xref: /petsc/src/snes/tutorials/output/ex18_3.out (revision 27f49a208b01d2e827ab9db411a2d16003fe9262)
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    kmdc=0.0
7    fallback=DOGLEG
8  maximum iterations=50, maximum function evaluations=10000
9  tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
10  total number of linear solver iterations=24
11  total number of function evaluations=10
12  norm schedule ALWAYS
13  KSP Object: 1 MPI process
14    type: fgmres
15      restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
16      happy breakdown tolerance 1e-30
17    maximum iterations=10000, initial guess is zero
18    tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
19    right preconditioning
20    using UNPRECONDITIONED norm type for convergence test
21  PC Object: 1 MPI process
22    type: mg
23      type is MULTIPLICATIVE, levels=3 cycles=v
24        Cycles per PCApply=1
25        Using Galerkin computed coarse grid matrices for pmat
26    Coarse grid solver -- level 0 -------------------------------
27      KSP Object: (mg_coarse_) 1 MPI process
28        type: preonly
29        maximum iterations=10000, initial guess is zero
30        tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
31        left preconditioning
32        using NONE norm type for convergence test
33      PC Object: (mg_coarse_) 1 MPI process
34        type: lu
35          out-of-place factorization
36          tolerance for zero pivot 2.22045e-14
37          using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
38          matrix ordering: nd
39          factor fill ratio given 5., needed 1.59172
40            Factored matrix follows:
41              Mat Object: (mg_coarse_) 1 MPI process
42                type: seqaij
43                rows=25, cols=25
44                package used to perform factorization: petsc
45                total: nonzeros=269, allocated nonzeros=269
46                  using I-node routines: found 17 nodes, limit used is 5
47        linear system matrix = precond matrix:
48        Mat Object: 1 MPI process
49          type: seqaij
50          rows=25, cols=25
51          total: nonzeros=169, allocated nonzeros=169
52          total number of mallocs used during MatSetValues calls=0
53            not using I-node routines
54    Down solver (pre-smoother) on level 1 -------------------------------
55      KSP Object: (mg_levels_1_) 1 MPI process
56        type: chebyshev
57          Chebyshev polynomial of first kind
58          eigenvalue targets used: min 0.0996438, max 1.09608
59          eigenvalues estimated via gmres: min 0.139653, max 0.996438
60          eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
61          KSP Object: (mg_levels_1_esteig_) 1 MPI process
62            type: gmres
63              restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
64              happy breakdown tolerance 1e-30
65            maximum iterations=10, initial guess is zero
66            tolerances:  relative=1e-12, absolute=1e-50, divergence=10000.
67            left preconditioning
68            using PRECONDITIONED norm type for convergence test
69          estimating eigenvalues using noisy right hand side
70        maximum iterations=2, nonzero initial guess
71        tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
72        left preconditioning
73        using NONE norm type for convergence test
74      PC Object: (mg_levels_1_) 1 MPI process
75        type: sor
76          type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
77        linear system matrix = precond matrix:
78        Mat Object: 1 MPI process
79          type: seqaij
80          rows=81, cols=81
81          total: nonzeros=625, allocated nonzeros=625
82          total number of mallocs used during MatSetValues calls=0
83            not using I-node routines
84    Up solver (post-smoother) same as down solver (pre-smoother)
85    Down solver (pre-smoother) on level 2 -------------------------------
86      KSP Object: (mg_levels_2_) 1 MPI process
87        type: chebyshev
88          Chebyshev polynomial of first kind
89          eigenvalue targets used: min 0.0990486, max 1.08953
90          eigenvalues estimated via gmres: min 0.0626846, max 0.990486
91          eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
92          KSP Object: (mg_levels_2_esteig_) 1 MPI process
93            type: gmres
94              restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
95              happy breakdown tolerance 1e-30
96            maximum iterations=10, initial guess is zero
97            tolerances:  relative=1e-12, absolute=1e-50, divergence=10000.
98            left preconditioning
99            using PRECONDITIONED norm type for convergence test
100          estimating eigenvalues using noisy right hand side
101        maximum iterations=2, nonzero initial guess
102        tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
103        left preconditioning
104        using NONE norm type for convergence test
105      PC Object: (mg_levels_2_) 1 MPI process
106        type: sor
107          type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
108        linear system matrix = precond matrix:
109        Mat Object: 1 MPI process
110          type: seqaij
111          rows=289, cols=289
112          total: nonzeros=1377, allocated nonzeros=1377
113          total number of mallocs used during MatSetValues calls=0
114            not using I-node routines
115    Up solver (post-smoother) same as down solver (pre-smoother)
116    linear system matrix = precond matrix:
117    Mat Object: 1 MPI process
118      type: seqaij
119      rows=289, cols=289
120      total: nonzeros=1377, allocated nonzeros=1377
121      total number of mallocs used during MatSetValues calls=0
122        not using I-node routines
123Number of SNES iterations = 9
124Number of Linear iterations = 24
125Average Linear its / SNES = 2.666667e+00
126