0 SNES Function norm 1.32334 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 1.3212 1 KSP Residual norm 0.299275 2 KSP Residual norm 0.043515 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0408746 1 KSP Residual norm 0.00715117 2 KSP Residual norm 0.00200882 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 1.34445 1 KSP Residual norm 0.289515 2 KSP Residual norm 0.0546877 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0380401 1 KSP Residual norm 0.00836889 2 KSP Residual norm 0.00486415 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00592336 1 KSP Residual norm 0.00127555 2 KSP Residual norm 0.000253948 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.0502885 1 KSP Residual norm 0.00692009 2 KSP Residual norm 0.00304318 0 KSP Residual norm 5.82901 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.22657 1 KSP Residual norm 0.0513167 2 KSP Residual norm 0.00746422 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00701122 1 KSP Residual norm 0.0012265 2 KSP Residual norm 0.000344611 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.230327 1 KSP Residual norm 0.0496328 2 KSP Residual norm 0.00935522 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00652181 1 KSP Residual norm 0.00143468 2 KSP Residual norm 0.000834414 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00101614 1 KSP Residual norm 0.000218815 2 KSP Residual norm 4.35646e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.0085981 1 KSP Residual norm 0.00118416 2 KSP Residual norm 0.000520109 1 KSP Residual norm 0.00134258 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.524964 1 KSP Residual norm 0.103069 2 KSP Residual norm 0.0217471 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0207058 1 KSP Residual norm 0.00314867 2 KSP Residual norm 0.00113072 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 1.8397 1 KSP Residual norm 0.217655 2 KSP Residual norm 0.117319 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0498378 1 KSP Residual norm 0.0109218 2 KSP Residual norm 0.00247682 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00270397 1 KSP Residual norm 0.000566248 2 KSP Residual norm 0.000118256 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.11456 1 KSP Residual norm 0.012674 2 KSP Residual norm 0.00749368 2 KSP Residual norm 2.52518e-06 1 SNES Function norm 0.0426538 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0793943 1 KSP Residual norm 0.017905 2 KSP Residual norm 0.00276128 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.000710871 1 KSP Residual norm 0.000148814 2 KSP Residual norm 2.61706e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.0422535 1 KSP Residual norm 0.0104256 2 KSP Residual norm 0.000711525 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00102555 1 KSP Residual norm 0.000703008 2 KSP Residual norm 0.000457301 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.000432665 1 KSP Residual norm 9.69389e-05 2 KSP Residual norm 1.52326e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.000226183 1 KSP Residual norm 4.76493e-05 2 KSP Residual norm 1.0857e-05 0 KSP Residual norm 0.780398 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.101721 1 KSP Residual norm 0.0229401 2 KSP Residual norm 0.00353783 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.000910901 1 KSP Residual norm 0.000190679 2 KSP Residual norm 3.35381e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.0541359 1 KSP Residual norm 0.0133576 2 KSP Residual norm 0.000911499 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00131394 1 KSP Residual norm 0.000900707 2 KSP Residual norm 0.000585904 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.000554339 1 KSP Residual norm 0.0001242 2 KSP Residual norm 1.95163e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.00028944 1 KSP Residual norm 6.10183e-05 2 KSP Residual norm 1.38846e-05 1 KSP Residual norm 1.23638e-05 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.396136 1 KSP Residual norm 0.0823979 2 KSP Residual norm 0.0138349 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0143355 1 KSP Residual norm 0.0024337 2 KSP Residual norm 0.000681786 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.624996 1 KSP Residual norm 0.0849283 2 KSP Residual norm 0.0370791 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0121259 1 KSP Residual norm 0.00254363 2 KSP Residual norm 0.000483193 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.000359102 1 KSP Residual norm 6.39233e-05 2 KSP Residual norm 1.7077e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.0361135 1 KSP Residual norm 0.00417517 2 KSP Residual norm 0.002293 2 KSP Residual norm 1.0644e-08 2 SNES Function norm 0.000676784 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00128086 1 KSP Residual norm 0.000282989 2 KSP Residual norm 4.71378e-05 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 1.75471e-05 1 KSP Residual norm 3.47885e-06 2 KSP Residual norm 7.25532e-07 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.000688903 1 KSP Residual norm 0.000169178 2 KSP Residual norm 1.32901e-05 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 1.991e-05 1 KSP Residual norm 1.14298e-05 2 KSP Residual norm 7.56087e-06 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 7.30858e-06 1 KSP Residual norm 1.64187e-06 2 KSP Residual norm 2.5929e-07 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 4.03112e-06 1 KSP Residual norm 9.40672e-07 2 KSP Residual norm 1.73312e-07 0 KSP Residual norm 0.0123756 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.103481 1 KSP Residual norm 0.0228627 2 KSP Residual norm 0.00380829 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00141765 1 KSP Residual norm 0.000281056 2 KSP Residual norm 5.86174e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.0556575 1 KSP Residual norm 0.0136682 2 KSP Residual norm 0.00107369 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00160855 1 KSP Residual norm 0.000923429 2 KSP Residual norm 0.000610855 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.000590472 1 KSP Residual norm 0.000132649 2 KSP Residual norm 2.09484e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.000325537 1 KSP Residual norm 7.59825e-05 2 KSP Residual norm 1.39924e-05 1 KSP Residual norm 2.71146e-07 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.384332 1 KSP Residual norm 0.0842136 2 KSP Residual norm 0.0117152 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.0119953 1 KSP Residual norm 0.00218223 2 KSP Residual norm 0.000525707 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.307391 1 KSP Residual norm 0.0524142 2 KSP Residual norm 0.0157681 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00668548 1 KSP Residual norm 0.00129655 2 KSP Residual norm 0.000287599 Residual norms for mg_levels_1_ solve. 0 KSP Residual norm 0.00021681 1 KSP Residual norm 4.00612e-05 2 KSP Residual norm 1.00219e-05 Residual norms for mg_levels_2_ solve. 0 KSP Residual norm 0.0154905 1 KSP Residual norm 0.00200478 2 KSP Residual norm 0.0009371 2 KSP Residual norm 1.134e-10 3 SNES Function norm 1.8565e-07 SNES Object: 1 MPI process type: newtonls maximum iterations=50, maximum function evaluations=10000 tolerances: relative=1e-05, absolute=1e-50, solution=1e-08 total number of linear solver iterations=6 total number of function evaluations=4 norm schedule ALWAYS Jacobian is built using a DMDA local Jacobian SNESLineSearch Object: 1 MPI process type: bt interpolation: cubic alpha=1.000000e-04 maxstep=1.000000e+08, minlambda=1.000000e-12 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 maximum iterations=40 KSP Object: 1 MPI process type: gmres restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement happy breakdown tolerance 1e-30 maximum iterations=10000, initial guess is zero tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning using PRECONDITIONED norm type for convergence test PC Object: 1 MPI process type: mg type is FULL, levels=3 cycles=v Using Galerkin computed coarse grid matrices for pmat Coarse grid solver -- level 0 ------------------------------- KSP Object: (mg_coarse_) 1 MPI process type: preonly maximum iterations=10000, initial guess is zero tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning using NONE norm type for convergence test PC Object: (mg_coarse_) 1 MPI process type: lu out-of-place factorization tolerance for zero pivot 2.22045e-14 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] matrix ordering: nd factor fill ratio given 5., needed 1.59172 Factored matrix follows: Mat Object: 1 MPI process type: seqaij rows=25, cols=25 package used to perform factorization: petsc total: nonzeros=269, allocated nonzeros=269 using I-node routines: found 17 nodes, limit used is 5 linear system matrix = precond matrix: Mat Object: (mg_coarse_) 1 MPI process type: seqaij rows=25, cols=25 total: nonzeros=169, allocated nonzeros=169 total number of mallocs used during MatSetValues calls=0 not using I-node routines Down solver (pre-smoother) on level 1 ------------------------------- KSP Object: (mg_levels_1_) 1 MPI process type: chebyshev eigenvalue targets used: min 0.499526, max 1.09896 eigenvalues estimated via gmres: min 0.229855, max 0.999052 eigenvalues estimated using gmres with transform: [0. 0.5; 0. 1.1] KSP Object: (mg_levels_1_esteig_) 1 MPI process type: gmres restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement happy breakdown tolerance 1e-30 maximum iterations=10, initial guess is zero tolerances: relative=1e-12, absolute=1e-50, divergence=10000. left preconditioning using PRECONDITIONED norm type for convergence test estimating eigenvalues using noisy right hand side maximum iterations=2, nonzero initial guess tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning using UNPRECONDITIONED norm type for convergence test PC Object: (mg_levels_1_) 1 MPI process type: sor type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. linear system matrix = precond matrix: Mat Object: 1 MPI process type: seqaij rows=81, cols=81 total: nonzeros=625, allocated nonzeros=625 total number of mallocs used during MatSetValues calls=0 not using I-node routines Up solver (post-smoother) same as down solver (pre-smoother) Down solver (pre-smoother) on level 2 ------------------------------- KSP Object: (mg_levels_2_) 1 MPI process type: chebyshev eigenvalue targets used: min 0.499175, max 1.09819 eigenvalues estimated via gmres: min 0.050574, max 0.998351 eigenvalues estimated using gmres with transform: [0. 0.5; 0. 1.1] KSP Object: (mg_levels_2_esteig_) 1 MPI process type: gmres restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement happy breakdown tolerance 1e-30 maximum iterations=10, initial guess is zero tolerances: relative=1e-12, absolute=1e-50, divergence=10000. left preconditioning using PRECONDITIONED norm type for convergence test estimating eigenvalues using noisy right hand side maximum iterations=2, nonzero initial guess tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning using UNPRECONDITIONED norm type for convergence test PC Object: (mg_levels_2_) 1 MPI process type: sor type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. linear system matrix = precond matrix: Mat Object: 1 MPI process type: seqaij rows=289, cols=289 total: nonzeros=1377, allocated nonzeros=1377 total number of mallocs used during MatSetValues calls=0 not using I-node routines Up solver (post-smoother) same as down solver (pre-smoother) linear system matrix = precond matrix: Mat Object: 1 MPI process type: seqaij rows=289, cols=289 total: nonzeros=1377, allocated nonzeros=1377 total number of mallocs used during MatSetValues calls=0 not using I-node routines