Teko_MLPreconditionerFactory.cpp

// @HEADER
// *****************************************************************************
//      Teko: A package for block and physics based preconditioning
//
// Copyright 2010 NTESS and the Teko contributors.
// SPDX-License-Identifier: BSD-3-Clause
// *****************************************************************************
// @HEADER
 
#include "Teko_MLPreconditionerFactory.hpp"
 
#include "Teko_MLLinearOp.hpp"
 
#include "ml_include.h"
#include "ml_MultiLevelPreconditioner.h"
#include "ml_epetra_utils.h"
#include "ml_RowMatrix.h"
 
#include "Thyra_get_Epetra_Operator.hpp"
 
namespace Teko {
 
// MLPreconditionerState
 
MLPreconditionerState::MLPreconditionerState() : isFilled_(false) {}
 
void MLPreconditionerState::setMLComm(ML_Comm *comm) {
  mlComm_ = Teuchos::rcpWithDealloc(comm, Teuchos::deallocFunctorDelete<ML_Comm>(cleanup_ML_Comm));
}
 
void MLPreconditionerState::setMLOperator(ML_Operator *op) {
  mlOp_ =
      Teuchos::rcpWithDealloc(op, Teuchos::deallocFunctorDelete<ML_Operator>(cleanup_ML_Operator));
}
 
void MLPreconditionerState::setIsFilled(bool value) { isFilled_ = value; }
 
bool MLPreconditionerState::isFilled() const { return isFilled_; }
 
void MLPreconditionerState::cleanup_ML_Comm(ML_Comm *mlComm) { ML_Comm_Destroy(&mlComm); }
 
void MLPreconditionerState::cleanup_ML_Operator(ML_Operator *mlOp) { ML_Operator_Destroy(&mlOp); }
 
void MLPreconditionerState::setAggregationMatrices(const std::vector<Epetra_RowMatrix *> &diags) {
  diagonalOps_ = diags;
}
 
Teuchos::RCP<ML_Epetra::MultiLevelPreconditioner> MLPreconditionerState::constructMLPreconditioner(
    const Teuchos::ParameterList &mainList,
    const std::vector<Teuchos::RCP<const Teuchos::ParameterList> > &coarseningParams) {
  TEUCHOS_ASSERT(isFilled());
  std::vector<Teuchos::ParameterList> cpls(coarseningParams.size());
  for (std::size_t i = 0; i < coarseningParams.size(); i++) cpls[i] = *coarseningParams[i];
 
  mlPreconditioner_ = rcp(new ML_Epetra::MultiLevelPreconditioner(
      &*mlOp_, mainList, &diagonalOps_[0], &cpls[0], diagonalOps_.size()));
 
  return mlPreconditioner_;
}
 
// MLPreconditionerFactory
 
MLPreconditionerFactory::MLPreconditionerFactory() {}
 
LinearOp MLPreconditionerFactory::buildPreconditionerOperator(
    BlockedLinearOp &blo, BlockPreconditionerState &state) const {
  MLPreconditionerState &mlState = Teuchos::dyn_cast<MLPreconditionerState>(state);
 
  if (not mlState.isFilled()) fillMLPreconditionerState(blo, mlState);
  TEUCHOS_ASSERT(mlState.isFilled());
 
  Teuchos::RCP<ML_Epetra::MultiLevelPreconditioner> mlPrecOp =
      mlState.constructMLPreconditioner(mainParams_, coarseningParams_);
 
  // return Thyra::epetraLinearOp(mlPrecOp);
  return Teuchos::rcp(new MLLinearOp(mlPrecOp));
}
 
Teuchos::RCP<PreconditionerState> MLPreconditionerFactory::buildPreconditionerState() const {
  return Teuchos::rcp(new MLPreconditionerState());
}
 
void MLPreconditionerFactory::fillMLPreconditionerState(const BlockedLinearOp &blo,
                                                        MLPreconditionerState &mlState) const {
  TEUCHOS_ASSERT(not mlState.isFilled());
 
  EpetraExt::CrsMatrix_SolverMap RowMatrixColMapTrans;
 
  int rowCnt = blockRowCount(blo);
  int colCnt = blockRowCount(blo);
 
  // construct comm object...add to state
  ML_Comm *mlComm;
  ML_Comm_Create(&mlComm);
  mlState.setMLComm(mlComm);
 
  ML_Operator *mlBlkMat = ML_Operator_Create(mlComm);
  ML_Operator_BlkMatInit(mlBlkMat, mlComm, rowCnt, colCnt, ML_DESTROY_EVERYTHING);
 
  std::vector<Epetra_RowMatrix *> aggMats;
  for (int r = 0; r < rowCnt; r++) {
    for (int c = 0; c < colCnt; c++) {
      ML_Operator *tmp       = 0;
      Epetra_RowMatrix *EMat = 0;
      std::stringstream ss;
 
      ss << "fine_" << r << "_" << c;
 
      // extract crs matrix
      Teuchos::RCP<Epetra_CrsMatrix> crsMat = Teuchos::rcp_dynamic_cast<Epetra_CrsMatrix>(
          Thyra::get_Epetra_Operator(*blo->getNonconstBlock(r, c)));
      EMat = ML_Epetra::ModifyEpetraMatrixColMap(*crsMat, RowMatrixColMapTrans, ss.str().c_str());
      if (r == c)  // setup diagonal scaling matrices
        aggMats.push_back(EMat);
 
      // extract ml sub operator
      tmp = ML_Operator_Create(mlComm);
      ML_Operator_WrapEpetraMatrix(EMat, tmp);
 
      // add it to the block
      ML_Operator_BlkMatInsert(mlBlkMat, tmp, r, c);
    }
  }
  ML_Operator_BlkMatFinalize(mlBlkMat);
 
  // finish setting up state object
  mlState.setMLOperator(mlBlkMat);
 
  // now set aggregation matrices
  mlState.setAggregationMatrices(aggMats);
 
  mlState.setIsFilled(true);  // register state object as filled
}
 
void MLPreconditionerFactory::initializeFromParameterList(const Teuchos::ParameterList &settings) {
  using Teuchos::RCP;
  using Teuchos::rcp;
 
  Teko_DEBUG_SCOPE("MLPreconditionerFactory::initializeFromParameterList", 10);
 
  // clear initial state
  coarseningParams_.clear();
  blockRowCount_ = 0;
 
  blockRowCount_ = settings.get<int>("Block Row Count");
 
  // read in main parameter list: with smoothing information
  mainParams_ = settings.sublist("Smoothing Parameters");
  mainParams_.set<Teuchos::RCP<const Teko::InverseLibrary> >("smoother: teko inverse library",
                                                             getInverseLibrary());
 
  // read in aggregation sub lists
  const Teuchos::ParameterList &aggSublist = settings.sublist("Block Aggregation");
 
  for (int block = 0; block < blockRowCount_; block++) {
    // write out sub list name: "Block #"
    std::stringstream ss;
    ss << "Block " << block;
    std::string sublistName = ss.str();
 
    // grab sublist
    RCP<Teuchos::ParameterList> userSpec =
        rcp(new Teuchos::ParameterList(aggSublist.sublist(sublistName)));
    coarseningParams_.push_back(userSpec);
  }
}
 
}  // end namespace Teko