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 <[email protected]> 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 <[email protected]> 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 >
