0 TS dt 8.33333e-06 time 0. 1 TS dt 8.33333e-05 time 8.33333e-06 2 TS dt 0.000833333 time 9.16667e-05 3 TS dt 0.00833333 time 0.000925 4 TS dt 0.0132237 time 0.00925833 5 TS dt 0.0132566 time 0.022482 6 TS dt 0.0132919 time 0.0357387 7 TS dt 0.0133226 time 0.0490305 8 TS dt 0.0133482 time 0.0623531 9 TS dt 0.0133897 time 0.0757014 10 TS dt 0.0134319 time 0.0890911 11 TS dt 0.0134682 time 0.102523 12 TS dt 0.0134977 time 0.115991 13 TS dt 0.0135238 time 0.129489 14 TS dt 0.00489702 time 0.133796 15 TS dt 0.0100499 time 0.138693 16 TS dt 0.0135701 time 0.148743 17 TS dt 0.0136074 time 0.162313 18 TS dt 0.00444936 time 0.165984 19 TS dt 0.00858076 time 0.170433 20 TS dt 0.013541 time 0.179014 21 TS dt 0.0136961 time 0.192555 22 TS dt 0.00532605 time 0.197268 23 TS dt 0.010851 time 0.202594 24 TS dt 0.0137439 time 0.213445 25 TS dt 0.0137662 time 0.227189 26 TS dt 0.00367174 time 0.22978 27 TS dt 0.00589472 time 0.233452 28 TS dt 0.0114309 time 0.239346 29 TS dt 0.0138401 time 0.250777 30 TS dt 0.0137489 time 0.264617 31 TS dt 0.00291312 time 0.266458 32 TS dt 0.00408174 time 0.269371 33 TS dt 0.00693935 time 0.273453 34 TS dt 0.0130397 time 0.280392 35 TS dt 0.0139752 time 0.293432 36 TS dt 0.0129219 time 0.307407 TS Object: 1 MPI process type: arkimex ARK IMEX 3 Stiff abscissa ct = 0.000000 0.871733 0.600000 1.000000 Fully implicit: no Stiffly accurate: yes Explicit first stage: yes FSAL property: yes Nonstiff abscissa c = 0.000000 0.871733 0.600000 1.000000 initial time step=8.33333e-06 maximum steps=1000 maximum time=0.3 maximum number of step rejections=10 maximum number of SNES failures allowed=1 using relative error tolerance of 0.0001, using absolute error tolerance of 0.0001 TSAdapt Object: 1 MPI process type: basic safety factor 0.9 extra safety factor after step rejection 0.5 clip fastest increase 10. clip fastest decrease 0.1 maximum allowed timestep 1e+20 minimum allowed timestep 1e-20 maximum solution absolute value to be ignored -1. SNES Object: 1 MPI process type: newtonls maximum iterations=50, maximum function evaluations=10000 tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 norm schedule ALWAYS 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: 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 MULTIPLICATIVE, levels=3 cycles=v Cycles per PCApply=1 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-50, 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 2.22045e-14 using diagonal shift on blocks to prevent zero pivot [INBLOCKS] matrix ordering: nd factor fill ratio given 5., needed 1.63333 Factored matrix: Mat Object: (mg_coarse_) 1 MPI process type: seqaij rows=60, cols=60 package used to perform factorization: petsc total: nonzeros=294, allocated nonzeros=294 not using I-node routines linear system matrix, which is also used to construct the preconditioner: Mat Object: 1 MPI process type: seqaij rows=60, cols=60 total: nonzeros=180, allocated nonzeros=180 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 0.1, max 1.1 eigenvalues estimated via gmres: min 1., max 1. eigenvalues estimated using gmres with transform: [0. 0.1; 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=3, nonzero initial guess tolerances: relative=1e-05, absolute=1e-50, 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=120, cols=120 total: nonzeros=360, allocated nonzeros=360 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 0.1, max 1.1 eigenvalues estimated via gmres: min 1., max 1. eigenvalues estimated using gmres with transform: [0. 0.1; 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=3, nonzero initial guess tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning not checking for convergence PC Object: (mg_levels_2_) 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=240, cols=240 total: nonzeros=720, allocated nonzeros=720 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=240, cols=240 total: nonzeros=720, allocated nonzeros=720 not using I-node routines