1 0 SNES Function norm 0.146402 2 1 SNES Function norm 0.00120796 3 2 SNES Function norm 8.07655e-08 4 3 SNES Function norm < 1.e-11 5SNES Object: 1 MPI process 6 type: newtonls 7 maximum iterations=50, maximum function evaluations=10000 8 tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 9 total number of linear solver iterations=6 10 total number of function evaluations=4 11 norm schedule ALWAYS 12 Jacobian is built using colored finite differences on a DMDA 13 SNESLineSearch Object: 1 MPI process 14 type: bt 15 interpolation: cubic 16 alpha=1.000000e-04 17 maxstep=1.000000e+08, minlambda=1.000000e-12 18 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 19 maximum iterations=40 20 KSP Object: 1 MPI process 21 type: fgmres 22 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 23 happy breakdown tolerance 1e-30 24 maximum iterations=10000, initial guess is zero 25 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 26 right preconditioning 27 using UNPRECONDITIONED norm type for convergence test 28 PC Object: 1 MPI process 29 type: mg 30 type is FULL, levels=2 cycles=v 31 Not using Galerkin computed coarse grid matrices 32 Coarse grid solver -- level 0 ------------------------------- 33 KSP Object: (mg_coarse_) 1 MPI process 34 type: preonly 35 maximum iterations=10000, initial guess is zero 36 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 37 left preconditioning 38 using NONE norm type for convergence test 39 PC Object: (mg_coarse_) 1 MPI process 40 type: lu 41 out-of-place factorization 42 tolerance for zero pivot 2.22045e-14 43 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] 44 matrix ordering: nd 45 factor fill ratio given 5., needed 1.875 46 Factored matrix follows: 47 Mat Object: (mg_coarse_) 1 MPI process 48 type: seqaij 49 rows=16, cols=16 50 package used to perform factorization: petsc 51 total: nonzeros=120, allocated nonzeros=120 52 using I-node routines: found 12 nodes, limit used is 5 53 linear system matrix = precond matrix: 54 Mat Object: 1 MPI process 55 type: seqaij 56 rows=16, cols=16 57 total: nonzeros=64, allocated nonzeros=64 58 total number of mallocs used during MatSetValues calls=0 59 not using I-node routines 60 Down solver (pre-smoother) on level 1 ------------------------------- 61 KSP Object: (mg_levels_1_) 1 MPI process 62 type: chebyshev 63 Chebyshev polynomial of first kind 64 eigenvalue targets used: min 0.5, max 1.1 65 eigenvalues estimated via gmres: min 0.38553, max 0.999999 66 eigenvalues estimated using gmres with transform: [0. 0.5; 0. 1.1] 67 KSP Object: (mg_levels_1_esteig_) 1 MPI process 68 type: gmres 69 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 70 happy breakdown tolerance 1e-30 71 maximum iterations=10, initial guess is zero 72 tolerances: relative=1e-12, absolute=1e-50, divergence=10000. 73 left preconditioning 74 using PRECONDITIONED norm type for convergence test 75 estimating eigenvalues using a noisy random number generated right-hand side 76 maximum iterations=2, nonzero initial guess 77 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 78 left preconditioning 79 using NONE norm type for convergence test 80 PC Object: (mg_levels_1_) 1 MPI process 81 type: sor 82 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 83 linear system matrix = precond matrix: 84 Mat Object: 1 MPI process 85 type: seqaij 86 rows=49, cols=49 87 total: nonzeros=217, allocated nonzeros=217 88 total number of mallocs used during MatSetValues calls=0 89 not using I-node routines 90 Up solver (post-smoother) same as down solver (pre-smoother) 91 linear system matrix = precond matrix: 92 Mat Object: 1 MPI process 93 type: seqaij 94 rows=49, cols=49 95 total: nonzeros=217, allocated nonzeros=217 96 total number of mallocs used during MatSetValues calls=0 97 not using I-node routines 98Number of SNES iterations = 3 99