  0 KSP Residual norm 0.330719 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 1.1281 
      1 KSP Residual norm 0.64913 
      2 KSP Residual norm 0.352833 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.118031 
      1 KSP Residual norm 0.0666702 
      2 KSP Residual norm 0.0346549 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.556889 
    1 KSP Residual norm 0.384109 
    2 KSP Residual norm 0.377659 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.203053 
      1 KSP Residual norm 0.128639 
      2 KSP Residual norm 0.0906259 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0178338 
      1 KSP Residual norm 0.0118861 
      2 KSP Residual norm 0.0082036 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.293203 
    1 KSP Residual norm 0.216583 
    2 KSP Residual norm 0.188302 
  1 KSP Residual norm 0.0620572 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.36702 
      1 KSP Residual norm 0.222218 
      2 KSP Residual norm 0.143576 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0357556 
      1 KSP Residual norm 0.0184688 
      2 KSP Residual norm 0.00932426 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.570664 
    1 KSP Residual norm 0.378932 
    2 KSP Residual norm 0.372543 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0855957 
      1 KSP Residual norm 0.0481863 
      2 KSP Residual norm 0.032215 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0109691 
      1 KSP Residual norm 0.00669965 
      2 KSP Residual norm 0.00419864 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.1993 
    1 KSP Residual norm 0.126333 
    2 KSP Residual norm 0.129984 
  2 KSP Residual norm 0.00283284 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.443707 
      1 KSP Residual norm 0.267535 
      2 KSP Residual norm 0.172158 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0444566 
      1 KSP Residual norm 0.0225488 
      2 KSP Residual norm 0.0107175 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.320737 
    1 KSP Residual norm 0.206797 
    2 KSP Residual norm 0.212357 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0368695 
      1 KSP Residual norm 0.0166853 
      2 KSP Residual norm 0.00386126 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00297974 
      1 KSP Residual norm 0.00176037 
      2 KSP Residual norm 0.00102794 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0879867 
    1 KSP Residual norm 0.0623195 
    2 KSP Residual norm 0.0566098 
  3 KSP Residual norm 7.15764e-05 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.563547 
      1 KSP Residual norm 0.335207 
      2 KSP Residual norm 0.211241 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0623025 
      1 KSP Residual norm 0.0303212 
      2 KSP Residual norm 0.0113468 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.409594 
    1 KSP Residual norm 0.209216 
    2 KSP Residual norm 0.274074 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0604752 
      1 KSP Residual norm 0.0385541 
      2 KSP Residual norm 0.0233435 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00375382 
      1 KSP Residual norm 0.00220197 
      2 KSP Residual norm 0.00137675 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0985052 
    1 KSP Residual norm 0.0471054 
    2 KSP Residual norm 0.0640324 
  4 KSP Residual norm 9.2352e-07 
KSP Object: 1 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: 1 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_)     1 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_)     1 MPI processes
      type: lu
        LU: out-of-place factorization
        tolerance for zero pivot 2.22045e-14
        matrix ordering: nd
        factor fill ratio given 5, needed 1
          Factored matrix follows:
            Matrix Object:             1 MPI processes
              type: seqaij
              rows=3, cols=3
              package used to perform factorization: petsc
              total: nonzeros=7, allocated nonzeros=7
              total number of mallocs used during MatSetValues calls =0
                not using I-node routines
      linear system matrix = precond matrix:
      Matrix Object:       1 MPI processes
        type: seqaij
        rows=3, cols=3
        total: nonzeros=7, allocated nonzeros=9
        total number of mallocs used during MatSetValues calls =0
          not using I-node routines
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object:    (mg_levels_1_)     1 MPI processes
      type: chebyshev
        Chebyshev: eigenvalue estimates:  min = 0.69968, max = 7.69648
        Chebyshev: estimated using:  [0 0.1; 0 1.1]
        KSP Object:        (mg_levels_1_est_)         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=10
          tolerances:  relative=1e-05, absolute=1e-50, divergence=10000
          left preconditioning
          using nonzero initial guess
          using NONE norm type for convergence test
        PC Object:        (mg_levels_1_)         1 MPI processes
          type: sor
            SOR: type = local_symmetric, iterations = 1, local iterations = 1, omega = 1
          linear system matrix = precond matrix:
          Matrix Object:           1 MPI processes
            type: seqaij
            rows=5, cols=5
            total: nonzeros=13, allocated nonzeros=15
            total number of mallocs used during MatSetValues calls =0
              not using I-node routines
      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_)     1 MPI processes
      type: sor
        SOR: type = local_symmetric, iterations = 1, local iterations = 1, omega = 1
      linear system matrix = precond matrix:
      Matrix Object:       1 MPI processes
        type: seqaij
        rows=5, cols=5
        total: nonzeros=13, allocated nonzeros=15
        total number of mallocs used during MatSetValues calls =0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  Down solver (pre-smoother) on level 2 -------------------------------
    KSP Object:    (mg_levels_2_)     1 MPI processes
      type: chebyshev
        Chebyshev: eigenvalue estimates:  min = 0.263549, max = 2.89904
        Chebyshev: estimated using:  [0 0.1; 0 1.1]
        KSP Object:        (mg_levels_2_est_)         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=10
          tolerances:  relative=1e-05, absolute=1e-50, divergence=10000
          left preconditioning
          using nonzero initial guess
          using NONE norm type for convergence test
        PC Object:        (mg_levels_2_)         1 MPI processes
          type: sor
            SOR: type = local_symmetric, iterations = 1, local iterations = 1, omega = 1
          linear system matrix = precond matrix:
          Matrix Object:           1 MPI processes
            type: seqaij
            rows=9, cols=9
            total: nonzeros=25, allocated nonzeros=27
            total number of mallocs used during MatSetValues calls =0
              not using I-node routines
      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_)     1 MPI processes
      type: sor
        SOR: type = local_symmetric, iterations = 1, local iterations = 1, omega = 1
      linear system matrix = precond matrix:
      Matrix Object:       1 MPI processes
        type: seqaij
        rows=9, cols=9
        total: nonzeros=25, allocated nonzeros=27
        total number of mallocs used during MatSetValues calls =0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix = precond matrix:
  Matrix Object:   1 MPI processes
    type: seqaij
    rows=9, cols=9
    total: nonzeros=25, allocated nonzeros=27
    total number of mallocs used during MatSetValues calls =0
      not using I-node routines
Residual norm 5.57283e-07
