  0 KSP Residual norm 0.330719 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.651879 
      1 KSP Residual norm 0.413055 
      2 KSP Residual norm 0.369178 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.191655 
      1 KSP Residual norm 0.121706 
      2 KSP Residual norm 0.10937 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.558197 
    1 KSP Residual norm 0.367254 
    2 KSP Residual norm 0.353611 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0977061 
      1 KSP Residual norm 0.108969 
      2 KSP Residual norm 0.0789894 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.045305 
      1 KSP Residual norm 0.0273163 
      2 KSP Residual norm 0.0186973 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.296523 
    1 KSP Residual norm 0.192713 
    2 KSP Residual norm 0.172326 
  1 KSP Residual norm 0.0569789 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.409063 
      1 KSP Residual norm 0.310935 
      2 KSP Residual norm 0.217965 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.098603 
      1 KSP Residual norm 0.0874804 
      2 KSP Residual norm 0.0634073 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.511448 
    1 KSP Residual norm 0.416168 
    2 KSP Residual norm 0.318275 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0719037 
      1 KSP Residual norm 0.0835094 
      2 KSP Residual norm 0.0636631 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0366907 
      1 KSP Residual norm 0.0268843 
      2 KSP Residual norm 0.019278 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.158325 
    1 KSP Residual norm 0.150297 
    2 KSP Residual norm 0.102857 
  2 KSP Residual norm 0.00302078 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.219321 
      1 KSP Residual norm 0.14485 
      2 KSP Residual norm 0.102583 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0514244 
      1 KSP Residual norm 0.0405491 
      2 KSP Residual norm 0.0294789 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.294401 
    1 KSP Residual norm 0.368014 
    2 KSP Residual norm 0.209174 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0411425 
      1 KSP Residual norm 0.0118984 
      2 KSP Residual norm 0.0127463 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00479704 
      1 KSP Residual norm 0.00420086 
      2 KSP Residual norm 0.00314146 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0680661 
    1 KSP Residual norm 0.0729321 
    2 KSP Residual norm 0.0464817 
  3 KSP Residual norm 5.61784e-05 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.23894 
      1 KSP Residual norm 0.153827 
      2 KSP Residual norm 0.108215 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0399185 
      1 KSP Residual norm 0.0403325 
      2 KSP Residual norm 0.0331161 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.354328 
    1 KSP Residual norm 0.393047 
    2 KSP Residual norm 0.295842 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0539213 
      1 KSP Residual norm 0.0402286 
      2 KSP Residual norm 0.0359138 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.020569 
      1 KSP Residual norm 0.015505 
      2 KSP Residual norm 0.0109089 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.0990827 
    1 KSP Residual norm 0.109913 
    2 KSP Residual norm 0.0832559 
  4 KSP Residual norm 3.39153e-06 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.1173 
      1 KSP Residual norm 0.0705127 
      2 KSP Residual norm 0.051899 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0196781 
      1 KSP Residual norm 0.0181471 
      2 KSP Residual norm 0.0162582 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.384923 
    1 KSP Residual norm 0.19674 
    2 KSP Residual norm 0.210803 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0412664 
      1 KSP Residual norm 0.0443127 
      2 KSP Residual norm 0.0330698 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0213951 
      1 KSP Residual norm 0.0144478 
      2 KSP Residual norm 0.0104518 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.11934 
    1 KSP Residual norm 0.065453 
    2 KSP Residual norm 0.0690902 
  5 KSP Residual norm 2.17336e-08 
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
        using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
        matrix ordering: nd
        factor fill ratio given 5, needed 1
          Factored matrix follows:
            Mat 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:
      Mat 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 = 0.255106, max = 2.80617
        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:
          Mat 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:
      Mat 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 = 0.111418, max = 1.2256
        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:
          Mat 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:
      Mat 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:
  Mat 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 1.04083e-08
