In looking at the logs for icc it looks like Hong has done a little messing around with the shifting tolerance:
- ((PC_Factor*)icc)->info.shiftamount = 1.e-12; - ((PC_Factor*)icc)->info.zeropivot = 1.e-12; + ((PC_Factor*)icc)->info.shiftamount = 100.0*PETSC_MACHINE_EPSILON; + ((PC_Factor*)icc)->info.zeropivot = 100.0*PETSC_MACHINE_EPSILON; This looks like it would lower the shifting and drop tolerance. You might set these back to 1e-12. http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/PC/PCFactorSetZeroPivot.html http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/PC/PCFactorSetShiftAmount.html BTW, using an indefinite preconditioner, that has to be fixed with is-this-a-small-number kind of code, on a warm and fluffy Laplacian is not recommended. As I said before I would just use jacobi -- god gave you an easy problem. Exploit it. On Apr 17, 2013, at 7:22 PM, "Mark F. Adams" <mark.adams at columbia.edu> wrote: > > > Begin forwarded message: > >> From: "Christon, Mark A" <christon at lanl.gov> >> Subject: Re: [petsc-users] Any changes in ML usage between 3.1-p8 -> 3.3-p6? >> Date: April 17, 2013 7:06:11 PM EDT >> To: "Mark F. Adams" <mark.adams at columbia.edu>, "Bakosi, Jozsef" <jbakosi >> at lanl.gov> >> >> Hi Mark, >> >> Yes, looks like the new version does a little better after 2 iterations, but >> at the 8th iteration, the residuals increase:( >> >> I suspect this is why PETSc is whining about an indefinite preconditioner. >> >> Something definitely changes as we've had about 6-8 regression tests start >> failing that have been running flawlessly with ML + PETSc 3.1-p8 for almost >> two years. >> >> If we can understand what changed, we probably have a fighting chance of >> correcting it ? assuming it's some solver setting for PETSc that we're not >> currently using. >> >> - Mark >> >> -- >> Mark A. Christon >> Computational Physics Group (CCS-2) >> Computer, Computational and Statistical Sciences Division >> Los Alamos National Laboratory >> MS D413, P.O. Box 1663 >> Los Alamos, NM 87545 >> >> E-mail: christon at lanl.gov >> Phone: (505) 663-5124 >> Mobile: (505) 695-5649 (voice mail) >> >> International Journal for Numerical Methods in Fluids >> >> From: "Mark F. Adams" <mark.adams at columbia.edu> >> Date: Wed, 17 Apr 2013 18:51:02 -0400 >> To: PETSc users list <petsc-users at mcs.anl.gov> >> Cc: "Mark A. Christon" <christon at lanl.gov> >> Subject: Re: [petsc-users] Any changes in ML usage between 3.1-p8 -> 3.3-p6? >> >>> I see you are using icc. Perhaps our icc changed a bit between versions. >>> These results look like both solves are working and the old does a little >>> better (after two iterations). >>> >>> Try using jacobi instead of icc. >>> >>> >>> On Apr 17, 2013, at 6:21 PM, Jozsef Bakosi <jbakosi at lanl.gov> wrote: >>> >>>>> On 04.17.2013 15:38, Matthew Knepley wrote: >>>>>> On 04.17.2013 14:26, Jozsef Bakosi wrote: >>>>>>> Mark F. Adams mark.adams at columbia.edu >>>>>>> Wed Apr 17 14:25:04 CDT 2013 >>>>>>> 2) If you get "Indefinite PC" (I am guessing from using CG) it is >>>>>>> because the >>>>>>> preconditioner >>>>>>> really is indefinite (or possible non-symmetric). We improved the >>>>>>> checking >>>>>>> for this in one >>>>>>> of those releases. >>>>>>> AMG does not guarantee an SPD preconditioner so why persist in trying >>>>>>> to use >>>>>>> CG? >>>>>>> AMG is positive if everything is working correctly. >>>>>>> Are these problems only semidefinite? Singular systems can give erratic >>>>>>> behavior. >>>>>> It is a Laplace operator from Galerkin finite elements. And the PC is >>>>>> fine on >>>>>> ranks 1, 2, 3, and 5 -- indefinite only on 4. I think we can safely say >>>>>> that the >>>>>> same PC should be positive on 4 as well. >>>>> Why is it safe? Because it sounds plausible? Mathematics is replete with >>>>> things >>>>> that sound plausible and are false. Are there proofs that suggest this? >>>>> Is there >>>>> computational evidence? Why would I believe you? >>>> Okay, so here is some additional information: >>>> I tried both old and new PETSc versions again, but now only taking 2 >>>> iterations >>>> (both with 4 CPUs) and checked the residuals. I get the same exact PC from >>>> ML in >>>> both cases, however, the residuals are different after both iterations: >>>> Please do a diff on the attached files and you can verify that the ML >>>> diagnostics are exactly the same: same max eigenvalues, nodes aggregated, >>>> etc, >>>> while the norm coming out of the solver at the end at both iterations are >>>> different. >>>> We reproduced the same exact behavior on two different linux platforms. >>>> Once again: same application source code, same ML source code, different >>>> PETSc: >>>> 3.1-p8 vs. 3.3-p6. >>>> <old.out><new.out> >>> >>> > -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20130417/ae8f9771/attachment-0001.html>
