0 SNES Function norm 13709.3 0 SNES Function norm 13709.3 1 SNES Function norm 4063.09 2 SNES Function norm 1209.16 3 SNES Function norm 358.664 4 SNES Function norm 106.534 0 SNES Function norm 100.4 1 SNES Function norm 85.1096 2 SNES Function norm 73.9499 3 SNES Function norm 46.0381 4 SNES Function norm 21.1178 0 SNES Function norm 8.52767 1 SNES Function norm 720.169 2 SNES Function norm 211.546 3 SNES Function norm 60.9206 4 SNES Function norm 16.4878 5 SNES Function norm 3.75186 6 SNES Function norm 0.550474 7 SNES Function norm 0.0246361 8 SNES Function norm 6.49531e-05 9 SNES Function norm 5.157e-10 0 SNES Function norm 16.0595 1 SNES Function norm 3.22362 2 SNES Function norm 0.877344 3 SNES Function norm 0.241559 4 SNES Function norm 0.0458156 0 SNES Function norm 380.549 1 SNES Function norm 112.851 2 SNES Function norm 33.6101 3 SNES Function norm 10.1359 4 SNES Function norm 3.24012 1 SNES Function norm 3.24012 0 SNES Function norm 3.24012 1 SNES Function norm 1.103 2 SNES Function norm 0.274359 3 SNES Function norm 0.0273309 4 SNES Function norm 0.000588161 0 SNES Function norm 0.000492505 1 SNES Function norm 1.24678e-07 2 SNES Function norm < 1.e-11 3 SNES Function norm < 1.e-11 4 SNES Function norm < 1.e-11 0 SNES Function norm < 1.e-11 1 SNES Function norm < 1.e-11 0 SNES Function norm < 1.e-11 1 SNES Function norm < 1.e-11 2 SNES Function norm < 1.e-11 3 SNES Function norm < 1.e-11 0 SNES Function norm 0.000415292 1 SNES Function norm 6.33274e-08 2 SNES Function norm < 1.e-11 3 SNES Function norm < 1.e-11 4 SNES Function norm < 1.e-11 2 SNES Function norm < 1.e-11 Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 2 SNES Object: 4 MPI processes type: fas type is MULTIPLICATIVE, levels=3, cycles=1 Not using Galerkin computed coarse grid function evaluation Coarse grid solver -- level 0 ------------------------------- SNES Object: (fas_coarse_) 4 MPI processes type: newtonls maximum iterations=50, maximum function evaluations=10000 tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 total number of linear solver iterations=36 total number of function evaluations=1 SNESLineSearch Object: (fas_coarse_) 4 MPI processes type: basic maxlambda=1.000000e+00, minlambda=1.000000e-12 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 maximum iterations=40 KSP Object: (fas_coarse_) 4 MPI processes type: cg 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: (fas_coarse_) 4 MPI processes type: jacobi linear system matrix, which is also used to construct the preconditioner: Mat Object: 4 MPI processes type: mpiaij rows=211, cols=211 total: nonzeros=2817, allocated nonzeros=2817 total number of mallocs used during MatSetValues calls=0 not using I-node (on process 0) routines Down solver (pre-smoother) on level 1 ------------------------------- SNES Object: (fas_levels_1_) 4 MPI processes type: newtonls maximum iterations=4, maximum function evaluations=10000 tolerances: relative=0., absolute=0., solution=0. total number of linear solver iterations=235 total number of function evaluations=41 norm schedule FINALONLY SNESLineSearch Object: (fas_levels_1_) 4 MPI processes type: bt interpolation: cubic alpha=1.000000e-04 maxlambda=1.000000e+00, minlambda=1.000000e-12 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 maximum iterations=40 KSP Object: (fas_levels_1_) 4 MPI processes type: cg 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: (fas_levels_1_) 4 MPI processes type: jacobi linear system matrix, which is also used to construct the preconditioner: Mat Object: 4 MPI processes type: mpiaij rows=515, cols=515 total: nonzeros=7445, allocated nonzeros=7445 total number of mallocs used during MatSetValues calls=0 not using I-node (on process 0) routines Up solver (post-smoother) same as down solver (pre-smoother) Down solver (pre-smoother) on level 2 ------------------------------- SNES Object: (fas_levels_2_) 4 MPI processes type: newtonls maximum iterations=4, maximum function evaluations=10000 tolerances: relative=0., absolute=0., solution=0. total number of linear solver iterations=413 total number of function evaluations=5 norm schedule FINALONLY SNESLineSearch Object: (fas_levels_2_) 4 MPI processes type: bt interpolation: cubic alpha=1.000000e-04 maxlambda=1.000000e+00, minlambda=1.000000e-12 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 maximum iterations=40 KSP Object: (fas_levels_2_) 4 MPI processes type: cg 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: (fas_levels_2_) 4 MPI processes type: jacobi linear system matrix, which is also used to construct the preconditioner: Mat Object: 4 MPI processes type: mpiaij rows=1477, cols=1477 total: nonzeros=22453, allocated nonzeros=22453 total number of mallocs used during MatSetValues calls=0 not using I-node (on process 0) routines Up solver (post-smoother) same as down solver (pre-smoother) maximum iterations=10, maximum function evaluations=30000 tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 total number of function evaluations=1 norm schedule ALWAYS SNESLineSearch Object: 4 MPI processes type: bt interpolation: cubic alpha=1.000000e-04 maxlambda=1.000000e+00, minlambda=1.000000e-12 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 maximum iterations=40