Simon,
Thanks for the question. We would love to have such functionality in TAO,
but we do not currently have it.
For SNES, we provide SNESSetFunctionDomainError() and
SNESSetJacobianDomainError() which can be called (on any subset of the MPI
processes in the MPI communicator) to indicate such a domain error. Currently,
SNES simply checks this way (in a collective, friendly manner without extra
communication) and returns a clean SNES_DIVERGED_FUNCTION_DOMAIN via the
SNESConvergedReason. We would like at least some of the SNES solvers to handle
this better, as you suggest, by backtracking to find a valid point in the
domain.
For TS we provide TSSetFunctionDomainError(), which allows the user to pass
in a function to check if a point is in the domain. It is currently unused. I
think it should use the same approach as SNES.
So for TAO, I envision a similar TaoSetFunctionDomainError(),
TaoSetJacobianDomainError(), and TaoSetHessianDomainError(), which would allow
particular TAO solvers to "back off" but continue running as you request.
Would you be interested in collaborating with us on adding such support to
Tao? In particular, focusing exactly on the Tao solver algorithm you are using?
We don't currently have PETSc developers focusing on Tao, so can only make
progress on it by actively collaborating with others who need new/improved
functionality.
Barry
> On Dec 4, 2025, at 3:03 AM, Simon Wiesheier <[email protected]> wrote:
>
> Dear PETSc developers and users,
> I am considering using TAO’s Primal-Dual Interior-Point Method (PDIPM) for a
> constrained optimization problem in solid mechanics. The objective involves
> solving a nonlinear PDE (hyperelasticity) for each parameter vector, and for
> some parameter combinations the PDE solver may fail to converge or produce
> non-physical states.
>
> With MATLAB’s fmincon, it is possible to signal such failures by returning
> NaN/Inf for the objective, and the solver will then backtrack or try a
> different step without crashing.
>
> My questions are:
>
> How does TAO’s PDIPM handle cases where the user objective or gradient
> callback returns NaN/Inf (e.g., due to PDE solver failure)?
>
> Is there a recommended way in TAO/PETSc to gracefully signal an evaluation
> failure (like “bad point in parameter space”) so that the algorithm can back
> off and try a smaller step, instead of aborting?
>
> If the recommended pattern is not to return NaNs, what is the best practice
> in TAO for such PDE-constrained problems?
>
> Any guidance on how TAO/PDIPM is intended to behave in the presence of
> evaluation failures would be greatly appreciated.
>
> Best regards,
>
> Simon
>
