0 SNES Function norm 0.995735 Linear solve converged due to CONVERGED_RTOL iterations 3 1 SNES Function norm 0.276938 Linear solve converged due to CONVERGED_RTOL iterations 3 2 SNES Function norm 0.00668678 Linear solve converged due to CONVERGED_RTOL iterations 2 3 SNES Function norm 4.61502e-06 Linear solve converged due to CONVERGED_RTOL iterations 2 4 SNES Function norm 1.568e-11 0 SNES Function norm 0.0763997 Linear solve converged due to CONVERGED_RTOL iterations 2 1 SNES Function norm 2.67906e-05 Linear solve converged due to CONVERGED_RTOL iterations 2 2 SNES Function norm 9.312e-11 0 SNES Function norm 0.0408394 Linear solve converged due to CONVERGED_RTOL iterations 2 1 SNES Function norm 9.10598e-07 Linear solve converged due to CONVERGED_RTOL iterations 2 2 SNES Function norm < 1.e-11 0 SNES Function norm 0.021012 Linear solve converged due to CONVERGED_RTOL iterations 2 1 SNES Function norm 3.84069e-08 Linear solve converged due to CONVERGED_RTOL iterations 2 2 SNES Function norm < 1.e-11 SNES Object: 1 MPI process 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=22 total number of function evaluations=14 norm schedule ALWAYS total number of grid sequence refinements=3 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=-1., divergence=10000. left preconditioning using PRECONDITIONED norm type for convergence test PC Object: 1 MPI process type: mg type is FULL, levels=4 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 1.42 Factored matrix follows: Mat Object: (mg_coarse_) 1 MPI process type: seqaij rows=16, cols=16 package used to perform factorization: petsc total: nonzeros=142, allocated nonzeros=142 using I-node routines: found 11 nodes, limit used is 5 linear system matrix = precond matrix: Mat Object: 1 MPI process type: seqaij rows=16, cols=16 total: nonzeros=100, allocated nonzeros=100 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 Chebyshev polynomial of first kind eigenvalue targets used: min 0.49992, max 1.09982 eigenvalues estimated via gmres: min 0.38164, max 0.999839 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 a noisy random number generated 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=49, cols=49 total: nonzeros=361, allocated nonzeros=361 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 Chebyshev polynomial of first kind eigenvalue targets used: min 0.498238, max 1.09612 eigenvalues estimated via gmres: min 0.11325, max 0.996475 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 a noisy random number generated 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=169, cols=169 total: nonzeros=1369, allocated nonzeros=1369 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 3 ------------------------------- KSP Object: (mg_levels_3_) 1 MPI process type: chebyshev Chebyshev polynomial of first kind eigenvalue targets used: min 0.498868, max 1.09751 eigenvalues estimated via gmres: min 0.0267868, max 0.997736 eigenvalues estimated using gmres with transform: [0. 0.5; 0. 1.1] KSP Object: (mg_levels_3_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 a noisy random number generated 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_3_) 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=625, cols=625 total: nonzeros=3025, allocated nonzeros=3025 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=625, cols=625 total: nonzeros=3025, allocated nonzeros=3025 total number of mallocs used during MatSetValues calls=0 not using I-node routines