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 0.00494253 time 0.133832 15 TS dt 0.0101592 time 0.138775 16 TS dt 0.0135719 time 0.148934 17 TS dt 0.0136045 time 0.162506 18 TS dt 0.00437533 time 0.16608 19 TS dt 0.00831549 time 0.170455 20 TS dt 0.013504 time 0.17877 21 TS dt 0.0136927 time 0.192274 22 TS dt 0.00553705 time 0.19724 23 TS dt 0.010971 time 0.202777 24 TS dt 0.0137439 time 0.213748 25 TS dt 0.0137512 time 0.227492 26 TS dt 0.00340744 time 0.229825 27 TS dt 0.00522351 time 0.233233 28 TS dt 0.00987025 time 0.238456 29 TS dt 0.0138095 time 0.248327 30 TS dt 0.0138628 time 0.262136 31 TS dt 0.00395333 time 0.264939 32 TS dt 0.00660476 time 0.268892 33 TS dt 0.0126727 time 0.275497 34 TS dt 0.0139527 time 0.288169 35 TS dt 0.0132832 time 0.302122 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