0 SNES Function norm 1.371870931195e-01 
    0 KSP Residual norm 7.514924505889e-02 
    1 KSP Residual norm 3.030336958028e-02 
    2 KSP Residual norm 1.888992084147e-02 
    3 KSP Residual norm 1.177522877288e-02 
    4 KSP Residual norm 7.340211418424e-03 
    5 KSP Residual norm 4.575597188502e-03 
    6 KSP Residual norm 2.852246132704e-03 
    7 KSP Residual norm 1.777977314517e-03 
    8 KSP Residual norm 1.108320665138e-03 
    9 KSP Residual norm 6.908832226053e-04 
   10 KSP Residual norm 4.306692478914e-04 
   11 KSP Residual norm 2.684621583078e-04 
   12 KSP Residual norm 1.673486806782e-04 
   13 KSP Residual norm 1.043185419549e-04 
   14 KSP Residual norm 6.502804893049e-05 
   15 KSP Residual norm 4.053591114739e-05 
   16 KSP Residual norm 2.526848213307e-05 
   17 KSP Residual norm 1.575137134545e-05 
   18 KSP Residual norm 9.818781276860e-06 
   19 KSP Residual norm 6.120639508031e-06 
   20 KSP Residual norm 3.815364344205e-06 
   21 KSP Residual norm 2.378347076300e-06 
   22 KSP Residual norm 1.482567405081e-06 
   23 KSP Residual norm 9.241738233563e-07 
   24 KSP Residual norm 5.760933720636e-07 
   25 KSP Residual norm 3.591137997868e-07 
   26 KSP Residual norm 2.238573249405e-07 
   27 KSP Residual norm 1.395437935198e-07 
   28 KSP Residual norm 8.698607613686e-08 
   29 KSP Residual norm 5.422367591300e-08 
   30 KSP Residual norm 3.380089279537e-08 
   31 KSP Residual norm 2.107013833451e-08 
   32 KSP Residual norm 1.313429004435e-08 
   33 KSP Residual norm 8.187396421781e-09 
   34 KSP Residual norm 5.103698777487e-09 
   35 KSP Residual norm 3.181443757243e-09 
   36 KSP Residual norm 1.983186062110e-09 
   37 KSP Residual norm 1.236239719261e-09 
   38 KSP Residual norm 7.706228924241e-10 
   39 KSP Residual norm 4.803757550281e-10 
   40 KSP Residual norm 2.994472469490e-10 
   41 KSP Residual norm 1.866635638486e-10 
   42 KSP Residual norm 1.163586319954e-10 
   43 KSP Residual norm 7.253341723844e-11 
  1 SNES Function norm 2.289561665259e-10 
Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 1
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=43
  total number of function evaluations=2
  norm schedule ALWAYS
  SNESLineSearch Object:   2 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:   2 MPI processes
    type: richardson
      Richardson: damping factor=1
    maximum iterations=10000, initial guess is zero
    tolerances:  relative=1e-09, absolute=1e-50, divergence=10000
    left preconditioning
    using PRECONDITIONED norm type for convergence test
  PC Object:   2 MPI processes
    type: asm
      Additive Schwarz: total subdomain blocks = 2, amount of overlap = 0
      Additive Schwarz: restriction/interpolation type - RESTRICT
      Local solve is same for all blocks, in the following KSP and PC objects:
    KSP Object:    (sub_)     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:    (sub_)     1 MPI processes
      type: lu
        LU: out-of-place factorization
        tolerance for zero pivot 2.22045e-14
        matrix ordering: nd
        factor fill ratio given 5, needed 1.875
          Factored matrix follows:
            Mat Object:             1 MPI processes
              type: seqaij
              rows=16, cols=16
              package used to perform factorization: petsc
              total: nonzeros=120, allocated nonzeros=120
              total number of mallocs used during MatSetValues calls =0
                using I-node routines: found 12 nodes, limit used is 5
      linear system matrix = precond matrix:
      Mat Object:       1 MPI processes
        type: seqaij
        rows=16, cols=16
        total: nonzeros=64, allocated nonzeros=64
        total number of mallocs used during MatSetValues calls =0
          not using I-node routines
    linear system matrix = precond matrix:
    Mat Object:     2 MPI processes
      type: mpiaij
      rows=32, cols=32
      total: nonzeros=136, allocated nonzeros=136
      total number of mallocs used during MatSetValues calls =0
N: 32 error l2 6.01814e-12 inf 8.12005e-11