<div dir="ltr"><div class="gmail_quote"><div dir="ltr">On Mon, Dec 24, 2018 at 9:54 AM Yingjie Wu via petsc-users <<a href="mailto:petsc-users@mcs.anl.gov">petsc-users@mcs.anl.gov</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div>Dear Petsc developers:</div><div>Hi,</div><div>Recently I encounter an error message, but I don't know how to solve it. I solve a problem of a system of nonlinear equations in which the coefficients of the system vary with variables. The Args are:</div><div> mpiexec -n 1 ./myprogram -snes_mf_operator -snes_view -snes_converged_reason -snes_monitor -ksp_converged_reason -ksp_monitor -ksp_rtol 0.1 -snes_rtol 1e-8 -snes_max_funcs 10000000000 -snes_max_it 10000 -pc_factor_levels 6</div></div></div></div></div></blockquote><div><br></div><div>It looks like your Jacobian is wrong. In order to confirm this, I would</div><div><br></div><div> a) Try it with exact linear solves, -pc_type lu</div><div><br></div><div> b) Check it against an FD Jacobian, -snes_test_jacobian</div><div><br></div><div> Matt</div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div>The log is :</div><div><div style="margin-left:40px"><font size="2">0 SNES Function norm 2.818062118573e+07 <br> 0 KSP Residual norm 1.967792312615e+05 <br> 1 KSP Residual norm 3.423312208841e+03 <br> Linear solve converged due to CONVERGED_RTOL iterations 1<br> 1 SNES Function norm 2.818049788401e+07 <br> 0 KSP Residual norm 1.960830037415e+05 <br> 1 KSP Residual norm 3.458649556419e+03 <br> Linear solve converged due to CONVERGED_RTOL iterations 1<br>Nonlinear solve did not converge due to DIVERGED_LINE_SEARCH iterations 1<br>SNES Object: 1 MPI processes<br> type: newtonls<br> maximum iterations=10000, maximum function evaluations=1410065408<br> tolerances: relative=1e-08, absolute=1e-50, solution=1e-08<br> total number of linear solver iterations=2<br> total number of function evaluations=27<br> norm schedule ALWAYS<br> SNESLineSearch Object: 1 MPI processes<br> type: bt<br> interpolation: cubic<br> alpha=1.000000e-04<br> maxstep=1.000000e+08, minlambda=1.000000e-12<br> tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08<br> maximum iterations=40<br> KSP Object: 1 MPI processes<br> type: gmres<br> restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement<br> happy breakdown tolerance 1e-30<br> maximum iterations=10000, initial guess is zero<br> tolerances: relative=0.1, absolute=1e-50, divergence=10000.<br> left preconditioning<br> using PRECONDITIONED norm type for convergence test<br> PC Object: 1 MPI processes<br> type: ilu<br> out-of-place factorization<br> 6 levels of fill<br> tolerance for zero pivot 2.22045e-14<br> matrix ordering: natural<br> factor fill ratio given 1., needed 4.29616<br> Factored matrix follows:<br> Mat Object: 1 MPI processes<br> type: seqaij<br> rows=11368, cols=11368<br> package used to perform factorization: petsc<br> total: nonzeros=183764, allocated nonzeros=183764<br> total number of mallocs used during MatSetValues calls =0<br> not using I-node routines<br> linear system matrix followed by preconditioner matrix:<br> Mat Object: 1 MPI processes<br> type: mffd<br> rows=11368, cols=11368<br> Matrix-free approximation:<br> err=1.49012e-08 (relative error in function evaluation)<br> Using wp compute h routine<br> Does not compute normU<br> Mat Object: 1 MPI processes<br> type: seqaij<br> rows=11368, cols=11368<br> total: nonzeros=42774, allocated nonzeros=56840<br> total number of mallocs used during MatSetValues calls =0<br> not using I-node routines<br></font><br></div></div><div><br></div><div>I don't know what causes Line_Search to diverge.</div><div>The Ksp_rtol setting in the program is very small because I find that linear-step convergence is not good.</div><div><br></div><div>My best wishes for Christmas,</div><div>Yingjie<br></div></div></div></div></div>
</blockquote></div><br clear="all"><div><br></div>-- <br><div dir="ltr" class="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div>What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead.<br>-- Norbert Wiener</div><div><br></div><div><a href="http://www.cse.buffalo.edu/~knepley/" target="_blank">https://www.cse.buffalo.edu/~knepley/</a><br></div></div></div></div></div></div></div></div>