[petsc-users] When does DIVERGED_LINE_SEARCH Happen?

[Peter Brune]

This may be related to a bug we had reported before to petsc-maint:

https://bitbucket.org/petsc/petsc/commits/ced04f9d467b04aa83a18d3f8875c7f72c17217a

  What version of PETSc are you running?  Also, what happens if you set
-snes_stol to zero?

Thanks,

- Peter


On Mon, Mar 17, 2014 at 5:19 PM, Dafang Wang <dafang.wang at jhu.edu> wrote:

> Hi Barry,
>
> Thanks for your tips. I have read the webpage you mentioned many times
> before, but still I have been stuck on the line-search problem for weeks.
>
> I cannot guarantee my Jacobian is correct but I believe an incorrect
> Jacobian is very unlikely. My Jacobian-calculation code has been under test
> for a year with both analytical and realistic models, and the results have
> been good until recently when I ran a very realistic physical model.
>
> Also, I looked up the implementation of SNESSolve_NEWTONLS() in "ls.c".
> According to the algorithm, when the function "SNESLineSearchApply()" does
> not succeed, one may encounter two possible outcomes:
> CONVERGED_SNORM_RELATIVE (if the search step is too small) or otherwise,
> DIVERGED_LINE_SEARCH. Does this mean that both these two outcomes indicate
> that the line search fails?
>
> I ask this question because my simulation encountered many
> CONVERGED_SNORM_RELATIVE. I treated them as if my nonlinear system
> converged, accepted the nonlinear solution, and then proceeded to the next
> time step of my simulation. Apparently, such practice has worked well in
> most cases, (even when I encountered suspicious DIVERGED_LINE_SEARCH
> behaviors). However, I wonder if there are any potential pitfalls in my
> practice such as missing a nonlinear solve divergence and taking a partial
> solution as the correct solution.
>
> Thank you very much for your time and help.
>
> Best,
> Dafang
>
>
> On 03/15/2014 11:15 AM, Barry Smith wrote:
>
>>     Failed line search are almost always due to an incorrect Jacobian.
>> Please let us know if the suggestions at http://www.mcs.anl.gov/petsc/
>> documentation/faq.html#newton don't help.
>>
>>     Barry
>>
>> On Mar 14, 2014, at 8:57 PM, Dafang Wang <dafang.wang at jhu.edu> wrote:
>>
>>  Hi,
>>>
>>> Does anyone know what the error code DIVERGED_LINE_SEARCH means in the
>>> SNES nonlinear solve? Or what scenario would lead to this error code?
>>>
>>> Running a solid mechanics simulation, I found that the occurrence of
>>> DIVERGED_LINE_SEARCH was very unpredictable and sensitive to the input
>>> values to my nonlinear system, although my system should not be that
>>> unstable. As shown by the two examples below, my system diverged in one
>>> case and converged in the other, although the input values in these two
>>> cases differed by only 1e-4,
>>>
>>> Moreover, the Newton steps in the two cases were very similar up to NL
>>> step 1. Since then, however, Case 1 encountered a line-search divergence
>>> whereas Case 2 converged successfully. This is my main confusion. (Note
>>> that each residual vector contains 3e04 DOF, so when their L2 norms differ
>>> within 1e-4, the two systems should be very close.)
>>>
>>> My simulation input consists of two scalar values (p1 and p2), each of
>>> which acts as a constant pressure boundary condition.
>>>
>>> Case 1, diverge:
>>> p1= -10.190869   p2= -2.367555
>>>    NL step  0, |residual|_2 = 1.621402e-02
>>>        Line search: Using full step: fnorm 1.621401550027e-02 gnorm
>>> 7.022558235262e-05
>>>    NL step  1, |residual|_2 = 7.022558e-05
>>>        Line search: Using full step: fnorm 7.022558235262e-05 gnorm
>>> 1.636418730611e-06
>>>    NL step  2, |residual|_2 = 1.636419e-06
>>> Nonlinear solve did not converge due to DIVERGED_LINE_SEARCH iterations 2
>>> Case 2: converge:
>>> p1= -10.190747 p2= -2.367558
>>>    NL step  0, |residual|_2 = 1.621380e-02
>>>        Line search: Using full step: fnorm 1.621379778276e-02 gnorm
>>> 6.976373804153e-05
>>>    NL step  1, |residual|_2 = 6.976374e-05
>>>        Line search: Using full step: fnorm 6.976373804153e-05 gnorm
>>> 4.000992847275e-07
>>>    NL step  2, |residual|_2 = 4.000993e-07
>>>        Line search: Using full step: fnorm 4.000992847275e-07 gnorm
>>> 1.621646014441e-08
>>>    NL step  3, |residual|_2 = 1.621646e-08
>>> Nonlinear solve converged due to CONVERGED_SNORM_RELATIVE iterations 3
>>>
>>> Aside from the input values, the initial solution in both cases may
>>> differ very slightly. (Each case is one time step in a time-sequence
>>> simulation. The two cases behaved nearly identically up to the last time
>>> step before the step shown above, so their initial solutions may differ by
>>> a cumulative error but such error should be very small.)  Is it possible
>>> that little difference in initial guess leads to different local minimum
>>> regions where the line search in Case 1 failed?
>>>
>>> Any comments will be greatly appreciated.
>>>
>>> Thanks,
>>> Dafang
>>> --
>>> Dafang Wang, Ph.D
>>> Postdoctoral Fellow
>>> Institute of Computational Medicine
>>> Department of Biomedical Engineering
>>> Johns Hopkins University
>>> Hackerman Hall Room 218
>>> Baltimore, MD, 21218
>>>
>>
> --
> Dafang Wang, Ph.D
> Postdoctoral Fellow
> Institute of Computational Medicine
> Department of Biomedical Engineering
> Johns Hopkins University
> Hackerman Hall Room 218
> Baltimore, MD, 21218
>
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