  0 KSP Residual norm 4.83627 
  1 KSP Residual norm 0.0513333 
  2 KSP Residual norm 0.00128508 
  3 KSP Residual norm 2.53427e-05 
KSP Object: 1 MPI processes
  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 processes
  type: gamg
    type is MULTIPLICATIVE, levels=2 cycles=v
      Cycles per PCApply=1
      Using externally compute Galerkin coarse grid matrices
      GAMG specific options
        Threshold for dropping small values in graph on each level =  
        Threshold scaling factor for each level not specified = 1.
        AGG specific options
          Symmetric graph false
          Number of levels to square graph 1
          Number smoothing steps 1
        Complexity:    grid = 1.3
  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: bjacobi
        number of blocks = 1
        Local solver is the same for all blocks, as in the following KSP and PC objects on rank 0:
        KSP Object: (mg_coarse_sub_) 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_sub_) 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 1.06667
              Factored matrix follows:
                Mat Object: 1 MPI processes
                  type: seqaij
                  rows=6, cols=6
                  package used to perform factorization: petsc
                  total: nonzeros=32, allocated nonzeros=32
                    using I-node routines: found 3 nodes, limit used is 5
          linear system matrix = precond matrix:
          Mat Object: 1 MPI processes
            type: seqaijcusparse
            rows=6, cols=6
            total: nonzeros=30, allocated nonzeros=30
            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: seqaijcusparse
        rows=6, cols=6
        total: nonzeros=30, allocated nonzeros=30
        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 estimates used:  min = 0.0999687, max = 1.09966
        eigenvalues estimate via gmres min 0.413331, max 0.999687
        eigenvalues estimated using gmres with translations  [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 NONE 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: seqaijcusparse
        rows=24, cols=24
        total: nonzeros=100, allocated nonzeros=120
        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: seqaijcusparse
    rows=24, cols=24
    total: nonzeros=100, allocated nonzeros=120
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
Norm of error 2.70373e-05 iterations 3
