  0 KSP Residual norm 0.0443241 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 2.33385 
      1 KSP Residual norm 1.18269 
      2 KSP Residual norm 0.367737 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.372534 
      1 KSP Residual norm 0.190318 
      2 KSP Residual norm 0.0612006 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 1.65824 
    1 KSP Residual norm 0.864691 
    2 KSP Residual norm 0.214791 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0276895 
      1 KSP Residual norm 0.0154796 
      2 KSP Residual norm 0.00702236 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00783567 
      1 KSP Residual norm 0.00476578 
      2 KSP Residual norm 0.00137409 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.217797 
    1 KSP Residual norm 0.116558 
    2 KSP Residual norm 0.0312166 
  1 KSP Residual norm 0.00138323 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.26684 
      1 KSP Residual norm 0.173881 
      2 KSP Residual norm 0.061286 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0629698 
      1 KSP Residual norm 0.0351539 
      2 KSP Residual norm 0.0119135 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.982198 
    1 KSP Residual norm 0.561428 
    2 KSP Residual norm 0.152152 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0507925 
      1 KSP Residual norm 0.0331169 
      2 KSP Residual norm 0.00961403 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0100591 
      1 KSP Residual norm 0.00669029 
      2 KSP Residual norm 0.00249984 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.16365 
    1 KSP Residual norm 0.100099 
    2 KSP Residual norm 0.0346352 
  2 KSP Residual norm 3.36276e-05 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.574261 
      1 KSP Residual norm 0.370644 
      2 KSP Residual norm 0.103663 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.095791 
      1 KSP Residual norm 0.0584995 
      2 KSP Residual norm 0.0234572 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 1.13144 
    1 KSP Residual norm 0.657896 
    2 KSP Residual norm 0.198591 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.132276 
      1 KSP Residual norm 0.0940755 
      2 KSP Residual norm 0.0309249 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0234275 
      1 KSP Residual norm 0.0102593 
      2 KSP Residual norm 0.00680986 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.238703 
    1 KSP Residual norm 0.158193 
    2 KSP Residual norm 0.0604068 
  3 KSP Residual norm 1.97101e-06 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.495273 
      1 KSP Residual norm 0.234702 
      2 KSP Residual norm 0.146941 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.19482 
      1 KSP Residual norm 0.115058 
      2 KSP Residual norm 0.0323438 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.852783 
    1 KSP Residual norm 0.42757 
    2 KSP Residual norm 0.242289 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.100108 
      1 KSP Residual norm 0.0444515 
      2 KSP Residual norm 0.037141 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0466498 
      1 KSP Residual norm 0.0264831 
      2 KSP Residual norm 0.00780339 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.28356 
    1 KSP Residual norm 0.155117 
    2 KSP Residual norm 0.0560442 
  4 KSP Residual norm 1.01338e-07 
KSP Object: 1 MPI processes
  type: fgmres
    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
    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
    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=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_) 1 MPI processes
      type: 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
                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=384
        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
        eigenvalue targets used: min 0.099124, max 1.09036
        eigenvalues estimated via gmres: min 0.0171844, max 0.99124
        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_1_esteig_) 1 MPI processes
          type: gmres
            restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
            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
        estimating eigenvalues using noisy right hand side
      maximum iterations=2, nonzero initial guess
      tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using UNPRECONDITIONED norm type for convergence test
    PC Object: (mg_levels_1_) 1 MPI processes
      type: sor
        type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
      linear system matrix = precond matrix:
      Mat Object: 1 MPI processes
        type: seqaij
        rows=255, cols=255
        total: nonzeros=763, allocated nonzeros=765
        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
        eigenvalue targets used: min 0.0977779, max 1.07556
        eigenvalues estimated via gmres: min 0.00339269, max 0.977779
        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_2_esteig_) 1 MPI processes
          type: gmres
            restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
            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
        estimating eigenvalues using noisy right hand side
      maximum iterations=2, nonzero initial guess
      tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using UNPRECONDITIONED norm type for convergence test
    PC Object: (mg_levels_2_) 1 MPI processes
      type: sor
        type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
      linear system matrix = precond matrix:
      Mat Object: 1 MPI processes
        type: seqaij
        rows=509, cols=509
        total: nonzeros=1525, allocated nonzeros=1527
        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=509, cols=509
    total: nonzeros=1525, allocated nonzeros=1527
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
Residual norm 5.83374e-08
