1SNES Object: 1 MPI processes
2  type: newtonls
3  maximum iterations=50, maximum function evaluations=10000
4  tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
5  total number of linear solver iterations=24
6  total number of function evaluations=7
7  norm schedule ALWAYS
8  SNESLineSearch Object: 1 MPI processes
9    type: bt
10      interpolation: cubic
11      alpha=1.000000e-04
12    maxstep=1.000000e+08, minlambda=1.000000e-12
13    tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08
14    maximum iterations=40
15  KSP Object: 1 MPI processes
16    type: fgmres
17      restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
18      happy breakdown tolerance 1e-30
19    maximum iterations=10000, initial guess is zero
20    tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
21    right preconditioning
22    using UNPRECONDITIONED norm type for convergence test
23  PC Object: 1 MPI processes
24    type: mg
25      type is MULTIPLICATIVE, levels=3 cycles=v
26        Cycles per PCApply=1
27        Using Galerkin computed coarse grid matrices for pmat
28    Coarse grid solver -- level -------------------------------
29      KSP Object: (mg_coarse_) 1 MPI processes
30        type: preonly
31        maximum iterations=10000, initial guess is zero
32        tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
33        left preconditioning
34        using NONE norm type for convergence test
35      PC Object: (mg_coarse_) 1 MPI processes
36        type: lu
37          out-of-place factorization
38          tolerance for zero pivot 2.22045e-14
39          using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
40          matrix ordering: nd
41          factor fill ratio given 5., needed 1.59172
42            Factored matrix follows:
43              Mat Object: 1 MPI processes
44                type: seqaij
45                rows=25, cols=25
46                package used to perform factorization: petsc
47                total: nonzeros=269, allocated nonzeros=269
48                  using I-node routines: found 17 nodes, limit used is 5
49        linear system matrix = precond matrix:
50        Mat Object: 1 MPI processes
51          type: seqaij
52          rows=25, cols=25
53          total: nonzeros=169, allocated nonzeros=169
54          total number of mallocs used during MatSetValues calls=0
55            not using I-node routines
56    Down solver (pre-smoother) on level 1 -------------------------------
57      KSP Object: (mg_levels_1_) 1 MPI processes
58        type: chebyshev
59          eigenvalue estimates used:  min = 0.0996438, max = 1.09608
60          eigenvalues estimate via gmres min 0.139653, max 0.996438
61          eigenvalues estimated using gmres with translations  [0. 0.1; 0. 1.1]
62          KSP Object: (mg_levels_1_esteig_) 1 MPI processes
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 noisy 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 processes
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 processes
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 processes
88        type: chebyshev
89          eigenvalue estimates used:  min = 0.0990486, max = 1.08953
90          eigenvalues estimate via gmres min 0.0626846, max 0.990486
91          eigenvalues estimated using gmres with translations  [0. 0.1; 0. 1.1]
92          KSP Object: (mg_levels_2_esteig_) 1 MPI processes
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 processes
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 processes
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 processes
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 = 6
124Number of Linear iterations = 24
125Average Linear its / SNES = 4.000000e+00
126