KSP Object: 1 MPI process
  type: gmres
    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.
  left preconditioning
  using PRECONDITIONED norm type for convergence test
PC Object: 1 MPI process
  type: mg
    type is MULTIPLICATIVE, levels=3 cycles=v
      Cycles per PCApply=1
      Not using Galerkin computed coarse grid matrices
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 1 MPI process
      type: preonly
      maximum iterations=10000, initial guess is zero
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      not checking for convergence
    PC Object: (mg_coarse_) 1 MPI process
      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 1.54545
          Factored matrix:
            Mat Object: (mg_coarse_) 1 MPI process
              type: seqaij
              rows=9, cols=9
              package used to perform factorization: petsc
              total: nonzeros=51, allocated nonzeros=51
                not using I-node routines
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 1 MPI process
        type: seqaij
        rows=9, cols=9
        total: nonzeros=33, allocated nonzeros=33
        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 process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.1, max 1.1
        eigenvalues estimated via gmres: min 0.642839, max 1.
        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_1_esteig_) 1 MPI process
          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 a noisy random number generated right-hand side
      maximum iterations=2, initial guess is zero
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      not checking for convergence
    PC Object: (mg_levels_1_) 1 MPI process
      type: sor
        type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 1 MPI process
        type: seqaij
        rows=25, cols=25
        total: nonzeros=105, allocated nonzeros=105
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_up_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.170711, max 1.87782
        eigenvalues estimated via gmres: min 0.292893, max 1.70711
        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_1_up_esteig_) 1 MPI process
          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 a noisy random number generated right-hand side
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      not checking for convergence
    PC Object: (mg_levels_1_up_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 1 MPI process
        type: seqaij
        rows=25, cols=25
        total: nonzeros=105, allocated nonzeros=105
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Down solver (pre-smoother) on level 2 -------------------------------
    KSP Object: (mg_levels_2_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.100018, max 1.1002
        eigenvalues estimated via gmres: min 0.250619, max 1.00018
        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_2_esteig_) 1 MPI process
          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 a noisy random number generated right-hand side
      maximum iterations=2, initial guess is zero
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      not checking for convergence
    PC Object: (mg_levels_2_) 1 MPI process
      type: sor
        type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 1 MPI process
        type: seqaij
        rows=81, cols=81
        total: nonzeros=369, allocated nonzeros=369
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) on level 2 -------------------------------
    KSP Object: (mg_levels_2_up_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.192344, max 2.11578
        eigenvalues estimated via gmres: min 0.0875558, max 1.92344
        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
        KSP Object: (mg_levels_2_up_esteig_) 1 MPI process
          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 a noisy random number generated right-hand side
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      not checking for convergence
    PC Object: (mg_levels_2_up_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 1 MPI process
        type: seqaij
        rows=81, cols=81
        total: nonzeros=369, allocated nonzeros=369
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  linear system matrix, which is also used to construct the preconditioner:
  Mat Object: 1 MPI process
    type: seqaij
    rows=81, cols=81
    total: nonzeros=369, allocated nonzeros=369
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
