  0 KSP Residual norm 0.0443241 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 2.33385 
      1 KSP Residual norm 0.149578 
      2 KSP Residual norm 1.22679 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 1.23503 
      1 KSP Residual norm 0.0794808 
      2 KSP Residual norm 0.648684 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 1.78001 
    1 KSP Residual norm 0.105963 
    2 KSP Residual norm 0.937442 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.340912 
      1 KSP Residual norm 0.0213783 
      2 KSP Residual norm 0.17921 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.179876 
      1 KSP Residual norm 0.0100323 
      2 KSP Residual norm 0.0948167 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.874599 
    1 KSP Residual norm 0.0478285 
    2 KSP Residual norm 0.461302 
  1 KSP Residual norm 0.0185809 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.114582 
      1 KSP Residual norm 0.012349 
      2 KSP Residual norm 0.0594869 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0591948 
      1 KSP Residual norm 0.00584115 
      2 KSP Residual norm 0.0309345 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.993391 
    1 KSP Residual norm 0.0537321 
    2 KSP Residual norm 0.523741 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0192774 
      1 KSP Residual norm 0.00266358 
      2 KSP Residual norm 0.00984219 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.00893108 
      1 KSP Residual norm 0.00111185 
      2 KSP Residual norm 0.0046294 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.523143 
    1 KSP Residual norm 0.0273265 
    2 KSP Residual norm 0.276048 
  2 KSP Residual norm 0.000795661 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.998379 
      1 KSP Residual norm 0.0737639 
      2 KSP Residual norm 0.523585 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.518305 
      1 KSP Residual norm 0.0343328 
      2 KSP Residual norm 0.273078 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.401463 
    1 KSP Residual norm 0.0509673 
    2 KSP Residual norm 0.203322 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.149823 
      1 KSP Residual norm 0.0151393 
      2 KSP Residual norm 0.0784378 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0721186 
      1 KSP Residual norm 0.00488792 
      2 KSP Residual norm 0.0379712 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.12669 
    1 KSP Residual norm 0.0190126 
    2 KSP Residual norm 0.0636628 
  3 KSP Residual norm 3.98257e-05 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.47043 
      1 KSP Residual norm 0.092957 
      2 KSP Residual norm 0.234014 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.239915 
      1 KSP Residual norm 0.0468276 
      2 KSP Residual norm 0.11874 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 1.16151 
    1 KSP Residual norm 0.191695 
    2 KSP Residual norm 0.560581 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.133266 
      1 KSP Residual norm 0.0357375 
      2 KSP Residual norm 0.0628862 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0524995 
      1 KSP Residual norm 0.00991596 
      2 KSP Residual norm 0.0264384 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.485175 
    1 KSP Residual norm 0.0798161 
    2 KSP Residual norm 0.23725 
  4 KSP Residual norm 2.40449e-06 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.635269 
      1 KSP Residual norm 0.140149 
      2 KSP Residual norm 0.312191 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.358238 
      1 KSP Residual norm 0.0742635 
      2 KSP Residual norm 0.174384 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.838294 
    1 KSP Residual norm 0.107736 
    2 KSP Residual norm 0.433668 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.201841 
      1 KSP Residual norm 0.042807 
      2 KSP Residual norm 0.0951668 
      Residual norms for mg_levels_1_ solve.
      0 KSP Residual norm 0.0819979 
      1 KSP Residual norm 0.0177626 
      2 KSP Residual norm 0.0403337 
    Residual norms for mg_levels_2_ solve.
    0 KSP Residual norm 0.412919 
    1 KSP Residual norm 0.054804 
    2 KSP Residual norm 0.212956 
  5 KSP Residual norm 1.35943e-07 
KSP Object: 2 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: 2 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_) 2 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_) 2 MPI processes
      type: redundant
        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
            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=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
        eigenvalue estimates used:  min = 0.141423, max = 1.55565
        eigenvalues estimate via gmres min 0.0186576, max 1.41423
        eigenvalues estimated using gmres with translations  [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_1_esteig_) 2 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_) 2 MPI processes
      type: 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
        eigenvalue estimates used:  min = 0.141422, max = 1.55565
        eigenvalues estimate via gmres min 0.00388229, max 1.41422
        eigenvalues estimated using gmres with translations  [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_2_esteig_) 2 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_) 2 MPI processes
      type: 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 6.6474e-08
