1 0 SNES Function norm 0.137187 2 0 KSP Residual norm 0.0454401 3 1 KSP Residual norm 0.0301134 4 2 KSP Residual norm 0.0224377 5 3 KSP Residual norm 0.0154666 6 4 KSP Residual norm 0.0112611 7 5 KSP Residual norm 0.00790289 8 6 KSP Residual norm 0.00568847 9 7 KSP Residual norm 0.00402494 10 8 KSP Residual norm 0.00288147 11 9 KSP Residual norm 0.00204651 12 10 KSP Residual norm 0.0014614 13 11 KSP Residual norm 0.00103974 14 12 KSP Residual norm 0.000741601 15 13 KSP Residual norm 0.000528048 16 14 KSP Residual norm 0.000376428 17 15 KSP Residual norm 0.000268131 18 16 KSP Residual norm 0.000191093 19 17 KSP Residual norm 0.00013614 20 18 KSP Residual norm 9.70138e-05 21 19 KSP Residual norm 6.91206e-05 22 20 KSP Residual norm 4.92529e-05 23 21 KSP Residual norm 3.50932e-05 24 22 KSP Residual norm 2.50055e-05 25 23 KSP Residual norm 1.7817e-05 26 24 KSP Residual norm 1.26953e-05 27 25 KSP Residual norm 9.04572e-06 28 26 KSP Residual norm 6.44539e-06 29 27 KSP Residual norm 4.59253e-06 30 28 KSP Residual norm 3.27233e-06 31 29 KSP Residual norm 2.33164e-06 32 30 KSP Residual norm 1.66137e-06 33 31 KSP Residual norm 1.18377e-06 34 32 KSP Residual norm 8.43477e-07 35 33 KSP Residual norm 6.01004e-07 36 34 KSP Residual norm 4.28234e-07 37 35 KSP Residual norm 3.0513e-07 38 36 KSP Residual norm 2.17415e-07 39 37 KSP Residual norm 1.54915e-07 40 38 KSP Residual norm 1.10382e-07 41 39 KSP Residual norm 7.86506e-08 42 40 KSP Residual norm 5.6041e-08 43 41 KSP Residual norm 3.9931e-08 44 42 KSP Residual norm 2.84521e-08 45 43 KSP Residual norm 2.0273e-08 46 44 KSP Residual norm 1.44452e-08 47 45 KSP Residual norm 1.02926e-08 48 46 KSP Residual norm 7.33383e-09 49 47 KSP Residual norm 5.22558e-09 50 48 KSP Residual norm 3.72339e-09 51 49 KSP Residual norm 2.65303e-09 52 50 KSP Residual norm 1.89037e-09 53 51 KSP Residual norm 1.34695e-09 54 52 KSP Residual norm 9.597e-10 55 53 KSP Residual norm 6.838e-10 56 54 KSP Residual norm 4.873e-10 57 55 KSP Residual norm 3.472e-10 58 56 KSP Residual norm 2.474e-10 59 57 KSP Residual norm 1.763e-10 60 58 KSP Residual norm 1.256e-10 61 59 KSP Residual norm 8.949e-11 62 60 KSP Residual norm 6.377e-11 63 61 KSP Residual norm 4.544e-11 64 1 SNES Function norm 1.488e-10 65Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 1 66SNES Object: 2 MPI processes 67 type: newtonls 68 maximum iterations=50, maximum function evaluations=10000 69 tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 70 total number of linear solver iterations=61 71 total number of function evaluations=2 72 norm schedule ALWAYS 73 Jacobian is built using a DMDA local Jacobian 74SNESLineSearch Object: 2 MPI processes 75 type: bt 76 interpolation: cubic 77 alpha=1.000000e-04 78 maxstep=1.000000e+08, minlambda=1.000000e-12 79 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 80 maximum iterations=40 81 KSP Object: 2 MPI processes 82 type: richardson 83 damping factor=1. 84 maximum iterations=10000, initial guess is zero 85 tolerances: relative=1e-09, absolute=1e-50, divergence=10000. 86 left preconditioning 87 using PRECONDITIONED norm type for convergence test 88 PC Object: 2 MPI processes 89 type: asm 90 total subdomain blocks = 4, amount of overlap = 0 91 restriction/interpolation type - RESTRICT 92 Local solve is same for all blocks, in the following KSP and PC objects: 93 KSP Object: (sub_) 1 MPI processes 94 type: preonly 95 maximum iterations=10000, initial guess is zero 96 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 97 left preconditioning 98 using NONE norm type for convergence test 99 PC Object: (sub_) 1 MPI processes 100 type: lu 101 out-of-place factorization 102 tolerance for zero pivot 2.22045e-14 103 matrix ordering: nd 104 factor fill ratio given 5., needed 1.35714 105 Factored matrix follows: 106 Mat Object: 1 MPI processes 107 type: seqaij 108 rows=8, cols=8 109 package used to perform factorization: petsc 110 total: nonzeros=38, allocated nonzeros=38 111 total number of mallocs used during MatSetValues calls=0 112 not using I-node routines 113 linear system matrix = precond matrix: 114 Mat Object: 1 MPI processes 115 type: seqaij 116 rows=8, cols=8 117 total: nonzeros=28, allocated nonzeros=28 118 total number of mallocs used during MatSetValues calls=0 119 not using I-node routines 120 linear system matrix = precond matrix: 121 Mat Object: 2 MPI processes 122 type: mpiaij 123 rows=32, cols=32 124 total: nonzeros=136, allocated nonzeros=136 125 total number of mallocs used during MatSetValues calls=0 126N: 32 error L2 2.794e-11 inf 5.79417e-11 127