xref: /petsc/src/snes/tutorials/output/ex5_7_ksp_view_pre.out (revision a29dfd43bb0c77e2653d3bfa2c953f902720a6d2)
1KSP Object: 1 MPI process
2  type: gmres
3    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
4    happy breakdown tolerance 1e-30
5  maximum iterations=10000, initial guess is zero
6  tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
7  left preconditioning
8  using DEFAULT norm type for convergence test
9PC Object: 1 MPI process
10  type: gamg
11  PC has not been set up so information may be incomplete
12    type is MULTIPLICATIVE, levels=0 cycles=unknown
13      Cycles per PCApply=0
14      Using externally compute Galerkin coarse grid matrices
15      GAMG specific options
16        Threshold for dropping small values in graph on each level =
17        Threshold scaling factor for each level not specified = 1.
18        AGG specific options
19          Number of levels of aggressive coarsening 1
20          Square graph aggressive coarsening
21          Coarsening algorithm not yet selected
22          Number smoothing steps to construct prolongation 1
23        Complexity:    grid = 0.    operator = 0.
24  linear system matrix = precond matrix:
25  Mat Object: 1 MPI process
26    type: seqaij
27    rows=16, cols=16
28    total: nonzeros=64, allocated nonzeros=64
29    total number of mallocs used during MatSetValues calls=0
30      not using I-node routines
31KSP Object: 1 MPI process
32  type: gmres
33    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
34    happy breakdown tolerance 1e-30
35  maximum iterations=10000, initial guess is zero
36  tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
37  left preconditioning
38  using PRECONDITIONED norm type for convergence test
39PC Object: 1 MPI process
40  type: gamg
41    type is MULTIPLICATIVE, levels=2 cycles=v
42      Cycles per PCApply=1
43      Using externally compute Galerkin coarse grid matrices
44      GAMG specific options
45        Threshold for dropping small values in graph on each level =   -1.   -1.
46        Threshold scaling factor for each level not specified = 1.
47        AGG specific options
48          Number of levels of aggressive coarsening 1
49          Square graph aggressive coarsening
50          MatCoarsen Object: (pc_gamg_) 1 MPI process
51            type: mis
52          Number smoothing steps to construct prolongation 1
53        Complexity:    grid = 1.1875    operator = 1.14062
54  Coarse grid solver -- level 0 -------------------------------
55    KSP Object: (mg_coarse_) 1 MPI process
56      type: preonly
57      maximum iterations=10000, initial guess is zero
58      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
59      left preconditioning
60      using NONE norm type for convergence test
61    PC Object: (mg_coarse_) 1 MPI process
62      type: bjacobi
63        number of blocks = 1
64        Local solver information for first block is in the following KSP and PC objects on rank 0:
65        Use -mg_coarse_ksp_view ::ascii_info_detail to display information for all blocks
66        KSP Object: (mg_coarse_sub_) 1 MPI process
67          type: preonly
68          maximum iterations=1, initial guess is zero
69          tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
70          left preconditioning
71          using NONE norm type for convergence test
72        PC Object: (mg_coarse_sub_) 1 MPI process
73          type: lu
74            out-of-place factorization
75            tolerance for zero pivot 2.22045e-14
76            using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
77            matrix ordering: nd
78            factor fill ratio given 5., needed 1.
79              Factored matrix follows:
80                Mat Object: (mg_coarse_sub_) 1 MPI process
81                  type: seqaij
82                  rows=3, cols=3
83                  package used to perform factorization: petsc
84                  total: nonzeros=9, allocated nonzeros=9
85                    using I-node routines: found 1 nodes, limit used is 5
86          linear system matrix = precond matrix:
87          Mat Object: (mg_coarse_sub_) 1 MPI process
88            type: seqaij
89            rows=3, cols=3
90            total: nonzeros=9, allocated nonzeros=9
91            total number of mallocs used during MatSetValues calls=0
92              using I-node routines: found 1 nodes, limit used is 5
93      linear system matrix = precond matrix:
94      Mat Object: (mg_coarse_sub_) 1 MPI process
95        type: seqaij
96        rows=3, cols=3
97        total: nonzeros=9, allocated nonzeros=9
98        total number of mallocs used during MatSetValues calls=0
99          using I-node routines: found 1 nodes, limit used is 5
100  Down solver (pre-smoother) on level 1 -------------------------------
101    KSP Object: (mg_levels_1_) 1 MPI process
102      type: chebyshev
103        Chebyshev polynomial of first kind
104        eigenvalue targets used: min 1.06112, max 11.6723
105        eigenvalues provided (min 0.311583, max 10.6112) with transform: [0. 0.1; 0. 1.1]
106      maximum iterations=2, nonzero initial guess
107      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
108      left preconditioning
109      using NONE norm type for convergence test
110    PC Object: (mg_levels_1_) 1 MPI process
111      type: jacobi
112        type DIAGONAL
113      linear system matrix = precond matrix:
114      Mat Object: 1 MPI process
115        type: seqaij
116        rows=16, cols=16
117        total: nonzeros=64, allocated nonzeros=64
118        total number of mallocs used during MatSetValues calls=0
119          not using I-node routines
120  Up solver (post-smoother) same as down solver (pre-smoother)
121  linear system matrix = precond matrix:
122  Mat Object: 1 MPI process
123    type: seqaij
124    rows=16, cols=16
125    total: nonzeros=64, allocated nonzeros=64
126    total number of mallocs used during MatSetValues calls=0
127      not using I-node routines
128KSP Object: 1 MPI process
129  type: gmres
130    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
131    happy breakdown tolerance 1e-30
132  maximum iterations=10000, initial guess is zero
133  tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
134  left preconditioning
135  using PRECONDITIONED norm type for convergence test
136PC Object: 1 MPI process
137  type: gamg
138    type is MULTIPLICATIVE, levels=2 cycles=v
139      Cycles per PCApply=1
140      Using externally compute Galerkin coarse grid matrices
141      GAMG specific options
142        Threshold for dropping small values in graph on each level =   -1.   -1.
143        Threshold scaling factor for each level not specified = 1.
144        AGG specific options
145          Number of levels of aggressive coarsening 1
146          Square graph aggressive coarsening
147          MatCoarsen Object: (pc_gamg_) 1 MPI process
148            type: mis
149          Number smoothing steps to construct prolongation 1
150        Complexity:    grid = 1.1875    operator = 1.14062
151  Coarse grid solver -- level 0 -------------------------------
152    KSP Object: (mg_coarse_) 1 MPI process
153      type: preonly
154      maximum iterations=10000, initial guess is zero
155      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
156      left preconditioning
157      using NONE norm type for convergence test
158    PC Object: (mg_coarse_) 1 MPI process
159      type: bjacobi
160        number of blocks = 1
161        Local solver information for first block is in the following KSP and PC objects on rank 0:
162        Use -mg_coarse_ksp_view ::ascii_info_detail to display information for all blocks
163        KSP Object: (mg_coarse_sub_) 1 MPI process
164          type: preonly
165          maximum iterations=1, initial guess is zero
166          tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
167          left preconditioning
168          using NONE norm type for convergence test
169        PC Object: (mg_coarse_sub_) 1 MPI process
170          type: lu
171            out-of-place factorization
172            tolerance for zero pivot 2.22045e-14
173            using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
174            matrix ordering: nd
175            factor fill ratio given 5., needed 1.
176              Factored matrix follows:
177                Mat Object: (mg_coarse_sub_) 1 MPI process
178                  type: seqaij
179                  rows=3, cols=3
180                  package used to perform factorization: petsc
181                  total: nonzeros=9, allocated nonzeros=9
182                    using I-node routines: found 1 nodes, limit used is 5
183          linear system matrix = precond matrix:
184          Mat Object: (mg_coarse_sub_) 1 MPI process
185            type: seqaij
186            rows=3, cols=3
187            total: nonzeros=9, allocated nonzeros=9
188            total number of mallocs used during MatSetValues calls=0
189              using I-node routines: found 1 nodes, limit used is 5
190      linear system matrix = precond matrix:
191      Mat Object: (mg_coarse_sub_) 1 MPI process
192        type: seqaij
193        rows=3, cols=3
194        total: nonzeros=9, allocated nonzeros=9
195        total number of mallocs used during MatSetValues calls=0
196          using I-node routines: found 1 nodes, limit used is 5
197  Down solver (pre-smoother) on level 1 -------------------------------
198    KSP Object: (mg_levels_1_) 1 MPI process
199      type: chebyshev
200        Chebyshev polynomial of first kind
201        eigenvalue targets used: min 0.159372, max 1.75309
202        eigenvalues estimated via gmres: min 0.406283, max 1.59372
203        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
204        KSP Object: (mg_levels_1_esteig_) 1 MPI process
205          type: gmres
206            restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
207            happy breakdown tolerance 1e-30
208          maximum iterations=10, initial guess is zero
209          tolerances: relative=1e-12, absolute=1e-50, divergence=10000.
210          left preconditioning
211          using PRECONDITIONED norm type for convergence test
212        estimating eigenvalues using a noisy random number generated right-hand side
213      maximum iterations=2, nonzero initial guess
214      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
215      left preconditioning
216      using NONE norm type for convergence test
217    PC Object: (mg_levels_1_) 1 MPI process
218      type: jacobi
219        type DIAGONAL
220      linear system matrix = precond matrix:
221      Mat Object: 1 MPI process
222        type: seqaij
223        rows=16, cols=16
224        total: nonzeros=64, allocated nonzeros=64
225        total number of mallocs used during MatSetValues calls=0
226          not using I-node routines
227  Up solver (post-smoother) same as down solver (pre-smoother)
228  linear system matrix = precond matrix:
229  Mat Object: 1 MPI process
230    type: seqaij
231    rows=16, cols=16
232    total: nonzeros=64, allocated nonzeros=64
233    total number of mallocs used during MatSetValues calls=0
234      not using I-node routines
235KSP Object: 1 MPI process
236  type: gmres
237    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
238    happy breakdown tolerance 1e-30
239  maximum iterations=10000, initial guess is zero
240  tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
241  left preconditioning
242  using PRECONDITIONED norm type for convergence test
243PC Object: 1 MPI process
244  type: gamg
245    type is MULTIPLICATIVE, levels=2 cycles=v
246      Cycles per PCApply=1
247      Using externally compute Galerkin coarse grid matrices
248      GAMG specific options
249        Threshold for dropping small values in graph on each level =   -1.   -1.
250        Threshold scaling factor for each level not specified = 1.
251        AGG specific options
252          Number of levels of aggressive coarsening 1
253          Square graph aggressive coarsening
254          MatCoarsen Object: (pc_gamg_) 1 MPI process
255            type: mis
256          Number smoothing steps to construct prolongation 1
257        Complexity:    grid = 1.1875    operator = 1.14062
258  Coarse grid solver -- level 0 -------------------------------
259    KSP Object: (mg_coarse_) 1 MPI process
260      type: preonly
261      maximum iterations=10000, initial guess is zero
262      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
263      left preconditioning
264      using NONE norm type for convergence test
265    PC Object: (mg_coarse_) 1 MPI process
266      type: bjacobi
267        number of blocks = 1
268        Local solver information for first block is in the following KSP and PC objects on rank 0:
269        Use -mg_coarse_ksp_view ::ascii_info_detail to display information for all blocks
270        KSP Object: (mg_coarse_sub_) 1 MPI process
271          type: preonly
272          maximum iterations=1, initial guess is zero
273          tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
274          left preconditioning
275          using NONE norm type for convergence test
276        PC Object: (mg_coarse_sub_) 1 MPI process
277          type: lu
278            out-of-place factorization
279            tolerance for zero pivot 2.22045e-14
280            using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
281            matrix ordering: nd
282            factor fill ratio given 5., needed 1.
283              Factored matrix follows:
284                Mat Object: (mg_coarse_sub_) 1 MPI process
285                  type: seqaij
286                  rows=3, cols=3
287                  package used to perform factorization: petsc
288                  total: nonzeros=9, allocated nonzeros=9
289                    using I-node routines: found 1 nodes, limit used is 5
290          linear system matrix = precond matrix:
291          Mat Object: (mg_coarse_sub_) 1 MPI process
292            type: seqaij
293            rows=3, cols=3
294            total: nonzeros=9, allocated nonzeros=9
295            total number of mallocs used during MatSetValues calls=0
296              using I-node routines: found 1 nodes, limit used is 5
297      linear system matrix = precond matrix:
298      Mat Object: (mg_coarse_sub_) 1 MPI process
299        type: seqaij
300        rows=3, cols=3
301        total: nonzeros=9, allocated nonzeros=9
302        total number of mallocs used during MatSetValues calls=0
303          using I-node routines: found 1 nodes, limit used is 5
304  Down solver (pre-smoother) on level 1 -------------------------------
305    KSP Object: (mg_levels_1_) 1 MPI process
306      type: chebyshev
307        Chebyshev polynomial of first kind
308        eigenvalue targets used: min 0.160581, max 1.76639
309        eigenvalues estimated via gmres: min 0.394193, max 1.60581
310        eigenvalues estimated using gmres with transform: [0. 0.1; 0. 1.1]
311        KSP Object: (mg_levels_1_esteig_) 1 MPI process
312          type: gmres
313            restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
314            happy breakdown tolerance 1e-30
315          maximum iterations=10, initial guess is zero
316          tolerances: relative=1e-12, absolute=1e-50, divergence=10000.
317          left preconditioning
318          using PRECONDITIONED norm type for convergence test
319        estimating eigenvalues using a noisy random number generated right-hand side
320      maximum iterations=2, nonzero initial guess
321      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
322      left preconditioning
323      using NONE norm type for convergence test
324    PC Object: (mg_levels_1_) 1 MPI process
325      type: jacobi
326        type DIAGONAL
327      linear system matrix = precond matrix:
328      Mat Object: 1 MPI process
329        type: seqaij
330        rows=16, cols=16
331        total: nonzeros=64, allocated nonzeros=64
332        total number of mallocs used during MatSetValues calls=0
333          not using I-node routines
334  Up solver (post-smoother) same as down solver (pre-smoother)
335  linear system matrix = precond matrix:
336  Mat Object: 1 MPI process
337    type: seqaij
338    rows=16, cols=16
339    total: nonzeros=64, allocated nonzeros=64
340    total number of mallocs used during MatSetValues calls=0
341      not using I-node routines
342