  0 KSP Residual norm 811.998
  1 KSP Residual norm 197.037
  2 KSP Residual norm 76.0612
  3 KSP Residual norm 28.3601
  4 KSP Residual norm 7.64702
  5 KSP Residual norm 4.00353
  6 KSP Residual norm 1.74934
  7 KSP Residual norm 0.751483
  8 KSP Residual norm 0.28333
  9 KSP Residual norm 0.0874762
 10 KSP Residual norm 0.0353676
 11 KSP Residual norm 0.017824
 12 KSP Residual norm 0.00703599
  Linear solve converged due to CONVERGED_RTOL iterations 12
KSP Object: 8 MPI processes
  type: cg
  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: 8 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 =   -0.01   -0.01  
        Threshold scaling factor for each level not specified = 1.
        Using parallel coarse grid solver (all coarse grid equations not put on one process)
        AGG specific options
          Number of levels of aggressive coarsening 1
          Square graph aggressive coarsening
          MatCoarsen Object: (pc_gamg_) 8 MPI processes
            type: mis
          Number smoothing steps to construct prolongation 1
        Complexity:    grid = 1.054    operator = 1.07125
        Per-level complexity: op = operator, int = interpolation
            #equations  | #active PEs | avg nnz/row op | avg nnz/row int
                162            4             87                0
               3000            8             66               19
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 8 MPI processes
      type: cg
      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: (mg_coarse_) 8 MPI processes
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 8 MPI processes
        type: mpiaij
        rows=162, cols=162, bs=6
        total: nonzeros=14076, allocated nonzeros=14076
        total number of mallocs used during MatSetValues calls=0
          using nonscalable MatPtAP() implementation
          using I-node (on process 0) routines: found 4 nodes, limit used is 5
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_) 8 MPI processes
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.637067, max 3.3446
        eigenvalues provided (min 0.0597913, max 3.18533) with transform: [0. 0.2; 0. 1.05]
      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_) 8 MPI processes
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 8 MPI processes
        type: mpiaij
        rows=3000, cols=3000, bs=3
        total: nonzeros=197568, allocated nonzeros=243000
        total number of mallocs used during MatSetValues calls=0
          has attached near null space
          using I-node (on process 0) routines: found 125 nodes, limit used is 5
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix, which is also used to construct the preconditioner:
  Mat Object: 8 MPI processes
    type: mpiaij
    rows=3000, cols=3000, bs=3
    total: nonzeros=197568, allocated nonzeros=243000
    total number of mallocs used during MatSetValues calls=0
      has attached near null space
      using I-node (on process 0) routines: found 125 nodes, limit used is 5
  0 KSP Residual norm 0.00811969
  1 KSP Residual norm 0.00196934
  2 KSP Residual norm 0.000759615
  3 KSP Residual norm 0.000282977
  4 KSP Residual norm 7.65127e-05
  5 KSP Residual norm 4.02809e-05
  6 KSP Residual norm 1.76022e-05
  7 KSP Residual norm 7.54699e-06
  8 KSP Residual norm 2.84038e-06
  9 KSP Residual norm 8.7449e-07
 10 KSP Residual norm 3.53116e-07
 11 KSP Residual norm 1.7785e-07
 12 KSP Residual norm 7.0347e-08
  Linear solve converged due to CONVERGED_RTOL iterations 12
KSP Object: 8 MPI processes
  type: cg
  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: 8 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 =   -0.01   -0.01  
        Threshold scaling factor for each level not specified = 1.
        Using parallel coarse grid solver (all coarse grid equations not put on one process)
        AGG specific options
          Number of levels of aggressive coarsening 1
          Square graph aggressive coarsening
          MatCoarsen Object: (pc_gamg_) 8 MPI processes
            type: mis
          Number smoothing steps to construct prolongation 1
        Complexity:    grid = 1.054    operator = 1.07125
        Per-level complexity: op = operator, int = interpolation
            #equations  | #active PEs | avg nnz/row op | avg nnz/row int
                162            4             87                0
               3000            8             66               19
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 8 MPI processes
      type: cg
      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: (mg_coarse_) 8 MPI processes
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 8 MPI processes
        type: mpiaij
        rows=162, cols=162, bs=6
        total: nonzeros=14076, allocated nonzeros=14076
        total number of mallocs used during MatSetValues calls=0
          using nonscalable MatPtAP() implementation
          using I-node (on process 0) routines: found 4 nodes, limit used is 5
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_) 8 MPI processes
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.637376, max 3.34622
        eigenvalues estimated via gmres: min 0.0806313, max 3.18688
        eigenvalues estimated using gmres with transform: [0. 0.2; 0. 1.05]
        KSP Object: (mg_levels_1_esteig_) 8 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 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_) 8 MPI processes
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 8 MPI processes
        type: mpiaij
        rows=3000, cols=3000, bs=3
        total: nonzeros=197568, allocated nonzeros=243000
        total number of mallocs used during MatSetValues calls=0
          has attached near null space
          using I-node (on process 0) routines: found 125 nodes, limit used is 5
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix, which is also used to construct the preconditioner:
  Mat Object: 8 MPI processes
    type: mpiaij
    rows=3000, cols=3000, bs=3
    total: nonzeros=197568, allocated nonzeros=243000
    total number of mallocs used during MatSetValues calls=0
      has attached near null space
      using I-node (on process 0) routines: found 125 nodes, limit used is 5
  0 KSP Residual norm 0.00811969
  1 KSP Residual norm 0.00196934
  2 KSP Residual norm 0.000759615
  3 KSP Residual norm 0.000282977
  4 KSP Residual norm 7.65127e-05
  5 KSP Residual norm 4.02809e-05
  6 KSP Residual norm 1.76022e-05
  7 KSP Residual norm 7.54699e-06
  8 KSP Residual norm 2.84038e-06
  9 KSP Residual norm 8.7449e-07
 10 KSP Residual norm 3.53116e-07
 11 KSP Residual norm 1.7785e-07
 12 KSP Residual norm 7.0347e-08
  Linear solve converged due to CONVERGED_RTOL iterations 12
KSP Object: 8 MPI processes
  type: cg
  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: 8 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 =   -0.01   -0.01  
        Threshold scaling factor for each level not specified = 1.
        Using parallel coarse grid solver (all coarse grid equations not put on one process)
        AGG specific options
          Number of levels of aggressive coarsening 1
          Square graph aggressive coarsening
          MatCoarsen Object: (pc_gamg_) 8 MPI processes
            type: mis
          Number smoothing steps to construct prolongation 1
        Complexity:    grid = 1.054    operator = 1.07125
        Per-level complexity: op = operator, int = interpolation
            #equations  | #active PEs | avg nnz/row op | avg nnz/row int
                162            4             87                0
               3000            8             66               19
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 8 MPI processes
      type: cg
      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: (mg_coarse_) 8 MPI processes
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 8 MPI processes
        type: mpiaij
        rows=162, cols=162, bs=6
        total: nonzeros=14076, allocated nonzeros=14076
        total number of mallocs used during MatSetValues calls=0
          using nonscalable MatPtAP() implementation
          using I-node (on process 0) routines: found 4 nodes, limit used is 5
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_) 8 MPI processes
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.637376, max 3.34622
        eigenvalues estimated via gmres: min 0.0806313, max 3.18688
        eigenvalues estimated using gmres with transform: [0. 0.2; 0. 1.05]
        KSP Object: (mg_levels_1_esteig_) 8 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 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_) 8 MPI processes
      type: jacobi
        type DIAGONAL
      linear system matrix, which is also used to construct the preconditioner:
      Mat Object: 8 MPI processes
        type: mpiaij
        rows=3000, cols=3000, bs=3
        total: nonzeros=197568, allocated nonzeros=243000
        total number of mallocs used during MatSetValues calls=0
          has attached near null space
          using I-node (on process 0) routines: found 125 nodes, limit used is 5
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix, which is also used to construct the preconditioner:
  Mat Object: 8 MPI processes
    type: mpiaij
    rows=3000, cols=3000, bs=3
    total: nonzeros=197568, allocated nonzeros=243000
    total number of mallocs used during MatSetValues calls=0
      has attached near null space
      using I-node (on process 0) routines: found 125 nodes, limit used is 5
[0]main |b-Ax|/|b|=2.425235e-04, |b|=5.391826e+00, emax=9.946388e-01
