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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