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: gamg type is MULTIPLICATIVE, levels=2 cycles=v Cycles per PCApply=1 Using externally compute Galerkin coarse grid matrices GAMG specific options Threshold for dropping small values in graph on each level = -1. -1. Threshold scaling factor for each level not specified = 1. AGG specific options Number of levels of aggressive coarsening 0 MatCoarsen Object: (pc_gamg_) 1 MPI process type: hem 4 matching steps with threshold = -1. HEM aggregator lists are not available Number smoothing steps to construct prolongation 1 Complexity: grid = 1.125 operator = 1.0625 Per-level complexity: op = operator, int = interpolation #equations | #active PEs | avg nnz/row op | avg nnz/row int 2 1 2 0 16 1 4 2 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: bjacobi number of blocks = 1 Local solver information for each block is in the following KSP and PC objects: [0] number of local blocks = 1, first local block number = 0 [0] local block number 0 KSP Object: (mg_coarse_sub_) 1 MPI process type: preonly maximum iterations=1, initial guess is zero tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning not checking for convergence PC Object: (mg_coarse_sub_) 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. Factored matrix: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 package used to perform factorization: petsc total: nonzeros=4, allocated nonzeros=4 using I-node routines: found 1 nodes, limit used is 5 linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 - - - - - - - - - - - - - - - - - - linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 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 0.514268, max 5.65695 eigenvalues provided (min 0.299461, max 5.14268) with transform: [0. 0.1; 0. 1.1] maximum iterations=2, 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: jacobi type DIAGONAL Vec Object: 1 MPI process type: seq length=16 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 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=16, cols=16 total: nonzeros=64, allocated nonzeros=64 total number of mallocs used during MatSetValues calls=0 not using I-node routines 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: gamg type is MULTIPLICATIVE, levels=2 cycles=v Cycles per PCApply=1 Using externally compute Galerkin coarse grid matrices GAMG specific options Threshold for dropping small values in graph on each level = -1. -1. Threshold scaling factor for each level not specified = 1. AGG specific options Number of levels of aggressive coarsening 0 MatCoarsen Object: (pc_gamg_) 1 MPI process type: hem 4 matching steps with threshold = -1. HEM aggregator lists are not available Number smoothing steps to construct prolongation 1 Complexity: grid = 1.125 operator = 1.0625 Per-level complexity: op = operator, int = interpolation #equations | #active PEs | avg nnz/row op | avg nnz/row int 2 1 2 0 16 1 4 2 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: bjacobi number of blocks = 1 Local solver information for each block is in the following KSP and PC objects: [0] number of local blocks = 1, first local block number = 0 [0] local block number 0 KSP Object: (mg_coarse_sub_) 1 MPI process type: preonly maximum iterations=1, initial guess is zero tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning not checking for convergence PC Object: (mg_coarse_sub_) 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. Factored matrix: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 package used to perform factorization: petsc total: nonzeros=4, allocated nonzeros=4 using I-node routines: found 1 nodes, limit used is 5 linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 - - - - - - - - - - - - - - - - - - linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 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 0.159372, max 1.75309 eigenvalues estimated via gmres: min 0.406283, max 1.59372 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=2, 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: jacobi type DIAGONAL Vec Object: 1 MPI process type: seq length=16 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 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=16, cols=16 total: nonzeros=64, allocated nonzeros=64 total number of mallocs used during MatSetValues calls=0 not using I-node routines 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: gamg type is MULTIPLICATIVE, levels=2 cycles=v Cycles per PCApply=1 Using externally compute Galerkin coarse grid matrices GAMG specific options Threshold for dropping small values in graph on each level = -1. -1. Threshold scaling factor for each level not specified = 1. AGG specific options Number of levels of aggressive coarsening 0 MatCoarsen Object: (pc_gamg_) 1 MPI process type: hem 4 matching steps with threshold = -1. HEM aggregator lists are not available Number smoothing steps to construct prolongation 1 Complexity: grid = 1.125 operator = 1.0625 Per-level complexity: op = operator, int = interpolation #equations | #active PEs | avg nnz/row op | avg nnz/row int 2 1 2 0 16 1 4 2 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: bjacobi number of blocks = 1 Local solver information for each block is in the following KSP and PC objects: [0] number of local blocks = 1, first local block number = 0 [0] local block number 0 KSP Object: (mg_coarse_sub_) 1 MPI process type: preonly maximum iterations=1, initial guess is zero tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning not checking for convergence PC Object: (mg_coarse_sub_) 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. Factored matrix: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 package used to perform factorization: petsc total: nonzeros=4, allocated nonzeros=4 using I-node routines: found 1 nodes, limit used is 5 linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 - - - - - - - - - - - - - - - - - - linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 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 0.160581, max 1.76639 eigenvalues estimated via gmres: min 0.394193, max 1.60581 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=2, 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: jacobi type DIAGONAL Vec Object: 1 MPI process type: seq length=16 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 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=16, cols=16 total: nonzeros=64, allocated nonzeros=64 total number of mallocs used during MatSetValues calls=0 not using I-node routines 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: gamg type is MULTIPLICATIVE, levels=2 cycles=v Cycles per PCApply=1 Using externally compute Galerkin coarse grid matrices GAMG specific options Threshold for dropping small values in graph on each level = -1. -1. Threshold scaling factor for each level not specified = 1. AGG specific options Number of levels of aggressive coarsening 0 MatCoarsen Object: (pc_gamg_) 1 MPI process type: hem 4 matching steps with threshold = -1. HEM aggregator lists are not available Number smoothing steps to construct prolongation 1 Complexity: grid = 1.125 operator = 1.0625 Per-level complexity: op = operator, int = interpolation #equations | #active PEs | avg nnz/row op | avg nnz/row int 2 1 2 0 16 1 4 2 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: bjacobi number of blocks = 1 Local solver information for each block is in the following KSP and PC objects: [0] number of local blocks = 1, first local block number = 0 [0] local block number 0 KSP Object: (mg_coarse_sub_) 1 MPI process type: preonly maximum iterations=1, initial guess is zero tolerances: relative=1e-05, absolute=1e-50, divergence=10000. left preconditioning not checking for convergence PC Object: (mg_coarse_sub_) 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. Factored matrix: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 package used to perform factorization: petsc total: nonzeros=4, allocated nonzeros=4 using I-node routines: found 1 nodes, limit used is 5 linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 - - - - - - - - - - - - - - - - - - linear system matrix, which is also used to construct the preconditioner: Mat Object: (mg_coarse_sub_) 1 MPI process type: seqaij rows=2, cols=2 total: nonzeros=4, allocated nonzeros=4 total number of mallocs used during MatSetValues calls=0 using I-node routines: found 1 nodes, limit used is 5 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 0.160614, max 1.76675 eigenvalues estimated via gmres: min 0.393863, max 1.60614 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=2, 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: jacobi type DIAGONAL Vec Object: 1 MPI process type: seq length=16 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 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=16, cols=16 total: nonzeros=64, allocated nonzeros=64 total number of mallocs used during MatSetValues calls=0 not using I-node routines