[petsc-users] Problem with AMG packages
Barry Smith
bsmith at mcs.anl.gov
Tue Oct 8 16:16:55 CDT 2013
We need the output from running with -log_summary -pc_mg_log
Also you can run with PETSc's AMG called GAMG (run with -pc_type gamg) This will give the most useful information about where it is spending the time.
Barry
On Oct 8, 2013, at 4:11 PM, Pierre Jolivet <jolivet at ann.jussieu.fr> wrote:
> Dear all,
> I'm trying to compare linear solvers for a simple Poisson equation in 3D.
> I thought that MG was the way to go, but looking at my log, the
> performance looks abysmal (I know that the matrices are way too small but
> if I go bigger, it just never performs a single iteration ..). Even though
> this is neither the BoomerAMG nor the ML mailing list, could you please
> tell me if PETSc sets some default flags that make the setup for those
> solvers so slow for this simple problem ? The performance of (G)ASM is in
> comparison much better.
>
> Thanks in advance for your help.
>
> PS: first the BoomerAMG log, then ML (much more verbose, sorry).
>
> 0 KSP Residual norm 1.599647112604e+00
> 1 KSP Residual norm 5.450838232404e-02
> 2 KSP Residual norm 3.549673478318e-03
> 3 KSP Residual norm 2.901826808841e-04
> 4 KSP Residual norm 2.574235778729e-05
> 5 KSP Residual norm 2.253410171682e-06
> 6 KSP Residual norm 1.871067784877e-07
> 7 KSP Residual norm 1.681162800670e-08
> 8 KSP Residual norm 2.120841512414e-09
> KSP Object: 2048 MPI processes
> type: gmres
> GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> Orthogonalization with no iterative refinement
> GMRES: happy breakdown tolerance 1e-30
> maximum iterations=200, initial guess is zero
> tolerances: relative=1e-08, absolute=1e-50, divergence=10000
> left preconditioning
> using PRECONDITIONED norm type for convergence test
> PC Object: 2048 MPI processes
> type: hypre
> HYPRE BoomerAMG preconditioning
> HYPRE BoomerAMG: Cycle type V
> HYPRE BoomerAMG: Maximum number of levels 25
> HYPRE BoomerAMG: Maximum number of iterations PER hypre call 1
> HYPRE BoomerAMG: Convergence tolerance PER hypre call 0
> HYPRE BoomerAMG: Threshold for strong coupling 0.25
> HYPRE BoomerAMG: Interpolation truncation factor 0
> HYPRE BoomerAMG: Interpolation: max elements per row 0
> HYPRE BoomerAMG: Number of levels of aggressive coarsening 0
> HYPRE BoomerAMG: Number of paths for aggressive coarsening 1
> HYPRE BoomerAMG: Maximum row sums 0.9
> HYPRE BoomerAMG: Sweeps down 1
> HYPRE BoomerAMG: Sweeps up 1
> HYPRE BoomerAMG: Sweeps on coarse 1
> HYPRE BoomerAMG: Relax down symmetric-SOR/Jacobi
> HYPRE BoomerAMG: Relax up symmetric-SOR/Jacobi
> HYPRE BoomerAMG: Relax on coarse Gaussian-elimination
> HYPRE BoomerAMG: Relax weight (all) 1
> HYPRE BoomerAMG: Outer relax weight (all) 1
> HYPRE BoomerAMG: Using CF-relaxation
> HYPRE BoomerAMG: Measure type local
> HYPRE BoomerAMG: Coarsen type Falgout
> HYPRE BoomerAMG: Interpolation type classical
> linear system matrix = precond matrix:
> Matrix Object: 2048 MPI processes
> type: mpiaij
> rows=4173281, cols=4173281
> total: nonzeros=102576661, allocated nonzeros=102576661
> total number of mallocs used during MatSetValues calls =0
> not using I-node (on process 0) routines
> --- system solved with PETSc (in 1.005199e+02 seconds)
>
> 0 KSP Residual norm 2.368804472986e-01
> 1 KSP Residual norm 5.676430019132e-02
> 2 KSP Residual norm 1.898005876002e-02
> 3 KSP Residual norm 6.193922902926e-03
> 4 KSP Residual norm 2.008448794493e-03
> 5 KSP Residual norm 6.390465670228e-04
> 6 KSP Residual norm 2.157709394389e-04
> 7 KSP Residual norm 7.295973819979e-05
> 8 KSP Residual norm 2.358343271482e-05
> 9 KSP Residual norm 7.489696222066e-06
> 10 KSP Residual norm 2.390946857593e-06
> 11 KSP Residual norm 8.068086385140e-07
> 12 KSP Residual norm 2.706607789749e-07
> 13 KSP Residual norm 8.636910863376e-08
> 14 KSP Residual norm 2.761981175852e-08
> 15 KSP Residual norm 8.755459874369e-09
> 16 KSP Residual norm 2.708848598341e-09
> 17 KSP Residual norm 8.968748876265e-10
> KSP Object: 2048 MPI processes
> type: gmres
> GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> Orthogonalization with no iterative refinement
> GMRES: happy breakdown tolerance 1e-30
> maximum iterations=200, initial guess is zero
> tolerances: relative=1e-08, absolute=1e-50, divergence=10000
> left preconditioning
> using PRECONDITIONED norm type for convergence test
> PC Object: 2048 MPI processes
> type: ml
> MG: type is MULTIPLICATIVE, levels=3 cycles=v
> Cycles per PCApply=1
> Using Galerkin computed coarse grid matrices
> Coarse grid solver -- level -------------------------------
> KSP Object: (mg_coarse_) 2048 MPI processes
> type: preonly
> maximum iterations=1, initial guess is zero
> tolerances: relative=1e-05, absolute=1e-50, divergence=10000
> left preconditioning
> using NONE norm type for convergence test
> PC Object: (mg_coarse_) 2048 MPI processes
> type: redundant
> Redundant preconditioner: First (color=0) of 2048 PCs follows
> KSP Object: (mg_coarse_redundant_) 1 MPI processes
> type: preonly
> maximum iterations=10000, initial guess is zero
> tolerances: relative=1e-05, absolute=1e-50, divergence=10000
> left preconditioning
> using NONE norm type for convergence test
> PC Object: (mg_coarse_redundant_) 1 MPI processes
> type: lu
> LU: out-of-place factorization
> tolerance for zero pivot 2.22045e-14
> using diagonal shift on blocks to prevent zero pivot
> matrix ordering: nd
> factor fill ratio given 5, needed 4.38504
> Factored matrix follows:
> Matrix Object: 1 MPI processes
> type: seqaij
> rows=2055, cols=2055
> package used to perform factorization: petsc
> total: nonzeros=2476747, allocated nonzeros=2476747
> total number of mallocs used during MatSetValues calls =0
> using I-node routines: found 1638 nodes, limit used is 5
> linear system matrix = precond matrix:
> Matrix Object: 1 MPI processes
> type: seqaij
> rows=2055, cols=2055
> total: nonzeros=564817, allocated nonzeros=1093260
> total number of mallocs used during MatSetValues calls =0
> not using I-node routines
> linear system matrix = precond matrix:
> Matrix Object: 2048 MPI processes
> type: mpiaij
> rows=2055, cols=2055
> total: nonzeros=564817, allocated nonzeros=564817
> total number of mallocs used during MatSetValues calls =0
> not using I-node (on process 0) routines
> Down solver (pre-smoother) on level 1 -------------------------------
> KSP Object: (mg_levels_1_) 2048 MPI processes
> type: richardson
> Richardson: damping factor=1
> maximum iterations=2
> tolerances: relative=1e-05, absolute=1e-50, divergence=10000
> left preconditioning
> using nonzero initial guess
> using NONE norm type for convergence test
> PC Object: (mg_levels_1_) 2048 MPI processes
> type: sor
> SOR: type = local_symmetric, iterations = 1, local iterations = 1,
> omega = 1
> linear system matrix = precond matrix:
> Matrix Object: 2048 MPI processes
> type: mpiaij
> rows=30194, cols=30194
> total: nonzeros=3368414, allocated nonzeros=3368414
> total number of mallocs used during MatSetValues calls =0
> not using I-node (on process 0) routines
> Up solver (post-smoother) same as down solver (pre-smoother)
> Down solver (pre-smoother) on level 2 -------------------------------
> KSP Object: (mg_levels_2_) 2048 MPI processes
> type: richardson
> Richardson: damping factor=1
> maximum iterations=2
> tolerances: relative=1e-05, absolute=1e-50, divergence=10000
> left preconditioning
> using nonzero initial guess
> using NONE norm type for convergence test
> PC Object: (mg_levels_2_) 2048 MPI processes
> type: sor
> SOR: type = local_symmetric, iterations = 1, local iterations = 1,
> omega = 1
> linear system matrix = precond matrix:
> Matrix Object: 2048 MPI processes
> type: mpiaij
> rows=531441, cols=531441
> total: nonzeros=12476324, allocated nonzeros=12476324
> total number of mallocs used during MatSetValues calls =0
> not using I-node (on process 0) routines
> Up solver (post-smoother) same as down solver (pre-smoother)
> linear system matrix = precond matrix:
> Matrix Object: 2048 MPI processes
> type: mpiaij
> rows=531441, cols=531441
> total: nonzeros=12476324, allocated nonzeros=12476324
> total number of mallocs used during MatSetValues calls =0
> not using I-node (on process 0) routines
> --- system solved with PETSc (in 2.407844e+02 seconds)
>
>
More information about the petsc-users
mailing list