1SNES Object: 1 MPI process 2 type: newtontr 3 Trust region parameters: 4 eta1=0.001, eta2=0.25, eta3=0.75 5 t1=0.25, t2=2. 6 delta_min=1e-12, delta_0=0.2, delta_max=1e+10 7 kmdc=0. 8 fallback=DOGLEG 9 maximum iterations=50, maximum function evaluations=10000 10 tolerances: relative=1e-08, absolute=1e-50, solution=0. 11 total number of linear solver iterations=24 12 total number of function evaluations=10 13 norm schedule ALWAYS 14 KSP Object: 1 MPI process 15 type: fgmres 16 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 17 happy breakdown tolerance 1e-30 18 maximum iterations=10000, initial guess is zero 19 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 20 right preconditioning 21 using UNPRECONDITIONED norm type for convergence test 22 PC Object: 1 MPI process 23 type: mg 24 type is MULTIPLICATIVE, levels=3 cycles=v 25 Cycles per PCApply=1 26 Using Galerkin computed coarse grid matrices for pmat 27 Coarse grid solver -- level 0 ------------------------------- 28 KSP Object: (mg_coarse_) 1 MPI process 29 type: preonly 30 maximum iterations=10000, initial guess is zero 31 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 32 left preconditioning 33 using NONE norm type for convergence test 34 PC Object: (mg_coarse_) 1 MPI process 35 type: lu 36 out-of-place factorization 37 tolerance for zero pivot 2.22045e-14 38 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] 39 matrix ordering: nd 40 factor fill ratio given 5., needed 1.59172 41 Factored matrix follows: 42 Mat Object: (mg_coarse_) 1 MPI process 43 type: seqaij 44 rows=25, cols=25 45 package used to perform factorization: petsc 46 total: nonzeros=269, allocated nonzeros=269 47 using I-node routines: found 17 nodes, limit used is 5 48 linear system matrix = precond matrix: 49 Mat Object: 1 MPI process 50 type: seqaij 51 rows=25, cols=25 52 total: nonzeros=169, allocated nonzeros=169 53 total number of mallocs used during MatSetValues calls=0 54 not using I-node routines 55 Down solver (pre-smoother) on level 1 ------------------------------- 56 KSP Object: (mg_levels_1_) 1 MPI process 57 type: chebyshev 58 Chebyshev polynomial of first kind 59 eigenvalue targets used: min 0.0996438, max 1.09608 60 eigenvalues estimated via gmres: min 0.139653, max 0.996438 61 eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1] 62 KSP Object: (mg_levels_1_esteig_) 1 MPI process 63 type: gmres 64 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 65 happy breakdown tolerance 1e-30 66 maximum iterations=10, initial guess is zero 67 tolerances: relative=1e-12, absolute=1e-50, divergence=10000. 68 left preconditioning 69 using PRECONDITIONED norm type for convergence test 70 estimating eigenvalues using a noisy random number generated right-hand side 71 maximum iterations=2, nonzero initial guess 72 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 73 left preconditioning 74 using NONE norm type for convergence test 75 PC Object: (mg_levels_1_) 1 MPI process 76 type: sor 77 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 78 linear system matrix = precond matrix: 79 Mat Object: 1 MPI process 80 type: seqaij 81 rows=81, cols=81 82 total: nonzeros=625, allocated nonzeros=625 83 total number of mallocs used during MatSetValues calls=0 84 not using I-node routines 85 Up solver (post-smoother) same as down solver (pre-smoother) 86 Down solver (pre-smoother) on level 2 ------------------------------- 87 KSP Object: (mg_levels_2_) 1 MPI process 88 type: chebyshev 89 Chebyshev polynomial of first kind 90 eigenvalue targets used: min 0.0990486, max 1.08953 91 eigenvalues estimated via gmres: min 0.0626846, max 0.990486 92 eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1] 93 KSP Object: (mg_levels_2_esteig_) 1 MPI process 94 type: gmres 95 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 96 happy breakdown tolerance 1e-30 97 maximum iterations=10, initial guess is zero 98 tolerances: relative=1e-12, absolute=1e-50, divergence=10000. 99 left preconditioning 100 using PRECONDITIONED norm type for convergence test 101 estimating eigenvalues using a noisy random number generated right-hand side 102 maximum iterations=2, nonzero initial guess 103 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 104 left preconditioning 105 using NONE norm type for convergence test 106 PC Object: (mg_levels_2_) 1 MPI process 107 type: sor 108 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 109 linear system matrix = precond matrix: 110 Mat Object: 1 MPI process 111 type: seqaij 112 rows=289, cols=289 113 total: nonzeros=1377, allocated nonzeros=1377 114 total number of mallocs used during MatSetValues calls=0 115 not using I-node routines 116 Up solver (post-smoother) same as down solver (pre-smoother) 117 linear system matrix = precond matrix: 118 Mat Object: 1 MPI process 119 type: seqaij 120 rows=289, cols=289 121 total: nonzeros=1377, allocated nonzeros=1377 122 total number of mallocs used during MatSetValues calls=0 123 not using I-node routines 124Number of SNES iterations = 9 125Number of Linear iterations = 24 126Average Linear its / SNES = 2.666667e+00 127