xref: /petsc/src/snes/tutorials/output/ex46_1.out (revision c4762a1b19cd2af06abeed90e8f9d34fb975dd94)
1  0 SNES Function norm 0.146402
2  1 SNES Function norm 0.00120796
3  2 SNES Function norm 8.07655e-08
4  3 SNES Function norm < 1.e-11
5SNES Object: 1 MPI processes
6  type: newtonls
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=6
10  total number of function evaluations=4
11  norm schedule ALWAYS
12  Jacobian is built using colored finite differences on a DMDA
13SNESLineSearch Object: 1 MPI processes
14    type: bt
15      interpolation: cubic
16      alpha=1.000000e-04
17    maxstep=1.000000e+08, minlambda=1.000000e-12
18    tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08
19    maximum iterations=40
20  KSP Object: 1 MPI processes
21    type: fgmres
22      restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
23      happy breakdown tolerance 1e-30
24    maximum iterations=10000, initial guess is zero
25    tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
26    right preconditioning
27    using UNPRECONDITIONED norm type for convergence test
28  PC Object: 1 MPI processes
29    type: mg
30      type is FULL, levels=2 cycles=v
31        Not using Galerkin computed coarse grid matrices
32    Coarse grid solver -- level -------------------------------
33      KSP Object: (mg_coarse_) 1 MPI processes
34        type: preonly
35        maximum iterations=10000, initial guess is zero
36        tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
37        left preconditioning
38        using NONE norm type for convergence test
39      PC Object: (mg_coarse_) 1 MPI processes
40        type: lu
41          out-of-place factorization
42          tolerance for zero pivot 2.22045e-14
43          using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
44          matrix ordering: nd
45          factor fill ratio given 5., needed 1.875
46            Factored matrix follows:
47              Mat Object: 1 MPI processes
48                type: seqaij
49                rows=16, cols=16
50                package used to perform factorization: petsc
51                total: nonzeros=120, allocated nonzeros=120
52                total number of mallocs used during MatSetValues calls=0
53                  using I-node routines: found 12 nodes, limit used is 5
54        linear system matrix = precond matrix:
55        Mat Object: 1 MPI processes
56          type: seqaij
57          rows=16, cols=16
58          total: nonzeros=64, allocated nonzeros=64
59          total number of mallocs used during MatSetValues calls=0
60            not using I-node routines
61    Down solver (pre-smoother) on level 1 -------------------------------
62      KSP Object: (mg_levels_1_) 1 MPI processes
63        type: chebyshev
64          eigenvalue estimates used:  min = 0.5, max = 1.1
65          eigenvalues estimate via gmres min 0.38553, max 0.999999
66          eigenvalues estimated using gmres with translations  [0. 0.5; 0. 1.1]
67          KSP Object: (mg_levels_1_esteig_) 1 MPI processes
68            type: gmres
69              restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
70              happy breakdown tolerance 1e-30
71            maximum iterations=10, initial guess is zero
72            tolerances:  relative=1e-12, absolute=1e-50, divergence=10000.
73            left preconditioning
74            using PRECONDITIONED norm type for convergence test
75          estimating eigenvalues using noisy right hand side
76        maximum iterations=2, nonzero initial guess
77        tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
78        left preconditioning
79        using NONE norm type for convergence test
80      PC Object: (mg_levels_1_) 1 MPI processes
81        type: sor
82          type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
83        linear system matrix = precond matrix:
84        Mat Object: 1 MPI processes
85          type: seqaij
86          rows=49, cols=49
87          total: nonzeros=217, allocated nonzeros=217
88          total number of mallocs used during MatSetValues calls=0
89            not using I-node routines
90    Up solver (post-smoother) same as down solver (pre-smoother)
91    linear system matrix = precond matrix:
92    Mat Object: 1 MPI processes
93      type: seqaij
94      rows=49, cols=49
95      total: nonzeros=217, allocated nonzeros=217
96      total number of mallocs used during MatSetValues calls=0
97        not using I-node routines
98Number of SNES iterations = 3
99