Okay, I pushed Cheby(2)+SOR as the default smoother, with Cheby targeting the interval [0.1*emax, 1.1*emax].<div><br></div><div><a href="http://petsc.cs.iit.edu/petsc/petsc-dev/rev/234274ab894d">http://petsc.cs.iit.edu/petsc/petsc-dev/rev/234274ab894d</a></div>
<div><a href="http://petsc.cs.iit.edu/petsc/petsc-dev/rev/3212aa40b0ef">http://petsc.cs.iit.edu/petsc/petsc-dev/rev/3212aa40b0ef</a> (updating tests)<br><div><br></div><div>Its effect on convergence is varied. For smooth elliptic problems, it tends to be better to target [emax/coarsening_ratio,1.1*emax]. For hyperbolic problems, it's also often better to target a smaller range because then the damping region extends further from the real axis.</div>
<div><br></div><div>The default configuration of Chebyshev now does eigenvalue estimation. You have to (programmatically or via command line) manually set eigenvalues to avoid estimation. I think that's okay because the old [0.01, 100] wasn't much use anyway. We'll make the eigenvalue estimation faster/more parallel later.</div>
<div><br></div><div>I have disabled norms and convergence tests for the smoother by default because those are extra reductions that are best avoided. If you want to monitor norms, you have to explicitly turn them on (e.g. -mg_levels_ksp_norm_type unpreconditioned).</div>
<div><br><div class="gmail_quote">On Wed, May 23, 2012 at 2:52 PM, Jed Brown <span dir="ltr"><<a href="mailto:jedbrown@mcs.anl.gov" target="_blank">jedbrown@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">
<div class="im">On Wed, May 23, 2012 at 2:26 PM, 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">
<br>
This looks good:<br>
<div><br>
$ $base -mg_levels_ksp_type chebyshev -mg_levels_ksp_chebyshev_estimate_eigenvalues 0.1,1.1 -mg_levels_ksp_max_it 2 -mg_levels_pc_type sor<br>
lid velocity = 100, prandtl # = 1, grashof # = 10000<br>
Linear solve converged due to CONVERGED_RTOL iterations 10<br>
Linear solve converged due to CONVERGED_RTOL iterations 7<br>
Linear solve converged due to CONVERGED_RTOL iterations 8<br>
Linear solve converged due to CONVERGED_RTOL iterations 8<br>
Linear solve converged due to CONVERGED_RTOL iterations 9<br>
Linear solve converged due to CONVERGED_RTOL iterations 9<br>
Linear solve converged due to CONVERGED_RTOL iterations 8<br>
Linear solve converged due to CONVERGED_RTOL iterations 8<br>
Linear solve converged due to CONVERGED_RTOL iterations 7<br>
Number of SNES iterations = 9<br>
<br>
</div> I assume it is independent of the number of levels of refinement?<br></blockquote><div><br></div></div><div><div>$ $base -da_refine 0 -snes_grid_sequence 5 -mg_levels_ksp_type chebyshev -mg_levels_ksp_chebyshev_estimate_eigenvalues 0.1,1.1 -mg_levels_ksp_max_it 2 -mg_levels_pc_type sor</div>
<div class="im">
<div>lid velocity = 100, prandtl # = 1, grashof # = 10000</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 13</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 7</div>
<div> Linear solve converged due to CONVERGED_RTOL iterations 8</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 9</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 7</div>
<div> Linear solve converged due to CONVERGED_RTOL iterations 8</div><div> Linear solve converged due to CONVERGED_RTOL iterations 10</div><div> Linear solve converged due to CONVERGED_RTOL iterations 7</div>
</div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 12</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 8</div></div><div class="im">
<div> Linear solve converged due to CONVERGED_RTOL iterations 11</div>
<div> Linear solve converged due to CONVERGED_RTOL iterations 11</div><div> Linear solve converged due to CONVERGED_RTOL iterations 11</div><div> Linear solve converged due to CONVERGED_RTOL iterations 11</div>
<div> Linear solve converged due to CONVERGED_RTOL iterations 11</div><div> Linear solve converged due to CONVERGED_RTOL iterations 11</div></div><div> Linear solve converged due to CONVERGED_RTOL iterations 14</div>
<div class="im">
<div> Linear solve converged due to CONVERGED_RTOL iterations 11</div><div> Linear solve converged due to CONVERGED_RTOL iterations 11</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 10</div>
</div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 9</div><div> Linear solve converged due to CONVERGED_RTOL iterations 8</div><div> Linear solve converged due to CONVERGED_RTOL iterations 8</div>
<div> Linear solve converged due to CONVERGED_RTOL iterations 7</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 8</div><div> Linear solve converged due to CONVERGED_RTOL iterations 8</div>
</div><div class="im"><div>
Linear solve converged due to CONVERGED_RTOL iterations 6</div><div> Linear solve converged due to CONVERGED_RTOL iterations 7</div><div> Linear solve converged due to CONVERGED_RTOL iterations 6</div></div><div class="im">
<div> Linear solve converged due to CONVERGED_RTOL iterations 11</div>
</div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 7</div></div><div class="im"><div> Linear solve converged due to CONVERGED_RTOL iterations 5</div><div> Linear solve converged due to CONVERGED_RTOL iterations 5</div>
</div><div>Number of SNES iterations = 4</div></div></blockquote></div><br></div></div>