  0 KSP Residual norm 0.0443241 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.149561 
      1 KSP Residual norm 1.2268 
      2 KSP Residual norm 0.15327 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0210069 
      1 KSP Residual norm 0.0847678 
      2 KSP Residual norm 0.0214209 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0939908 
    1 KSP Residual norm 0.873169 
    2 KSP Residual norm 0.0980441 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0038076 
      1 KSP Residual norm 0.00685996 
      2 KSP Residual norm 0.00260573 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.000538844 
      1 KSP Residual norm 0.00135852 
      2 KSP Residual norm 0.000505156 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0108329 
    1 KSP Residual norm 0.052835 
    2 KSP Residual norm 0.0110949 
  1 KSP Residual norm 0.000491767 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.050083 
      1 KSP Residual norm 0.152054 
      2 KSP Residual norm 0.0512354 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00996495 
      1 KSP Residual norm 0.028754 
      2 KSP Residual norm 0.0101831 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.144253 
    1 KSP Residual norm 0.448802 
    2 KSP Residual norm 0.148289 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00711105 
      1 KSP Residual norm 0.0154823 
      2 KSP Residual norm 0.00714874 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00157816 
      1 KSP Residual norm 0.00384401 
      2 KSP Residual norm 0.00150827 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0297913 
    1 KSP Residual norm 0.0852035 
    2 KSP Residual norm 0.0304236 
  2 KSP Residual norm 5.73397e-06 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.026582 
      1 KSP Residual norm 0.115623 
      2 KSP Residual norm 0.0243272 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00462221 
      1 KSP Residual norm 0.0116701 
      2 KSP Residual norm 0.00436434 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0760263 
    1 KSP Residual norm 0.523384 
    2 KSP Residual norm 0.078089 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00388263 
      1 KSP Residual norm 0.00863398 
      2 KSP Residual norm 0.0035181 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.000680082 
      1 KSP Residual norm 0.0017475 
      2 KSP Residual norm 0.000644399 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0130749 
    1 KSP Residual norm 0.0444045 
    2 KSP Residual norm 0.0132856 
  3 KSP Residual norm 1.40227e-08 
KSP Object: 2 MPI processes
  type: fgmres
    GMRES: restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
    GMRES: happy breakdown tolerance 1e-30
  maximum iterations=10000, initial guess is zero
  tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
  right preconditioning
  using UNPRECONDITIONED norm type for convergence test
PC Object: 2 MPI processes
  type: mg
    MG: type is FULL, levels=3 cycles=v
      Not using Galerkin computed coarse grid matrices
  Coarse grid solver -- level -------------------------------
    KSP Object:    (mg_coarse_)     2 MPI processes
      type: preonly
      maximum iterations=1, initial guess is zero
      tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object:    (mg_coarse_)     2 MPI processes
      type: redundant
        Redundant preconditioner: First (color=0) of 2 PCs follows
        KSP Object:        (mg_coarse_redundant_)         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:        (mg_coarse_redundant_)         1 MPI processes
          type: lu
            LU: out-of-place factorization
            tolerance for zero pivot 2.22045e-14
            using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
            matrix ordering: nd
            factor fill ratio given 5., needed 1.60209
              Factored matrix follows:
                Mat Object:                 1 MPI processes
                  type: seqaij
                  rows=128, cols=128
                  package used to perform factorization: petsc
                  total: nonzeros=612, allocated nonzeros=612
                  total number of mallocs used during MatSetValues calls =0
                    not using I-node routines
          linear system matrix = precond matrix:
          Mat Object:           1 MPI processes
            type: seqaij
            rows=128, cols=128
            total: nonzeros=382, allocated nonzeros=382
            total number of mallocs used during MatSetValues calls =0
              not using I-node routines
      linear system matrix = precond matrix:
      Mat Object:       2 MPI processes
        type: mpiaij
        rows=128, cols=128
        total: nonzeros=382, allocated nonzeros=768
        total number of mallocs used during MatSetValues calls =0
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object:    (mg_levels_1_)     2 MPI processes
      type: chebyshev
        Chebyshev: eigenvalue estimates:  min = 0.141424, max = 1.55567
        Chebyshev: eigenvalues estimated using gmres with translations  [0. 0.1; 0. 1.1]
        KSP Object:        (mg_levels_1_esteig_)         2 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=10, initial guess is zero
          tolerances:  relative=1e-12, absolute=1e-50, divergence=10000.
          left preconditioning
          using PRECONDITIONED norm type for convergence test
      maximum iterations=2
      tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using nonzero initial guess
      using UNPRECONDITIONED norm type for convergence test
    PC Object:    (mg_levels_1_)     2 MPI processes
      type: sor
        SOR: type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
      linear system matrix = precond matrix:
      Mat Object:       2 MPI processes
        type: mpiaij
        rows=255, cols=255
        total: nonzeros=763, allocated nonzeros=1530
        total number of mallocs used during MatSetValues calls =0
  Up solver (post-smoother) same as down solver (pre-smoother)
  Down solver (pre-smoother) on level 2 -------------------------------
    KSP Object:    (mg_levels_2_)     2 MPI processes
      type: chebyshev
        Chebyshev: eigenvalue estimates:  min = 0.141422, max = 1.55564
        Chebyshev: eigenvalues estimated using gmres with translations  [0. 0.1; 0. 1.1]
        KSP Object:        (mg_levels_2_esteig_)         2 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=10, initial guess is zero
          tolerances:  relative=1e-12, absolute=1e-50, divergence=10000.
          left preconditioning
          using PRECONDITIONED norm type for convergence test
      maximum iterations=2
      tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using nonzero initial guess
      using UNPRECONDITIONED norm type for convergence test
    PC Object:    (mg_levels_2_)     2 MPI processes
      type: sor
        SOR: type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
      linear system matrix = precond matrix:
      Mat Object:       2 MPI processes
        type: mpiaij
        rows=509, cols=509
        total: nonzeros=1525, allocated nonzeros=3054
        total number of mallocs used during MatSetValues calls =0
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix = precond matrix:
  Mat Object:   2 MPI processes
    type: mpiaij
    rows=509, cols=509
    total: nonzeros=1525, allocated nonzeros=3054
    total number of mallocs used during MatSetValues calls =0
Residual norm 1.0832e-08
