[petsc-users] KSP linear solver returns inf

[Manav Bhatia]

Thanks, Matt. 

Following is the output with: -ksp_monitor_lg_residualnorm -ksp_log -ksp_view -ksp_monitor_true_residual -ksp_converged_reason

  0 KSP preconditioned resid norm            inf true resid norm 2.709083260443e+06 ||r(i)||/||b|| 1.000000000000e+00
Linear solve did not converge due to DIVERGED_NANORINF iterations 0
KSP Object: 12 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=1000
  tolerances:  relative=1e-10, absolute=1e-50, divergence=10000
  left preconditioning
  using nonzero initial guess
  using PRECONDITIONED norm type for convergence test
PC Object: 12 MPI processes
  type: bjacobi
    block Jacobi: number of blocks = 12
    Local solve is same for all blocks, in the following KSP and PC objects:
  KSP Object:  (sub_)   1 MPI processes
    type: preonly
    maximum iterations=10000, initial guess is zero
    tolerances:  relative=1e-05, absolute=1e-50, divergence=10000
    left preconditioning
    using NONE norm type for convergence test
  PC Object:  (sub_)   1 MPI processes
    type: ilu
      ILU: out-of-place factorization
      0 levels of fill
      tolerance for zero pivot 2.22045e-14
      using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
      matrix ordering: natural
      factor fill ratio given 1, needed 1
        Factored matrix follows:
          Mat Object:           1 MPI processes
            type: seqaij
            rows=667070, cols=667070
            package used to perform factorization: petsc
            total: nonzeros=4.6765e+07, allocated nonzeros=4.6765e+07
            total number of mallocs used during MatSetValues calls =0
              using I-node routines: found 133414 nodes, limit used is 5
    linear system matrix = precond matrix:
    Mat Object:    ()     1 MPI processes
      type: seqaij
      rows=667070, cols=667070
      total: nonzeros=4.6765e+07, allocated nonzeros=5.473e+07
      total number of mallocs used during MatSetValues calls =0
        using I-node routines: found 133414 nodes, limit used is 5
  linear system matrix = precond matrix:
  Mat Object:  ()   12 MPI processes
    type: mpiaij
    rows=6723030, cols=6723030
    total: nonzeros=4.98852e+08, allocated nonzeros=5.38983e+08
    total number of mallocs used during MatSetValues calls =0
      using I-node (on process 0) routines: found 133414 nodes, limit used is 5


  Anything jumps out at you as odd? 

-Manav



> On Mar 26, 2015, at 9:34 AM, Matthew Knepley <knepley at gmail.com> wrote:
> 
> On Thu, Mar 26, 2015 at 9:21 AM, Manav Bhatia <bhatiamanav at gmail.com <mailto:bhatiamanav at gmail.com>> wrote:
> Hi,
> 
>   I am using the KSP linear solver for my system of equations, without any command line options at this point. I have checked that the L1 norms of my system matrix and the force vector are finite values, but the KSP solver is returning with an “inf” residual in the very first iteration.
> 
>   The problem has 6.7M dofs and I have tried this on multiple machines with different number of nodes with the same result.
> 
>    Is there a reason why the solver would return after the first iteration with an inf?
> 
>    I am not sure on where to start debugging this case, so I would appreciate any pointers.
> 
> For all solver questions, we want to see the output of
> 
>   -ksp_view -ksp_monitor_true_residual -ksp_converged_reason
> 
> The problem here would be that there is an error, so we would never see the output
> of -ksp_view and know what solver you are using. If you are using something complex,
> can you try using
> 
>   -pc_type jacobi
> 
> and send the output from the options above? Then we can figure out why the other solver
> gets an inf.
> 
>   Thanks,
> 
>      Matt
>  
> Thanks,
> Manav
> 
> 
> 
> 
> 
> -- 
> 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

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