lid velocity = 0.0625, prandtl # = 1., grashof # = 1.
  0 SNES Function norm 0.239155
    0 KSP Residual norm 0.0802764
    1 KSP Residual norm 0.0249277
    2 KSP Residual norm 0.0117306
    3 KSP Residual norm 0.00526274
    4 KSP Residual norm 0.00463185
    5 KSP Residual norm 0.00306201
    6 KSP Residual norm 0.0020143
    7 KSP Residual norm 0.00156512
    8 KSP Residual norm 0.0012814
    9 KSP Residual norm 0.00109837
   10 KSP Residual norm 0.000748519
   11 KSP Residual norm 0.000592453
   12 KSP Residual norm 0.000448783
   13 KSP Residual norm 0.000378752
   14 KSP Residual norm 0.000264337
   15 KSP Residual norm 0.000173765
   16 KSP Residual norm 0.000111263
   17 KSP Residual norm 6.5666e-05
   18 KSP Residual norm 1.75064e-05
   19 KSP Residual norm 1.60451e-05
   20 KSP Residual norm 9.20169e-06
   21 KSP Residual norm 1.08239e-06
   22 KSP Residual norm 8.45334e-07
   23 KSP Residual norm 3.62484e-07
  1 SNES Function norm 6.83886e-05
    0 KSP Residual norm 1.34538e-05
    1 KSP Residual norm 3.5938e-06
    2 KSP Residual norm 1.43034e-06
    3 KSP Residual norm 3.96202e-07
    4 KSP Residual norm 3.10187e-07
    5 KSP Residual norm 2.18322e-07
    6 KSP Residual norm 1.90422e-07
    7 KSP Residual norm 1.33363e-07
    8 KSP Residual norm 9.79339e-08
    9 KSP Residual norm 8.35383e-08
   10 KSP Residual norm 7.09248e-08
   11 KSP Residual norm 5.69143e-08
   12 KSP Residual norm 3.19231e-08
   13 KSP Residual norm 2.0429e-08
   14 KSP Residual norm 1.73693e-08
   15 KSP Residual norm 8.73233e-09
   16 KSP Residual norm 5.44314e-09
   17 KSP Residual norm 4.75858e-09
   18 KSP Residual norm 3.18157e-09
   19 KSP Residual norm 8.028e-10
   20 KSP Residual norm 7.187e-10
   21 KSP Residual norm 2.688e-10
   22 KSP Residual norm 6.997e-11
  2 SNES Function norm 1.22235e-09
SNES Object: 2 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=45
  total number of function evaluations=3
  norm schedule ALWAYS
  Jacobian is built using colored finite differences on a DMDA
  SNESLineSearch Object: 2 MPI processes
    type: bt
      interpolation: cubic
      alpha=1.000000e-04
    maxlambda=1.000000e+00, minlambda=1.000000e-12
    tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08
    maximum iterations=40
  KSP Object: 2 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: 2 MPI processes
    type: kaczmarz
      lambda = 1.
    linear system matrix, which is also used to construct the preconditioner:
    Mat Object: 2 MPI processes
      type: mpiaij
      rows=64, cols=64, bs=4
      total: nonzeros=1024, allocated nonzeros=1024
      total number of mallocs used during MatSetValues calls=0
Number of SNES iterations = 2
