lid velocity = 0.000106281, prandtl # = 1., grashof # = 1.
  0 SNES Function norm 1.036007954337e-02 
    0 KSP Residual norm 3.529801578944e+00 
    1 KSP Residual norm 9.549227287830e-01 
    2 KSP Residual norm 1.833989370926e-01 
    3 KSP Residual norm 3.207579266155e-02 
    4 KSP Residual norm 1.205175868015e-02 
    5 KSP Residual norm 3.633439929268e-03 
    6 KSP Residual norm 7.859510138803e-04 
    7 KSP Residual norm 1.906870003210e-04 
    8 KSP Residual norm 3.576753906100e-05 
    9 KSP Residual norm 7.330444204410e-06 
  1 SNES Function norm 3.201130805934e-06 
    0 KSP Residual norm 4.432732267457e-05 
    1 KSP Residual norm 1.369208870977e-05 
    2 KSP Residual norm 4.651992306344e-06 
    3 KSP Residual norm 1.540951999530e-06 
    4 KSP Residual norm 5.756704829591e-07 
    5 KSP Residual norm 1.031576233748e-07 
    6 KSP Residual norm 3.860545812196e-08 
    7 KSP Residual norm 1.221937916520e-08 
    8 KSP Residual norm 2.613169031973e-09 
    9 KSP Residual norm 4.602224202132e-10 
   10 KSP Residual norm 1.025651362460e-10 
  2 SNES Function norm 4.213263970740e-11 
SNES Object: 4 MPI processes
  type: newtonls
  maximum iterations=50, maximum function evaluations=10000
  tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
  total number of linear solver iterations=19
  total number of function evaluations=3
  norm schedule ALWAYS
  Jacobian is built using colored finite differences on a DMDA
  SNESLineSearch Object: 4 MPI processes
    type: bt
      interpolation: cubic
      alpha=1.000000e-04
    maxstep=1.000000e+08, minlambda=1.000000e-12
    tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08
    maximum iterations=40
  KSP Object: 4 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: 4 MPI processes
    type: hypre
      HYPRE BoomerAMG preconditioning
        Cycle type V
        Maximum number of levels 25
        Maximum number of iterations PER hypre call 1
        Convergence tolerance PER hypre call 0.
        Threshold for strong coupling 0.25
        Interpolation truncation factor 0.
        Interpolation: max elements per row 0
        Number of levels of aggressive coarsening 0
        Number of paths for aggressive coarsening 1
        Maximum row sums 0.9
        Sweeps down         1
        Sweeps up           1
        Sweeps on coarse    1
        Relax down          symmetric-SOR/Jacobi
        Relax up            symmetric-SOR/Jacobi
        Relax on coarse     Gaussian-elimination
        Relax weight  (all)      1.
        Outer relax weight (all) 1.
        Using CF-relaxation
        Not using more complex smoothers.
        Measure type        local
        Coarsen type        Falgout
        Interpolation type  classical
    linear system matrix = precond matrix:
    Mat Object: 4 MPI processes
      type: mpiaij
      rows=37636, cols=37636, bs=4
      total: nonzeros=746512, allocated nonzeros=746512
      total number of mallocs used during MatSetValues calls=0
Number of SNES iterations = 2
