1 0 SNES Function norm 0.146402 2 1 SNES Function norm 0.00119047 3 2 SNES Function norm 7.73027e-07 4SNES Object: 1 MPI process 5 type: newtonls 6 maximum iterations=50, maximum function evaluations=10000 7 tolerances: relative=1e-05, absolute=1e-25, solution=1e-05 8 total number of linear solver iterations=4 9 total number of function evaluations=3 10 norm schedule ALWAYS 11 Jacobian is built using colored finite differences on a DMDA 12SNESLineSearch Object: 1 MPI process 13 type: bt 14 interpolation: cubic 15 alpha=1.000000e-04 16 maxstep=1.000000e+08, minlambda=1.000000e-12 17 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 18 maximum iterations=40 19 KSP Object: 1 MPI process 20 type: fgmres 21 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 22 happy breakdown tolerance 1e-30 23 maximum iterations=10000, initial guess is zero 24 tolerances: relative=1e-05, absolute=1e-25, divergence=10000. 25 right preconditioning 26 using UNPRECONDITIONED norm type for convergence test 27 PC Object: 1 MPI process 28 type: mg 29 type is FULL, levels=2 cycles=v 30 Not using Galerkin computed coarse grid matrices 31 Coarse grid solver -- level 0 ------------------------------- 32 KSP Object: (mg_coarse_) 1 MPI process 33 type: preonly 34 maximum iterations=10000, initial guess is zero 35 tolerances: relative=1e-05, absolute=1e-25, divergence=10000. 36 left preconditioning 37 using NONE norm type for convergence test 38 PC Object: (mg_coarse_) 1 MPI process 39 type: lu 40 out-of-place factorization 41 tolerance for zero pivot 1.19209e-05 42 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] 43 matrix ordering: nd 44 factor fill ratio given 5., needed 1.875 45 Factored matrix follows: 46 Mat Object: (mg_coarse_) 1 MPI process 47 type: seqaij 48 rows=16, cols=16 49 package used to perform factorization: petsc 50 total: nonzeros=120, allocated nonzeros=120 51 using I-node routines: found 12 nodes, limit used is 5 52 linear system matrix = precond matrix: 53 Mat Object: 1 MPI process 54 type: seqaij 55 rows=16, cols=16 56 total: nonzeros=64, allocated nonzeros=64 57 total number of mallocs used during MatSetValues calls=0 58 not using I-node routines 59 Down solver (pre-smoother) on level 1 ------------------------------- 60 KSP Object: (mg_levels_1_) 1 MPI process 61 type: chebyshev 62 eigenvalue targets used: min 0.498841, max 1.09745 63 eigenvalues estimated via gmres: min 0.385405, max 0.997681 64 eigenvalues estimated using gmres with transform: [0. 0.5; 0. 1.1] 65 KSP Object: (mg_levels_1_esteig_) 1 MPI process 66 type: gmres 67 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 68 happy breakdown tolerance 1e-30 69 maximum iterations=10, initial guess is zero 70 tolerances: relative=1e-12, absolute=1e-25, divergence=10000. 71 left preconditioning 72 using PRECONDITIONED norm type for convergence test 73 estimating eigenvalues using noisy right hand side 74 maximum iterations=2, nonzero initial guess 75 tolerances: relative=1e-05, absolute=1e-25, divergence=10000. 76 left preconditioning 77 using NONE norm type for convergence test 78 PC Object: (mg_levels_1_) 1 MPI process 79 type: sor 80 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 81 linear system matrix = precond matrix: 82 Mat Object: 1 MPI process 83 type: seqaij 84 rows=49, cols=49 85 total: nonzeros=217, allocated nonzeros=217 86 total number of mallocs used during MatSetValues calls=0 87 not using I-node routines 88 Up solver (post-smoother) same as down solver (pre-smoother) 89 linear system matrix = precond matrix: 90 Mat Object: 1 MPI process 91 type: seqaij 92 rows=49, cols=49 93 total: nonzeros=217, allocated nonzeros=217 94 total number of mallocs used during MatSetValues calls=0 95 not using I-node routines 96Number of SNES iterations = 2 97