[petsc-users] how to speed up convergence?
Konstantinos Kontzialis
ckontzialis at lycos.com
Thu Nov 10 10:25:17 CST 2011
Dear all,
I use the DG method for simulationg the flow over a cylinder at M =
0.2 and Re=250. I use and implicit scheme.
I run my code as follows:
mpiexec -n 8 ./hoac cylinder -snes_mf_operator -llf_flux -n_out 2
-end_time 0.4 -implicit -pc_type asm -sub_pc_type ilu
-sub_pc_factor_mat_ordering_type rcm -sub_pc_factor_reuse_ordering
-sub_pc_factor_reuse_fill -gll -ksp_type fgmres -sub_pc_factor_levels 0
-snes_monitor -snes_converged_reason -ksp_converged_reason -ts_view
-ksp_pc_side right -sub_pc_factor_nonzeros_along_diagonal -dt 1.0e-3
-ts_type arkimex -ksp_gmres_restart 100 -ksp_max_it 500 -snes_max_fail
100 -snes_max_linear_solve_fail 100
and I get:
**********************************************************************
METIS 4.0.3 Copyright 1998, Regents of the University of Minnesota
Graph Information ---------------------------------------------------
Name: mesh.graph, #Vertices: 1680, #Edges: 3280, #Parts: 8
Recursive Partitioning... -------------------------------------------
8-way Edge-Cut: 177, Balance: 1.01
Timing Information --------------------------------------------------
I/O: 0.000
Partitioning: 0.000 (PMETIS time)
Total: 0.000
**********************************************************************
Approximation order = 2
# DOF = 115200
# nodes in mesh = 1680
# elements in mesh = 1600
Navier-Stokes solution
Using LLF flux
Linear solve converged due to CONVERGED_RTOL iterations 1
Timestep 0: dt = 0.001, T = 0, Res[rho] = 0.966549, Res[rhou] =
6.11366, Res[rhov] = 0.507325, Res[E] = 2.44463, CFL = 0.942045
0 SNES Function norm 3.203604511352e+03
Linear solve did not converge due to DIVERGED_ITS iterations 500
1 SNES Function norm 3.440800722147e+02
Linear solve did not converge due to DIVERGED_ITS iterations 500
2 SNES Function norm 2.008355246473e+02
Linear solve did not converge due to DIVERGED_ITS iterations 500
3 SNES Function norm 1.177925999321e+02
as you may see the step size is quite small for this problem and I use
and inexact solution for the linear part of the newton iterations.
Furthermore, I compute numerically the jacobian of the matrix using
coloring.
Is there a tuning parameter I should set differently or use something else?
Thank you,
Kostas
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