[petsc-users] SNES line search

[Dmitry Karpeev]

Thanks.
Dmitry.

On Wed, Oct 17, 2012 at 4:45 PM, Peter Brune <brune at mcs.anl.gov> wrote:

> Fix for the garbage in X part is in.
>
> http://petsc.cs.iit.edu/petsc/releases/petsc-3.3/rev/9d679552ef45
>
> - Peter
>
>
> On Wed, Oct 17, 2012 at 3:34 PM, Peter Brune <prbrune at gmail.com> wrote:
>
>>
>>
>> On Wed, Oct 17, 2012 at 3:01 PM, Dmitry Karpeev <karpeev at mcs.anl.gov>wrote:
>>
>>>
>>>
>>> On Wed, Oct 17, 2012 at 2:56 PM, Peter Brune <prbrune at gmail.com> wrote:
>>>
>>>>
>>>>
>>>> On Wed, Oct 17, 2012 at 2:40 PM, Dmitry Karpeev <karpeev at mcs.anl.gov>wrote:
>>>>
>>>>>
>>>>>
>>>>> On Wed, Oct 17, 2012 at 2:11 PM, Jed Brown <jedbrown at mcs.anl.gov>wrote:
>>>>>
>>>>>> On Wed, Oct 17, 2012 at 2:02 PM, Shiyuan Gu <sgu at anl.gov> wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>>     I am using petsc-3.3-p2.  For my particular equation, for the
>>>>>>> first few iterations, the residual norm is effectively reduced and the
>>>>>>> solution X is very close to the exact solution (the residual norm is e-17).
>>>>>>> Then in the next iteration, SNES_KSPSolve(....) returns a newton step very
>>>>>>> close to zero which is correct, but the line search after it fails, and the
>>>>>>> function SNESLSCheckLocalMin_Private(...) is called. In the function
>>>>>>> SNESLSCheckLocalMin_Private(),
>>>>>>> the solution vector X is rewritten to X=J^T*F where J is the
>>>>>>> Jacobian and F is the residual. Since F is very close to zero, X is also
>>>>>>> zero which is wrong.
>>>>>>> Is there a way to skip the line search?(if the line search is not
>>>>>>> performed, there would be no problem for this particular equation).  How
>>>>>>> should we handle this situation?
>>>>>>>
>>>>>>
>>>>>> You can turn off the line search with -snes_linesearch_type basic,
>>>>>> but I recommend setting an appropriate atol and stol instead, to prevent
>>>>>> attempting to solve the system more accurately than machine precision when
>>>>>> given a good initial guess.
>>>>>>
>>>>> Maybe it wouldn't be a bad idea to (a) not use the solution vector as
>>>>> a temporary in detecting the local minimum,
>>>>>
>>>>
>>>> Dumping garbage into X upon failure appears to be my careless mistake.
>>>> I'll fix it in 3.3.
>>>>
>>>>
>>>>>
>>>>>
>>>>>
>>>> (b) print the norm of the last solution before bailing out of the
>>>>> Newton loop?
>>>>>
>>>>
>>>> This can go into the -info output.
>>>>
>>> Why not (also) let SNESMonitor() be called on that last solution?
>>>
>>
>> Oh, I interpreted "norm of the solution" literally rather than "norm of
>> the function at that solution", which makes more sense.  However, as it
>> quits after failing the line search and doesn't transfer the failed
>> solution over.  This is indeed a divergence, so printing a failed norm
>> probably isn't the right solution.  You can see what the line search is
>> doing with -snes_linesearch_monitor.
>>
>> We changed the behavior in petsc-dev a little bit with respect to this
>> type of case, as we were seeing bad interaction between line search
>> divergence in the case of small step sizes and small-normed solutions with
>> the logic as it was in 3.3 and before.  This could be that type of problem,
>> where the solution is well converged and the line search cannot make more
>> progress.
>>
>> In any case, I'll fix the problem with writing garbage into the solution.
>>
>> In order to truly diagnose this, output with -snes_linesearch_monitor and
>> -snes_converged reason would be nice.
>>
>> - Peter
>>
>>
>>>
>>>
>>  Dmitry.
>>>
>>>>
>>>>
>>>> - Peter
>>>>
>>>>
>>>>>  Dmitry.
>>>>>
>>>>>>
>>>>>>
>>>>>>> Also, after the solution vector X is rewritten by
>>>>>>> SNESLSCheckLocalMin_Private(), the new residual  norm is not printed on
>>>>>>> screen (which is huge for this particular problem).  Since the residual
>>>>>>> norm printed on the screen is going to machine accuracy,  users might think
>>>>>>> that the SNESSolve converges nicely and the returned solution is correct.
>>>>>>> This seems a bit misleading in my opinion.
>>>>>>>
>>>>>>
>>>>>> Are you checking -snes_converged_reason?
>>>>>>
>>>>>>
>>>>>>>
>>>>>>> Thanks.
>>>>>>>
>>>>>>> Shiyuan
>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
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