0 SNES Function norm 0.146402 1 SNES Function norm 0.00119047 2 SNES Function norm 7.73027e-07 SNES Object: 1 MPI process type: newtonls maximum iterations=50, maximum function evaluations=10000 tolerances: relative=1e-05, absolute=1e-25, solution=1e-05 total number of linear solver iterations=4 total number of function evaluations=3 norm schedule ALWAYS Jacobian is built using colored finite differences on a DMDA SNESLineSearch Object: 1 MPI process 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: 1 MPI process type: fgmres 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-25, divergence=10000. right preconditioning using UNPRECONDITIONED norm type for convergence test PC Object: 1 MPI process type: mg type is FULL, levels=2 cycles=v Not using Galerkin computed coarse grid matrices 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-25, divergence=10000. left preconditioning not checking for convergence PC Object: (mg_coarse_) 1 MPI process type: lu out-of-place factorization tolerance for zero pivot 1.19209e-05 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] matrix ordering: nd factor fill ratio given 5., needed 1.875 Factored matrix: Mat Object: (mg_coarse_) 1 MPI process type: seqaij rows=16, cols=16 package used to perform factorization: petsc total: nonzeros=120, allocated nonzeros=120 using I-node routines: found 12 nodes, limit used is 5 linear system matrix, which is also used to construct the preconditioner: Mat Object: 1 MPI process type: seqaij rows=16, cols=16 total: nonzeros=64, allocated nonzeros=64 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 0.498841, max 1.09745 eigenvalues estimated via gmres: min 0.385405, max 0.997681 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-25, 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-25, divergence=10000. left preconditioning not checking for convergence PC Object: (mg_levels_1_) 1 MPI process type: sor type = local_symmetric, iterations = 1, local iterations = 1, omega = 1. linear system matrix, which is also used to construct the preconditioner: Mat Object: 1 MPI process type: seqaij rows=49, cols=49 total: nonzeros=217, allocated nonzeros=217 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, which is also used to construct the preconditioner: Mat Object: 1 MPI process type: seqaij rows=49, cols=49 total: nonzeros=217, allocated nonzeros=217 total number of mallocs used during MatSetValues calls=0 not using I-node routines Number of SNES iterations = 2