    0 KSP Residual norm 2.299206212228e+01
    1 KSP Residual norm 6.707681604902e+00
    2 KSP Residual norm 6.151688050939e+00
    3 KSP Residual norm 3.600696700911e-01
    4 KSP Residual norm 1.030497427936e-01
    5 KSP Residual norm 1.136054664899e-13
  Linear solve converged due to CONVERGED_RTOL iterations 5
KSP Object: 3 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: 3 MPI processes
  type: bjacobi
    number of blocks = 3
    Local solver information for first block is in the following KSP and PC objects on rank 0:
    Use -ksp_view ::ascii_info_detail to display information for all blocks
    KSP Object: (sub_) 1 MPI process
      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: (sub_) 1 MPI process
      type: ilu
        out-of-place factorization
        0 levels of fill
        tolerance for zero pivot 2.22045e-14
        matrix ordering: natural
        factor fill ratio given 1., needed 1.
          Factored matrix follows:
            Mat Object: (sub_) 1 MPI process
              type: seqaij
              rows=7, cols=7
              package used to perform factorization: petsc
              total: nonzeros=18, allocated nonzeros=18
                not using I-node routines
      linear system matrix = precond matrix:
      Mat Object: (sub_) 1 MPI process
        type: seqaij
        rows=7, cols=7
        total: nonzeros=18, allocated nonzeros=18
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  linear system matrix = precond matrix:
  Mat Object: (mpi_linear_solver_server_) 3 MPI processes
    type: mpiaij
    rows=20, cols=20
    total: nonzeros=56, allocated nonzeros=56
    total number of mallocs used during MatSetValues calls=0
      not using I-node (on process 0) routines
KSP Object: (mpi_linear_solver_server_) 1 MPI process
  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: (mpi_linear_solver_server_) 1 MPI process
  type: mpi
  Size of MPI communicator used for MPI parallel KSP solve 3
  Desired minimum number of matrix rows on each MPI process for MPI parallel solve 5
  *** Use -mpi_linear_solver_server_view to view statistics on all the solves ***
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=20, cols=20
    total: nonzeros=56, allocated nonzeros=0
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
    0 KSP Residual norm 2.499789933653e+00
    1 KSP Residual norm 1.913386996165e-01
    2 KSP Residual norm 1.154213781039e-04
    3 KSP Residual norm 1.670802013848e-08
  Linear solve converged due to CONVERGED_RTOL iterations 3
KSP Object: 3 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: 3 MPI processes
  type: bjacobi
    number of blocks = 3
    Local solver information for first block is in the following KSP and PC objects on rank 0:
    Use -ksp_view ::ascii_info_detail to display information for all blocks
    KSP Object: (sub_) 1 MPI process
      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: (sub_) 1 MPI process
      type: ilu
        out-of-place factorization
        0 levels of fill
        tolerance for zero pivot 2.22045e-14
        matrix ordering: natural
        factor fill ratio given 1., needed 1.
          Factored matrix follows:
            Mat Object: (sub_) 1 MPI process
              type: seqaij
              rows=7, cols=7
              package used to perform factorization: petsc
              total: nonzeros=18, allocated nonzeros=18
                not using I-node routines
      linear system matrix = precond matrix:
      Mat Object: (sub_) 1 MPI process
        type: seqaij
        rows=7, cols=7
        total: nonzeros=18, allocated nonzeros=18
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  linear system matrix = precond matrix:
  Mat Object: (mpi_linear_solver_server_) 3 MPI processes
    type: mpiaij
    rows=20, cols=20
    total: nonzeros=56, allocated nonzeros=56
    total number of mallocs used during MatSetValues calls=0
      not using I-node (on process 0) routines
KSP Object: (mpi_linear_solver_server_) 1 MPI process
  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: (mpi_linear_solver_server_) 1 MPI process
  type: mpi
  Size of MPI communicator used for MPI parallel KSP solve 3
  Desired minimum number of matrix rows on each MPI process for MPI parallel solve 5
  *** Use -mpi_linear_solver_server_view to view statistics on all the solves ***
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=20, cols=20
    total: nonzeros=56, allocated nonzeros=0
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
MPI linear solver server statistics:
    Ranks        KSPSolve()s     Mats        KSPs       Avg. Size      Avg. Its
     3               2            2           1            20            4
