrc requires each option to be on its own line
>     >
>     >> -ksp_view
>     >> -pc_type none
>     >> -ksp_type gmres
>     >> -ksp_monitor_singular_value
>     >> -ksp_gmres_restart 1000
> 
>     Oh man, didn't know that. Sorry! Is using a hash # ok for comments in .petscrc?
> 
>     I added the option accordingly:
> 
>     -ksp_view
>     -pc_type none
>     -ksp_type gmres
>     -ksp_monitor_singular_value
>     -ksp_gmres_restart 1000
> 
>     petsc outputs a line like:
> 
>     550 KSP Residual norm 1.374922291162e-07 % max 1.842011038215e+03 min 6.509297234157e-04 max/min 2.829815526858e+06
> 
>     for each iteration. Sorry about my mathematical illerateness, but where can I see the condition number of the matrix?
> 
> 
> Its max/min since this means max singular value/min singular value.
> 
>   Thanks,
> 
>      Matt
>  
> 
>     Thanks,
>     Florian
> 
>     >
>     >
>     >
>     >> On Aug 30, 2016, at 7:01 AM, Florian Lindner <mailinglists at xgm.de <mailto:mailinglists at xgm.de>> wrote:
>     >>
>     >> Hello,
>     >>
>     >> there is a FAQ and a Stackoverflow article about getting the condition number of a petsc matrix:
>     >>
>     >> http://www.mcs.anl.gov/petsc/documentation/faq.html#conditionnumber
>     <http://www.mcs.anl.gov/petsc/documentation/faq.html#conditionnumber>
>     >>
>     http://scicomp.stackexchange.com/questions/34/how-can-i-estimate-the-condition-number-of-a-large-sparse-matrix-using-petsc
>     <http://scicomp.stackexchange.com/questions/34/how-can-i-estimate-the-condition-number-of-a-large-sparse-matrix-using-petsc>
>     >>
>     >> Both tell me to add:
>     >>
>     >> -pc_type none -ksp_type gmres -ksp_monitor_singular_value -ksp_gmres_restart 1000
>     >>
>     >> to my options.
>     >>
>     >> I add the line to .petscrc but nothing happens, no additional output at all. I added -ksp_view, so my .petscrc looks
>     >> like that:
>     >>
>     >> -ksp_view
>     >> -pc_type none -ksp_type gmres -ksp_monitor_singular_value -ksp_gmres_restart 1000
>     >>
>     >> The complete output is below, but something I wonder about:
>     >>
>     >> GMRES: restart=30, shouldn't that be 1000
>     >>
>     >> And where can I read out the condition number approximation?
>     >>
>     >> Thanks,
>     >> Florian
>     >>
>     >>
>     >> KSP Object: 1 MPI processes
>     >>  type: gmres
>     >>    GMRES: restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
>     >>    GMRES: happy breakdown tolerance 1e-30
>     >>  maximum iterations=10000
>     >>  tolerances:  relative=1e-09, absolute=1e-50, divergence=10000.
>     >>  left preconditioning
>     >>  using nonzero initial guess
>     >>  using PRECONDITIONED norm type for convergence test
>     >> PC Object: 1 MPI processes
>     >>  type: none
>     >>  linear system matrix = precond matrix:
>     >>  Mat Object:  C   1 MPI processes
>     >>    type: seqsbaij
>     >>    rows=14403, cols=14403
>     >>    total: nonzeros=1044787, allocated nonzeros=1123449
>     >>    total number of mallocs used during MatSetValues calls =72016
>     >>        block size is 1
>     >> (0) 13:58:35 [precice::impl::SolverInterfaceImpl]:395 in initialize: it 1 of 1 | dt# 1 | t 0 of 1 | dt 1 | max dt 1 |
>     >> ongoing yes | dt complete no |
>     >> (0) 13:58:35 [precice::impl::SolverInterfaceImpl]:446 in advance: Iteration #1
>     >> KSP Object: 1 MPI processes
>     >>  type: gmres
>     >>    GMRES: restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
>     >>    GMRES: happy breakdown tolerance 1e-30
>     >>  maximum iterations=10000
>     >>  tolerances:  relative=1e-09, absolute=1e-50, divergence=10000.
>     >>  left preconditioning
>     >>  using nonzero initial guess
>     >>  using PRECONDITIONED norm type for convergence test
>     >> PC Object: 1 MPI processes
>     >>  type: none
>     >>  linear system matrix = precond matrix:
>     >>  Mat Object:  C   1 MPI processes
>     >>    type: seqsbaij
>     >>    rows=14403, cols=14403
>     >>    total: nonzeros=1044787, allocated nonzeros=1123449
>     >>    total number of mallocs used during MatSetValues calls =72016
>     >>        block size is 1
>     >
> 
> 
> 
> 
> -- 
> 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