<div dir="ltr"><div><span style="font-size:12.8000001907349px">Eduardo, as Matt said you problem is ill conditioned but and you might find that if you add more elements and make the mesh less anisotropic that your solve faster, and you get a better solution obviously.</span><br></div><div><br></div><div>I'm not sure what options there are for better discretization but you can probably do a lot better by using better solver (parameters). I would start with:</div><div><br></div><div><div>-ksp_type cg</div><div>-pc_type gamg</div><div>-pc_gamg_agg_nsmooths 1<br></div><div>-pc_gamg_threshold 0.02 # [0 - 0.1]</div><div>#-mg_levels_ksp_type richardson</div><div>-mg_levels_ksp_type chebyshev<br></div><div>-mg_levels_pc_type sor</div><div>#-mg_levels_pc_type jacobi<br></div><div>-mg_levels_ksp_max_it 2 # [1-8]</div></div><div><br></div><div>Experiment with the two # parameters. If you scan you should find a minima for each. And you might try the commented out smoother parameters.</div><div><br></div><div>Mark</div><div><br></div><div><br></div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Jun 2, 2015 at 9:42 AM, Matthew Knepley <span dir="ltr"><<a href="mailto:knepley@gmail.com" target="_blank">knepley@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div class="gmail_extra"><div class="gmail_quote"><span class="">On Mon, Jun 1, 2015 at 11:24 PM, Eduardo <span dir="ltr"><<a href="mailto:erocha.ssa@gmail.com" target="_blank">erocha.ssa@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">I am solving a FEM solid mechanics linear elasticity model, for now the only problem is the mesh that has needle-shaped and very flat elements. Have you any suggestion of preconditioner (and references).<div></div></div></blockquote><div><br></div></span><div>The problem here is your discretization. WIth quasi-regular elements, -pc_type gamg works fine. However, with flat elements, your FEM</div><div>basis becomes very ill-conditioned since the normal basis functions are almost linearly dependent. I think the best use of time here is</div><div>to investigate better discretization strategies for this problem, since no solver is really going to help you.</div><div><br></div><div> Thanks,</div><div><br></div><div> Matt</div><span class=""><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div>Thanks,</div><div>Eduardo</div></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Jun 2, 2015 at 4:11 AM, Barry Smith <span dir="ltr"><<a href="mailto:bsmith@mcs.anl.gov" target="_blank">bsmith@mcs.anl.gov</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><span><br>
> On Jun 1, 2015, at 4:06 PM, Eduardo <<a href="mailto:erocha.ssa@gmail.com" target="_blank">erocha.ssa@gmail.com</a>> wrote:<br>
><br>
> I am solving a linear system for which the preconditioned residual decreases, but the true residual increases (or have an erratic behavior). According to Petsc FAQ, this is due to a preconditioner that is singular or close to singular. What can I do in this case? I used GMRES with ILU preconditioner.<br>
</span> ^^^^^^^^^^^^^^^<br>
<span>><br>
> Incidentally, I tried to solve a smaller system with a direct solver (superlu_dist) and it ran, so the system apparently is not singular.<br>
<br>
</span> ILU can produce very badly conditioned (one could say singular PRECONDITIONER) from not singular sparse matrices. So it doesn't have anything to do with the system itself being singular.<br>
<br>
What type of problem are you solving? Different problems need different preconditioners.<br>
<br>
Barry<br>
<br>
<br>
<br>
><br>
> Thanks in advance,<br>
> Eduardo<br>
<br>
</blockquote></div><br></div>
</div></div></blockquote></span></div><br><br clear="all"><span class=""><div><br></div>-- <br><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>
</span></div></div>
</blockquote></div><br></div>