1SNES Object: 1 MPI process 2 type: newtontr 3 Trust region tolerance 1e-12 4 eta1=0.001, eta2=0.25, eta3=0.75 5 delta0=0.2, t1=0.25, t2=2., deltaM=1.79769e+308 6 fallback=DOGLEG 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=24 10 total number of function evaluations=10 11 norm schedule ALWAYS 12 KSP Object: 1 MPI process 13 type: fgmres 14 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 15 happy breakdown tolerance 1e-30 16 maximum iterations=10000, initial guess is zero 17 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 18 right preconditioning 19 using UNPRECONDITIONED norm type for convergence test 20 PC Object: 1 MPI process 21 type: mg 22 type is MULTIPLICATIVE, levels=3 cycles=v 23 Cycles per PCApply=1 24 Using Galerkin computed coarse grid matrices for pmat 25 Coarse grid solver -- level 0 ------------------------------- 26 KSP Object: (mg_coarse_) 1 MPI process 27 type: preonly 28 maximum iterations=10000, initial guess is zero 29 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 30 left preconditioning 31 using NONE norm type for convergence test 32 PC Object: (mg_coarse_) 1 MPI process 33 type: lu 34 out-of-place factorization 35 tolerance for zero pivot 2.22045e-14 36 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] 37 matrix ordering: nd 38 factor fill ratio given 5., needed 1.59172 39 Factored matrix follows: 40 Mat Object: (mg_coarse_) 1 MPI process 41 type: seqaij 42 rows=25, cols=25 43 package used to perform factorization: petsc 44 total: nonzeros=269, allocated nonzeros=269 45 using I-node routines: found 17 nodes, limit used is 5 46 linear system matrix = precond matrix: 47 Mat Object: 1 MPI process 48 type: seqaij 49 rows=25, cols=25 50 total: nonzeros=169, allocated nonzeros=169 51 total number of mallocs used during MatSetValues calls=0 52 not using I-node routines 53 Down solver (pre-smoother) on level 1 ------------------------------- 54 KSP Object: (mg_levels_1_) 1 MPI process 55 type: chebyshev 56 eigenvalue targets used: min 0.0996438, max 1.09608 57 eigenvalues estimated via gmres: min 0.139653, max 0.996438 58 eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1] 59 KSP Object: (mg_levels_1_esteig_) 1 MPI process 60 type: gmres 61 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 62 happy breakdown tolerance 1e-30 63 maximum iterations=10, initial guess is zero 64 tolerances: relative=1e-12, absolute=1e-50, divergence=10000. 65 left preconditioning 66 using PRECONDITIONED norm type for convergence test 67 estimating eigenvalues using noisy right hand side 68 maximum iterations=2, nonzero initial guess 69 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 70 left preconditioning 71 using NONE norm type for convergence test 72 PC Object: (mg_levels_1_) 1 MPI process 73 type: sor 74 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 75 linear system matrix = precond matrix: 76 Mat Object: 1 MPI process 77 type: seqaij 78 rows=81, cols=81 79 total: nonzeros=625, allocated nonzeros=625 80 total number of mallocs used during MatSetValues calls=0 81 not using I-node routines 82 Up solver (post-smoother) same as down solver (pre-smoother) 83 Down solver (pre-smoother) on level 2 ------------------------------- 84 KSP Object: (mg_levels_2_) 1 MPI process 85 type: chebyshev 86 eigenvalue targets used: min 0.0990486, max 1.08953 87 eigenvalues estimated via gmres: min 0.0626846, max 0.990486 88 eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1] 89 KSP Object: (mg_levels_2_esteig_) 1 MPI process 90 type: gmres 91 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 92 happy breakdown tolerance 1e-30 93 maximum iterations=10, initial guess is zero 94 tolerances: relative=1e-12, absolute=1e-50, divergence=10000. 95 left preconditioning 96 using PRECONDITIONED norm type for convergence test 97 estimating eigenvalues using noisy right hand side 98 maximum iterations=2, nonzero initial guess 99 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 100 left preconditioning 101 using NONE norm type for convergence test 102 PC Object: (mg_levels_2_) 1 MPI process 103 type: sor 104 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 105 linear system matrix = precond matrix: 106 Mat Object: 1 MPI process 107 type: seqaij 108 rows=289, cols=289 109 total: nonzeros=1377, allocated nonzeros=1377 110 total number of mallocs used during MatSetValues calls=0 111 not using I-node routines 112 Up solver (post-smoother) same as down solver (pre-smoother) 113 linear system matrix = precond matrix: 114 Mat Object: 1 MPI process 115 type: seqaij 116 rows=289, cols=289 117 total: nonzeros=1377, allocated nonzeros=1377 118 total number of mallocs used during MatSetValues calls=0 119 not using I-node routines 120Number of SNES iterations = 9 121Number of Linear iterations = 24 122Average Linear its / SNES = 2.666667e+00 123