0 KSP Residual norm 811.998 1 KSP Residual norm 197.037 2 KSP Residual norm 76.0612 3 KSP Residual norm 28.3601 4 KSP Residual norm 7.64702 5 KSP Residual norm 4.00353 6 KSP Residual norm 1.74934 7 KSP Residual norm 0.751483 8 KSP Residual norm 0.28333 9 KSP Residual norm 0.0874762 10 KSP Residual norm 0.0353676 11 KSP Residual norm 0.017824 12 KSP Residual norm 0.00703599 Linear solve converged due to CONVERGED_RTOL iterations 12 KSP Object: 8 MPI processes type: cg 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: 8 MPI processes 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 = -0.01 -0.01 Threshold scaling factor for each level not specified = 1. Using parallel coarse grid solver (all coarse grid equations not put on one process) AGG specific options Number of levels of aggressive coarsening 1 Square graph aggressive coarsening MatCoarsen Object: (pc_gamg_) 8 MPI processes type: mis Number smoothing steps to construct prolongation 1 Complexity: grid = 1.054 operator = 1.07125 Per-level complexity: op = operator, int = interpolation #equations | #active PEs | avg nnz/row op | avg nnz/row int 162 4 87 0 3000 8 66 19 Coarse grid solver -- level 0 ------------------------------- KSP Object: (mg_coarse_) 8 MPI processes type: cg 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: (mg_coarse_) 8 MPI processes type: jacobi type DIAGONAL linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=162, cols=162, bs=6 total: nonzeros=14076, allocated nonzeros=14076 total number of mallocs used during MatSetValues calls=0 using nonscalable MatPtAP() implementation using I-node (on process 0) routines: found 4 nodes, limit used is 5 Down solver (pre-smoother) on level 1 ------------------------------- KSP Object: (mg_levels_1_) 8 MPI processes type: chebyshev Chebyshev polynomial of first kind eigenvalue targets used: min 0.637067, max 3.3446 eigenvalues provided (min 0.0597913, max 3.18533) with transform: [0. 0.2; 0. 1.05] 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_) 8 MPI processes type: jacobi type DIAGONAL linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=3000, cols=3000, bs=3 total: nonzeros=197568, allocated nonzeros=243000 total number of mallocs used during MatSetValues calls=0 has attached near null space using I-node (on process 0) routines: found 125 nodes, limit used is 5 Up solver (post-smoother) same as down solver (pre-smoother) linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=3000, cols=3000, bs=3 total: nonzeros=197568, allocated nonzeros=243000 total number of mallocs used during MatSetValues calls=0 has attached near null space using I-node (on process 0) routines: found 125 nodes, limit used is 5 0 KSP Residual norm 0.00811969 1 KSP Residual norm 0.00196934 2 KSP Residual norm 0.000759615 3 KSP Residual norm 0.000282977 4 KSP Residual norm 7.65127e-05 5 KSP Residual norm 4.02809e-05 6 KSP Residual norm 1.76022e-05 7 KSP Residual norm 7.54699e-06 8 KSP Residual norm 2.84038e-06 9 KSP Residual norm 8.7449e-07 10 KSP Residual norm 3.53116e-07 11 KSP Residual norm 1.7785e-07 12 KSP Residual norm 7.0347e-08 Linear solve converged due to CONVERGED_RTOL iterations 12 KSP Object: 8 MPI processes type: cg 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: 8 MPI processes 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 = -0.01 -0.01 Threshold scaling factor for each level not specified = 1. Using parallel coarse grid solver (all coarse grid equations not put on one process) AGG specific options Number of levels of aggressive coarsening 1 Square graph aggressive coarsening MatCoarsen Object: (pc_gamg_) 8 MPI processes type: mis Number smoothing steps to construct prolongation 1 Complexity: grid = 1.054 operator = 1.07125 Per-level complexity: op = operator, int = interpolation #equations | #active PEs | avg nnz/row op | avg nnz/row int 162 4 87 0 3000 8 66 19 Coarse grid solver -- level 0 ------------------------------- KSP Object: (mg_coarse_) 8 MPI processes type: cg 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: (mg_coarse_) 8 MPI processes type: jacobi type DIAGONAL linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=162, cols=162, bs=6 total: nonzeros=14076, allocated nonzeros=14076 total number of mallocs used during MatSetValues calls=0 using nonscalable MatPtAP() implementation using I-node (on process 0) routines: found 4 nodes, limit used is 5 Down solver (pre-smoother) on level 1 ------------------------------- KSP Object: (mg_levels_1_) 8 MPI processes type: chebyshev Chebyshev polynomial of first kind eigenvalue targets used: min 0.637376, max 3.34622 eigenvalues estimated via gmres: min 0.0806313, max 3.18688 eigenvalues estimated using gmres with transform: [0. 0.2; 0. 1.05] KSP Object: (mg_levels_1_esteig_) 8 MPI processes 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_) 8 MPI processes type: jacobi type DIAGONAL linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=3000, cols=3000, bs=3 total: nonzeros=197568, allocated nonzeros=243000 total number of mallocs used during MatSetValues calls=0 has attached near null space using I-node (on process 0) routines: found 125 nodes, limit used is 5 Up solver (post-smoother) same as down solver (pre-smoother) linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=3000, cols=3000, bs=3 total: nonzeros=197568, allocated nonzeros=243000 total number of mallocs used during MatSetValues calls=0 has attached near null space using I-node (on process 0) routines: found 125 nodes, limit used is 5 0 KSP Residual norm 0.00811969 1 KSP Residual norm 0.00196934 2 KSP Residual norm 0.000759615 3 KSP Residual norm 0.000282977 4 KSP Residual norm 7.65127e-05 5 KSP Residual norm 4.02809e-05 6 KSP Residual norm 1.76022e-05 7 KSP Residual norm 7.54699e-06 8 KSP Residual norm 2.84038e-06 9 KSP Residual norm 8.7449e-07 10 KSP Residual norm 3.53116e-07 11 KSP Residual norm 1.7785e-07 12 KSP Residual norm 7.0347e-08 Linear solve converged due to CONVERGED_RTOL iterations 12 KSP Object: 8 MPI processes type: cg 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: 8 MPI processes 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 = -0.01 -0.01 Threshold scaling factor for each level not specified = 1. Using parallel coarse grid solver (all coarse grid equations not put on one process) AGG specific options Number of levels of aggressive coarsening 1 Square graph aggressive coarsening MatCoarsen Object: (pc_gamg_) 8 MPI processes type: mis Number smoothing steps to construct prolongation 1 Complexity: grid = 1.054 operator = 1.07125 Per-level complexity: op = operator, int = interpolation #equations | #active PEs | avg nnz/row op | avg nnz/row int 162 4 87 0 3000 8 66 19 Coarse grid solver -- level 0 ------------------------------- KSP Object: (mg_coarse_) 8 MPI processes type: cg 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: (mg_coarse_) 8 MPI processes type: jacobi type DIAGONAL linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=162, cols=162, bs=6 total: nonzeros=14076, allocated nonzeros=14076 total number of mallocs used during MatSetValues calls=0 using nonscalable MatPtAP() implementation using I-node (on process 0) routines: found 4 nodes, limit used is 5 Down solver (pre-smoother) on level 1 ------------------------------- KSP Object: (mg_levels_1_) 8 MPI processes type: chebyshev Chebyshev polynomial of first kind eigenvalue targets used: min 0.637376, max 3.34622 eigenvalues estimated via gmres: min 0.0806313, max 3.18688 eigenvalues estimated using gmres with transform: [0. 0.2; 0. 1.05] KSP Object: (mg_levels_1_esteig_) 8 MPI processes 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_) 8 MPI processes type: jacobi type DIAGONAL linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=3000, cols=3000, bs=3 total: nonzeros=197568, allocated nonzeros=243000 total number of mallocs used during MatSetValues calls=0 has attached near null space using I-node (on process 0) routines: found 125 nodes, limit used is 5 Up solver (post-smoother) same as down solver (pre-smoother) linear system matrix, which is also used to construct the preconditioner: Mat Object: 8 MPI processes type: mpiaij rows=3000, cols=3000, bs=3 total: nonzeros=197568, allocated nonzeros=243000 total number of mallocs used during MatSetValues calls=0 has attached near null space using I-node (on process 0) routines: found 125 nodes, limit used is 5 [0]main |b-Ax|/|b|=2.425235e-04, |b|=5.391826e+00, emax=9.946388e-01