Dear Felipe,

It might be that you need to set up the preconditioner operator with an
exemplar matrix (since the identity operator doesn't know the size of the
range and domain that it's working on).

If that's not the issue then could you please try to reproduce this as a
minimal example and share it with us? The program doesn't need to produce
any meaningful result, but it would be good if it shows both the working
scenario and the problematic one. That way we could investigate further and
try to figure out what's going wrong here.

Best,
Jean-Paul

Sent from my mobile device. Please excuse my brevity and any typos.

On Wed, 16 Jun 2021, 08:50 Juan Felipe Giraldo, <[email protected]>
wrote:

> Dear Jean-Paul,
>
> Thank you for your reply and the complete information you provide me.
> Effectively, declaring the preconditioner (out-of-line) was one problem,
> but the inverse_operator function is still not matching.
>
> What I just realized is that when I compute the operator as a
> multiplication of a linear operator, an inverse operator and a linear
> operator ( for instance, when I compute the Schur complement )
>
> const auto op_S = op_BT * op_M_inv * op_B;
>
> this operator becomes to the type
> 'dealii::TrilinosWrappers::internal::LinearOperatorImplementation::TrilinosPayload'
> ,
>
> but when I compute the operator as a multiplication of other linear
> operators directly (for instance, when I compute the Schur preconditioner,
> following the procedure in step 20 )
>
> const auto op_pre = linear_operator<LA::MPI::Vector>(prec_M);
> const auto op_aS = op_BT * op_pre * op_B;
>
> this operator becomes to the type
> 'dealii::internal::LinearOperatorImplementation::EmptyPayload&'.
>
> So, If I use the inverse_operator function with the first operator (op_S),
> I can obtain the inverse without any problem,
> (const auto op_S_inv = inverse_operator(op_S, solver_S, preconditioner_S );
>
> But if I do it with the second case, it doesn't work because the functions
> are not matching.
> (const auto op_S_inv = inverse_operator(opa_S, solver_S, preconditioner_S
> );
>
> I am not sure what is happening because all the operators are declared as
> "LA::MPI::Vector".
> If you have any suggestion, would be greatly appreciated.
>
> Thank you so much,
>
> Regards,
> Felipe Giraldo
>
>
>
> El martes, 15 de junio de 2021 a las 19:16:54 UTC+8, Jean-Paul Pelteret
> escribió:
>
>> Hi again Feilpe,
>>
>> Regarding the lack of documentation, I’ve opened an issue on Github to
>> track this. You can find that here:
>> https://github.com/dealii/dealii/issues/12466
>>
>> Best,
>> Jean-Paul
>>
>> On 15. Jun 2021, at 12:57, Jean-Paul Pelteret <[email protected]> wrote:
>>
>> Hi Feilpe,
>>
>> Firstly, I agree that the documentation is very light on details on how
>> to use the linear operators with Trilinos linear algebra types. We can
>> definitely improve this, and any contributions to that effect would be
>> greatly appreciated!
>>
>> Right now, I can direct you to a few of the tests that use Trilinos LA in
>> conjunction with the inverse operator, so that you can compare what you
>> have and figure out what the problematic differences are. There is this
>> one, for instance
>>
>> https://github.com/dealii/dealii/blob/master/tests/lac/linear_operator_12a.cc#L323-L341
>> that looks like a similar setup to yours, and
>>
>> https://github.com/dealii/dealii/blob/master/tests/lac/schur_complement_04.cc#L126-L137
>> that uses a Trilinos::SolverCG (as opposed to deal.II’s solver).
>>
>> Comparing to both of these, I think that the important point might be
>> that the preconditioner must be declared (out-of-line) before the
>> inverse_operation() function is called. The linear operators typically
>> expect the lifetime of the LA objects to exceed that of the operators, and
>> so you have to first create the matrix or preconditioner and then pass it
>> to the linear operators. This is similar to what you’d done when setting up 
>> op_M,
>> for example. The case of passing in a deal::PreconditionerIdentity() for
>> serial operations is a special case, and I don’t think that we’ve
>> duplicated that for TrilinosWrappers:: PreconditionerIdentity(). Maybe
>> that could be improved too.
>>
>> I hope that with this single change you’d be able to get your
>> program running. If not, then please do let us know so that we can try to
>> help further.
>>
>> Best,
>> Jean-Paul
>>
>>
>> On 14. Jun 2021, at 19:18, Juan Felipe Giraldo <[email protected]>
>> wrote:
>>
>> Hello everyone,
>>
>> I have implemented a residual-minimization framework that somehow is
>> similar to DPG. I want to extend my results by using parallelization using
>> MPI with PETSc or Trilinos.
>> So far, I have solved the saddle point problem using the Schur complement
>> exactly how it is described in step 20. Now, I am trying to replicate
>> exactly the same solver but using the MPI wrappers and the linear operators.
>>
>> The problem is that when I am trying to implement the inverse_operator to
>> compute the Preconditioner of the Schur complement, I get an error saying
>> that the functions are not matching "inverse_operator(op_aS, solver_aS,
>> TrilinosWrappers::PreconditionIdentity())."
>>
>> There is no much documentation about linear operators in parallel
>> solvers, so if anyone has any suggestion on how to fix this problem, it
>> would be well appreciated.
>>
>> I have pasted the complete function in below:
>>
>>
>> template <int dim>
>> void FEMwDG<dim>::
>>   solve()
>>   {
>>     TimerOutput::Scope t(computing_timer, "solve");
>>
>>     LA::MPI::PreconditionJacobi prec_M;
>>      LA::MPI::PreconditionJacobi::AdditionalData data;
>>      prec_M.initialize(system_matrix.block(0, 0), data);
>>     }
>>
>>     auto &E = solution.block(0);
>>     auto &U = solution.block(1);
>>     const auto &L = system_rhs.block(0);
>>     const auto  M =
>> linear_operator<LA::MPI::Vector>(system_matrix.block(0, 0));
>>
>>     const auto op_M  = linear_operator(M, prec_M);
>>     const auto op_B   =
>> linear_operator<LA::MPI::Vector>(system_matrix.block(0, 1));
>>     const auto op_BT =
>> linear_operator<LA::MPI::Vector>(system_matrix.block(1, 0));
>>
>>     ReductionControl          inner_solver_control2(5000,
>>                                                     1e-18 *
>> system_rhs.l2_norm(),
>>                                                     1.e-2);
>>
>>     SolverCG<LA::MPI::Vector> cg(inner_solver_control2);
>>     const auto op_M_inv = inverse_operator(M, cg, prec_M);
>>
>>     const auto op_S = op_BT * op_M_inv * op_B;
>>     const auto op_aS = op_BT * linear_operator<LA::MPI::Vector>(prec_M) *
>> op_B;
>>
>>     IterationNumberControl   iteration_number_control_aS(30, 1.e-18);
>>     SolverCG<LA::MPI::Vector> solver_aS(iteration_number_control_aS);
>>
>>     const auto preconditioner_S =
>>     inverse_operator(op_aS, solver_aS,
>> TrilinosWrappers::PreconditionIdentity());
>>     const auto schur_rhs = op_BT * op_M_inv * L ;
>>
>>     SolverControl            solver_control_S(2000, 1.e-12);
>>     SolverCG<LA::MPI::Vector> solver_S(solver_control_S);
>>
>>     const auto op_S_inv = inverse_operator(op_S, solver_S,
>> preconditioner_S );
>>
>>     U = op_S_inv * schur_rhs;
>>     std::cout << solver_control_S.last_step()
>>               << " CG Schur complement iterations to obtain convergence."
>>               << std::endl;
>>     E = op_M_inv * (L - op_B * U);
>>      }
>>
>> Thank you so much,
>>
>> Regards,
>> Felipe
>>
>>
>>
>>
>>
>> --
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>>
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