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 Chebyshev polynomial of first kind 57 eigenvalue targets used: min 0.0996438, max 1.09608 58 eigenvalues estimated via gmres: min 0.139653, max 0.996438 59 eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1] 60 KSP Object: (mg_levels_1_esteig_) 1 MPI process 61 type: gmres 62 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 63 happy breakdown tolerance 1e-30 64 maximum iterations=10, initial guess is zero 65 tolerances: relative=1e-12, absolute=1e-50, divergence=10000. 66 left preconditioning 67 using PRECONDITIONED norm type for convergence test 68 estimating eigenvalues using noisy right hand side 69 maximum iterations=2, nonzero initial guess 70 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 71 left preconditioning 72 using NONE norm type for convergence test 73 PC Object: (mg_levels_1_) 1 MPI process 74 type: sor 75 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 76 linear system matrix = precond matrix: 77 Mat Object: 1 MPI process 78 type: seqaij 79 rows=81, cols=81 80 total: nonzeros=625, allocated nonzeros=625 81 total number of mallocs used during MatSetValues calls=0 82 not using I-node routines 83 Up solver (post-smoother) same as down solver (pre-smoother) 84 Down solver (pre-smoother) on level 2 ------------------------------- 85 KSP Object: (mg_levels_2_) 1 MPI process 86 type: chebyshev 87 Chebyshev polynomial of first kind 88 eigenvalue targets used: min 0.0990486, max 1.08953 89 eigenvalues estimated via gmres: min 0.0626846, max 0.990486 90 eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1] 91 KSP Object: (mg_levels_2_esteig_) 1 MPI process 92 type: gmres 93 restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement 94 happy breakdown tolerance 1e-30 95 maximum iterations=10, initial guess is zero 96 tolerances: relative=1e-12, absolute=1e-50, divergence=10000. 97 left preconditioning 98 using PRECONDITIONED norm type for convergence test 99 estimating eigenvalues using noisy right hand side 100 maximum iterations=2, nonzero initial guess 101 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 102 left preconditioning 103 using NONE norm type for convergence test 104 PC Object: (mg_levels_2_) 1 MPI process 105 type: sor 106 type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. 107 linear system matrix = precond matrix: 108 Mat Object: 1 MPI process 109 type: seqaij 110 rows=289, cols=289 111 total: nonzeros=1377, allocated nonzeros=1377 112 total number of mallocs used during MatSetValues calls=0 113 not using I-node routines 114 Up solver (post-smoother) same as down solver (pre-smoother) 115 linear system matrix = precond matrix: 116 Mat Object: 1 MPI process 117 type: seqaij 118 rows=289, cols=289 119 total: nonzeros=1377, allocated nonzeros=1377 120 total number of mallocs used during MatSetValues calls=0 121 not using I-node routines 122Number of SNES iterations = 9 123Number of Linear iterations = 24 124Average Linear its / SNES = 2.666667e+00 125