  0 KSP Residual norm 0.000510152 
  1 KSP Residual norm 0.00357106 
  2 KSP Residual norm 0.00349891 
  3 KSP Residual norm 0.00342676 
  4 KSP Residual norm 0.00335461 
  5 KSP Residual norm 0.00328246 
  6 KSP Residual norm 0.00321031 
  7 KSP Residual norm 0.00313816 
  8 KSP Residual norm 0.00306601 
  9 KSP Residual norm 0.00299386 
 10 KSP Residual norm 0.00292171 
 11 KSP Residual norm 0.00284955 
 12 KSP Residual norm 0.0027774 
 13 KSP Residual norm 0.00270525 
 14 KSP Residual norm 0.0026331 
 15 KSP Residual norm 0.00256094 
 16 KSP Residual norm 0.00248879 
 17 KSP Residual norm 0.00241663 
 18 KSP Residual norm 0.00234448 
 19 KSP Residual norm 0.00227233 
 20 KSP Residual norm 0.00220017 
 21 KSP Residual norm 0.00212801 
 22 KSP Residual norm 0.00205586 
 23 KSP Residual norm 0.0019837 
 24 KSP Residual norm 0.00191154 
 25 KSP Residual norm 0.00183938 
 26 KSP Residual norm 0.00176722 
 27 KSP Residual norm 0.00169506 
 28 KSP Residual norm 0.00162289 
 29 KSP Residual norm 0.00155073 
 30 KSP Residual norm 0.00147856 
 31 KSP Residual norm 0.00140639 
 32 KSP Residual norm 0.00133422 
 33 KSP Residual norm 0.00126205 
 34 KSP Residual norm 0.00118987 
 35 KSP Residual norm 0.00111769 
 36 KSP Residual norm 0.0010455 
 37 KSP Residual norm 0.000973308 
 38 KSP Residual norm 0.000901108 
 39 KSP Residual norm 0.000828899 
 40 KSP Residual norm 0.000756678 
 41 KSP Residual norm 0.000684441 
 42 KSP Residual norm 0.000612182 
 43 KSP Residual norm 0.000539894 
 44 KSP Residual norm 0.000467562 
 45 KSP Residual norm 0.000395162 
 46 KSP Residual norm 0.000322648 
 47 KSP Residual norm 0.000249922 
 48 KSP Residual norm 0.000176722 
 49 KSP Residual norm 0.00010203 
 50 KSP Residual norm < 1.e-11
KSP Object: 1 MPI processes
  type: python
    Python: example1.ConjGrad
  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: 1 MPI processes
  type: python
    Python: example1.Jacobi
  linear system matrix = precond matrix:
  Matrix Object:   1 MPI processes  
    type: python
    rows=100, cols=100
        Python: example1.Laplace1D
 error norm =   6.83138198246195374E-013
