mirror of
https://github.com/OPM/opm-simulators.git
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583 lines
21 KiB
C++
583 lines
21 KiB
C++
// -*- mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
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// vi: set et ts=4 sw=4 sts=4:
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/*
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This file is part of the Open Porous Media project (OPM).
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OPM is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 2 of the License, or
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(at your option) any later version.
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OPM is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with OPM. If not, see <http://www.gnu.org/licenses/>.
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Consult the COPYING file in the top-level source directory of this
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module for the precise wording of the license and the list of
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copyright holders.
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*/
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/*!
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* \file
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*
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* \copydoc Opm::FvBaseLinearizer
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*/
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#ifndef EWOMS_FV_BASE_LINEARIZER_HH
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#define EWOMS_FV_BASE_LINEARIZER_HH
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#include "fvbaseproperties.hh"
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#include <opm/models/parallel/gridcommhandles.hh>
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#include <opm/models/parallel/threadmanager.hh>
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#include <opm/models/parallel/threadedentityiterator.hh>
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#include <opm/models/discretization/common/baseauxiliarymodule.hh>
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#include <opm/material/common/Exceptions.hpp>
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#include <dune/common/version.hh>
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#include <dune/common/fvector.hh>
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#include <dune/common/fmatrix.hh>
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#include <type_traits>
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#include <iostream>
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#include <vector>
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#include <thread>
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#include <set>
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#include <exception> // current_exception, rethrow_exception
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#include <mutex>
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namespace Opm {
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// forward declarations
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template<class TypeTag>
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class EcfvDiscretization;
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/*!
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* \ingroup FiniteVolumeDiscretizations
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*
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* \brief The common code for the linearizers of non-linear systems of equations
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*
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* This class assumes that these system of equations to be linearized are stemming from
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* models that use an finite volume scheme for spatial discretization and an Euler
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* scheme for time discretization.
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*/
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template<class TypeTag>
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class FvBaseLinearizer
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{
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//! \cond SKIP_THIS
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typedef typename GET_PROP_TYPE(TypeTag, Model) Model;
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typedef typename GET_PROP_TYPE(TypeTag, Discretization) Discretization;
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typedef typename GET_PROP_TYPE(TypeTag, Problem) Problem;
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typedef typename GET_PROP_TYPE(TypeTag, Simulator) Simulator;
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typedef typename GET_PROP_TYPE(TypeTag, GridView) GridView;
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typedef typename GET_PROP_TYPE(TypeTag, Scalar) Scalar;
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typedef typename GET_PROP_TYPE(TypeTag, Evaluation) Evaluation;
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typedef typename GET_PROP_TYPE(TypeTag, DofMapper) DofMapper;
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typedef typename GET_PROP_TYPE(TypeTag, ElementMapper) ElementMapper;
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typedef typename GET_PROP_TYPE(TypeTag, ElementContext) ElementContext;
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typedef typename GET_PROP_TYPE(TypeTag, SolutionVector) SolutionVector;
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typedef typename GET_PROP_TYPE(TypeTag, GlobalEqVector) GlobalEqVector;
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typedef typename GET_PROP_TYPE(TypeTag, SparseMatrixAdapter) SparseMatrixAdapter;
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typedef typename GET_PROP_TYPE(TypeTag, EqVector) EqVector;
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typedef typename GET_PROP_TYPE(TypeTag, Constraints) Constraints;
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typedef typename GET_PROP_TYPE(TypeTag, Stencil) Stencil;
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typedef typename GET_PROP_TYPE(TypeTag, ThreadManager) ThreadManager;
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typedef typename GET_PROP_TYPE(TypeTag, GridCommHandleFactory) GridCommHandleFactory;
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typedef Opm::MathToolbox<Evaluation> Toolbox;
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typedef typename GridView::template Codim<0>::Entity Element;
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typedef typename GridView::template Codim<0>::Iterator ElementIterator;
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typedef GlobalEqVector Vector;
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typedef typename SparseMatrixAdapter::IstlMatrix IstlMatrix;
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enum { numEq = GET_PROP_VALUE(TypeTag, NumEq) };
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enum { historySize = GET_PROP_VALUE(TypeTag, TimeDiscHistorySize) };
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typedef typename SparseMatrixAdapter::MatrixBlock MatrixBlock;
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typedef Dune::FieldVector<Scalar, numEq> VectorBlock;
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static const bool linearizeNonLocalElements = GET_PROP_VALUE(TypeTag, LinearizeNonLocalElements);
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// copying the linearizer is not a good idea
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FvBaseLinearizer(const FvBaseLinearizer&);
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//! \endcond
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public:
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FvBaseLinearizer()
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: jacobian_()
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{
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simulatorPtr_ = 0;
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}
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~FvBaseLinearizer()
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{
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auto it = elementCtx_.begin();
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const auto& endIt = elementCtx_.end();
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for (; it != endIt; ++it)
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delete *it;
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}
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/*!
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* \brief Register all run-time parameters for the Jacobian linearizer.
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*/
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static void registerParameters()
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{ }
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/*!
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* \brief Initialize the linearizer.
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*
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* At this point we can assume that all objects in the simulator
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* have been allocated. We cannot assume that they are fully
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* initialized, though.
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*
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* \copydetails Doxygen::simulatorParam
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*/
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void init(Simulator& simulator)
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{
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simulatorPtr_ = &simulator;
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eraseMatrix();
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}
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/*!
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* \brief Causes the Jacobian matrix to be recreated from scratch before the next
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* iteration.
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*
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* This method is usally called if the sparsity pattern has changed for some
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* reason. (e.g. by modifications of the grid or changes of the auxiliary equations.)
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*/
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void eraseMatrix()
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{
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jacobian_.reset();
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}
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/*!
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* \brief Linearize the full system of non-linear equations.
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*
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* This means the spatial domain plus all auxiliary equations.
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*/
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void linearize()
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{
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linearizeDomain();
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linearizeAuxiliaryEquations();
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}
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/*!
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* \brief Linearize the part of the non-linear system of equations that is associated
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* with the spatial domain.
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*
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* That means that the global Jacobian of the residual is assembled and the residual
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* is evaluated for the current solution.
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*
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* The current state of affairs (esp. the previous and the current solutions) is
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* represented by the model object.
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*/
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void linearizeDomain()
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{
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// we defer the initialization of the Jacobian matrix until here because the
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// auxiliary modules usually assume the problem, model and grid to be fully
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// initialized...
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if (!jacobian_)
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initFirstIteration_();
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int succeeded;
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try {
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linearize_();
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succeeded = 1;
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}
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catch (const std::exception& e)
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{
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std::cout << "rank " << simulator_().gridView().comm().rank()
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<< " caught an exception while linearizing:" << e.what()
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<< "\n" << std::flush;
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succeeded = 0;
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}
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catch (...)
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{
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std::cout << "rank " << simulator_().gridView().comm().rank()
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<< " caught an exception while linearizing"
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<< "\n" << std::flush;
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succeeded = 0;
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}
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succeeded = gridView_().comm().min(succeeded);
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if (!succeeded)
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throw Opm::NumericalIssue("A process did not succeed in linearizing the system");
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}
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void finalize()
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{ jacobian_->finalize(); }
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/*!
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* \brief Linearize the part of the non-linear system of equations that is associated
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* with the spatial domain.
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*/
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void linearizeAuxiliaryEquations()
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{
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// flush possible local caches into matrix structure
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jacobian_->commit();
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auto& model = model_();
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const auto& comm = simulator_().gridView().comm();
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for (unsigned auxModIdx = 0; auxModIdx < model.numAuxiliaryModules(); ++auxModIdx) {
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bool succeeded = true;
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try {
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model.auxiliaryModule(auxModIdx)->linearize(*jacobian_, residual_);
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}
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catch (const std::exception& e) {
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succeeded = false;
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std::cout << "rank " << simulator_().gridView().comm().rank()
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<< " caught an exception while linearizing:" << e.what()
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<< "\n" << std::flush;
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}
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succeeded = comm.min(succeeded);
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if (!succeeded)
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throw Opm::NumericalIssue("linearization of an auxilary equation failed");
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}
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}
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/*!
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* \brief Return constant reference to global Jacobian matrix backend.
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*/
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const SparseMatrixAdapter& jacobian() const
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{ return *jacobian_; }
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SparseMatrixAdapter& jacobian()
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{ return *jacobian_; }
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/*!
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* \brief Return constant reference to global residual vector.
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*/
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const GlobalEqVector& residual() const
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{ return residual_; }
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GlobalEqVector& residual()
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{ return residual_; }
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/*!
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* \brief Returns the map of constraint degrees of freedom.
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*
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* (This object is only non-empty if the EnableConstraints property is true.)
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*/
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const std::map<unsigned, Constraints>& constraintsMap() const
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{ return constraintsMap_; }
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private:
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Simulator& simulator_()
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{ return *simulatorPtr_; }
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const Simulator& simulator_() const
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{ return *simulatorPtr_; }
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Problem& problem_()
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{ return simulator_().problem(); }
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const Problem& problem_() const
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{ return simulator_().problem(); }
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Model& model_()
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{ return simulator_().model(); }
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const Model& model_() const
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{ return simulator_().model(); }
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const GridView& gridView_() const
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{ return problem_().gridView(); }
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const ElementMapper& elementMapper_() const
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{ return model_().elementMapper(); }
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const DofMapper& dofMapper_() const
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{ return model_().dofMapper(); }
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void initFirstIteration_()
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{
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// initialize the BCRS matrix for the Jacobian of the residual function
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createMatrix_();
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// initialize the Jacobian matrix and the vector for the residual function
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residual_.resize(model_().numTotalDof());
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resetSystem_();
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// create the per-thread context objects
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elementCtx_.resize(ThreadManager::maxThreads());
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for (unsigned threadId = 0; threadId != ThreadManager::maxThreads(); ++ threadId)
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elementCtx_[threadId] = new ElementContext(simulator_());
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}
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// Construct the BCRS matrix for the Jacobian of the residual function
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void createMatrix_()
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{
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const auto& model = model_();
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Stencil stencil(gridView_(), model_().dofMapper());
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// for the main model, find out the global indices of the neighboring degrees of
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// freedom of each primary degree of freedom
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typedef std::set< unsigned > NeighborSet;
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std::vector<NeighborSet> sparsityPattern(model.numTotalDof());
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ElementIterator elemIt = gridView_().template begin<0>();
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const ElementIterator elemEndIt = gridView_().template end<0>();
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for (; elemIt != elemEndIt; ++elemIt) {
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const Element& elem = *elemIt;
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stencil.update(elem);
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for (unsigned primaryDofIdx = 0; primaryDofIdx < stencil.numPrimaryDof(); ++primaryDofIdx) {
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unsigned myIdx = stencil.globalSpaceIndex(primaryDofIdx);
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for (unsigned dofIdx = 0; dofIdx < stencil.numDof(); ++dofIdx) {
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unsigned neighborIdx = stencil.globalSpaceIndex(dofIdx);
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sparsityPattern[myIdx].insert(neighborIdx);
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}
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}
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}
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// add the additional neighbors and degrees of freedom caused by the auxiliary
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// equations
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size_t numAuxMod = model.numAuxiliaryModules();
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for (unsigned auxModIdx = 0; auxModIdx < numAuxMod; ++auxModIdx)
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model.auxiliaryModule(auxModIdx)->addNeighbors(sparsityPattern);
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// allocate raw matrix
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jacobian_.reset(new SparseMatrixAdapter(simulator_()));
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// create matrix structure based on sparsity pattern
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jacobian_->reserve(sparsityPattern);
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}
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// reset the global linear system of equations.
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void resetSystem_()
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{
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residual_ = 0.0;
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// zero all matrix entries
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jacobian_->clear();
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}
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// query the problem for all constraint degrees of freedom. note that this method is
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// quite involved and is thus relatively slow.
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void updateConstraintsMap_()
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{
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if (!enableConstraints_())
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// constraints are not explictly enabled, so we don't need to consider them!
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return;
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constraintsMap_.clear();
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// loop over all elements...
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ThreadedEntityIterator<GridView, /*codim=*/0> threadedElemIt(gridView_());
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#ifdef _OPENMP
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#pragma omp parallel
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#endif
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{
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unsigned threadId = ThreadManager::threadId();
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ElementIterator elemIt = threadedElemIt.beginParallel();
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for (; !threadedElemIt.isFinished(elemIt); elemIt = threadedElemIt.increment()) {
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// create an element context (the solution-based quantities are not
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// available here!)
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const Element& elem = *elemIt;
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ElementContext& elemCtx = *elementCtx_[threadId];
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elemCtx.updateStencil(elem);
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// check if the problem wants to constrain any degree of the current
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// element's freedom. if yes, add the constraint to the map.
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for (unsigned primaryDofIdx = 0;
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primaryDofIdx < elemCtx.numPrimaryDof(/*timeIdx=*/0);
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++ primaryDofIdx)
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{
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Constraints constraints;
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elemCtx.problem().constraints(constraints,
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elemCtx,
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primaryDofIdx,
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/*timeIdx=*/0);
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if (constraints.isActive()) {
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unsigned globI = elemCtx.globalSpaceIndex(primaryDofIdx, /*timeIdx=*/0);
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constraintsMap_[globI] = constraints;
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continue;
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}
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}
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}
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}
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}
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// linearize the whole system
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void linearize_()
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{
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resetSystem_();
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// before the first iteration of each time step, we need to update the
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// constraints. (i.e., we assume that constraints can be time dependent, but they
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// can't depend on the solution.)
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if (model_().newtonMethod().numIterations() == 0)
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updateConstraintsMap_();
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applyConstraintsToSolution_();
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// to avoid a race condition if two threads handle an exception at the same time,
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// we use an explicit lock to control access to the exception storage object
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// amongst thread-local handlers
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std::mutex exceptionLock;
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// storage to any exception that needs to be bridged out of the
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// parallel block below. initialized to null to indicate no exception
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std::exception_ptr exceptionPtr = nullptr;
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// relinearize the elements...
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ThreadedEntityIterator<GridView, /*codim=*/0> threadedElemIt(gridView_());
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#ifdef _OPENMP
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#pragma omp parallel
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#endif
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{
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ElementIterator elemIt = threadedElemIt.beginParallel();
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ElementIterator nextElemIt = elemIt;
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try {
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for (; !threadedElemIt.isFinished(elemIt); elemIt = nextElemIt) {
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// give the model and the problem a chance to prefetch the data required
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// to linearize the next element, but only if we need to consider it
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nextElemIt = threadedElemIt.increment();
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if (!threadedElemIt.isFinished(nextElemIt)) {
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const auto& nextElem = *nextElemIt;
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if (linearizeNonLocalElements
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|| nextElem.partitionType() == Dune::InteriorEntity)
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{
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model_().prefetch(nextElem);
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problem_().prefetch(nextElem);
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}
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}
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const Element& elem = *elemIt;
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if (!linearizeNonLocalElements && elem.partitionType() != Dune::InteriorEntity)
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continue;
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linearizeElement_(elem);
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}
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}
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// If an exception occurs in the parallel block, it won't escape the
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// block; terminate() is called instead of a handler outside! hence, we
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// tuck any exceptions that occur away in the pointer. If an exception
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// occurs in more than one thread at the same time, we must pick one of
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// them to be rethrown as we cannot have two active exceptions at the
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// same time. This solution essentially picks one at random. This will
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// only be a problem if two different kinds of exceptions are thrown, for
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// instance if one thread experiences a (recoverable) numerical issue
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// while another is out of memory.
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catch(...) {
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std::lock_guard<std::mutex> take(exceptionLock);
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exceptionPtr = std::current_exception();
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threadedElemIt.setFinished();
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}
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} // parallel block
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// after reduction from the parallel block, exceptionPtr will point to
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// a valid exception if one occurred in one of the threads; rethrow
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// it here to let the outer handler take care of it properly
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if(exceptionPtr) {
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std::rethrow_exception(exceptionPtr);
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}
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applyConstraintsToLinearization_();
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}
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// linearize an element in the interior of the process' grid partition
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void linearizeElement_(const Element& elem)
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{
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unsigned threadId = ThreadManager::threadId();
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ElementContext *elementCtx = elementCtx_[threadId];
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auto& localLinearizer = model_().localLinearizer(threadId);
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// the actual work of linearization is done by the local linearizer class
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localLinearizer.linearize(*elementCtx, elem);
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// update the right hand side and the Jacobian matrix
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if (GET_PROP_VALUE(TypeTag, UseLinearizationLock))
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globalMatrixMutex_.lock();
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size_t numPrimaryDof = elementCtx->numPrimaryDof(/*timeIdx=*/0);
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for (unsigned primaryDofIdx = 0; primaryDofIdx < numPrimaryDof; ++ primaryDofIdx) {
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unsigned globI = elementCtx->globalSpaceIndex(/*spaceIdx=*/primaryDofIdx, /*timeIdx=*/0);
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// update the right hand side
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residual_[globI] += localLinearizer.residual(primaryDofIdx);
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// update the global Jacobian matrix
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for (unsigned dofIdx = 0; dofIdx < elementCtx->numDof(/*timeIdx=*/0); ++ dofIdx) {
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unsigned globJ = elementCtx->globalSpaceIndex(/*spaceIdx=*/dofIdx, /*timeIdx=*/0);
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jacobian_->addToBlock(globJ, globI, localLinearizer.jacobian(dofIdx, primaryDofIdx));
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}
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}
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if (GET_PROP_VALUE(TypeTag, UseLinearizationLock))
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globalMatrixMutex_.unlock();
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}
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// apply the constraints to the solution. (i.e., the solution of constraint degrees
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// of freedom is set to the value of the constraint.)
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void applyConstraintsToSolution_()
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{
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if (!enableConstraints_())
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return;
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// TODO: assuming a history size of 2 only works for Euler time discretizations!
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auto& sol = model_().solution(/*timeIdx=*/0);
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auto& oldSol = model_().solution(/*timeIdx=*/1);
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auto it = constraintsMap_.begin();
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const auto& endIt = constraintsMap_.end();
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for (; it != endIt; ++it) {
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sol[it->first] = it->second;
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oldSol[it->first] = it->second;
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}
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}
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// apply the constraints to the linearization. (i.e., for constrain degrees of
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// freedom the Jacobian matrix maps to identity and the residual is zero)
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void applyConstraintsToLinearization_()
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{
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if (!enableConstraints_())
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return;
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auto it = constraintsMap_.begin();
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const auto& endIt = constraintsMap_.end();
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for (; it != endIt; ++it) {
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unsigned constraintDofIdx = it->first;
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|
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// reset the column of the Jacobian matrix
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// put an identity matrix on the main diagonal of the Jacobian
|
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jacobian_->clearRow(constraintDofIdx, Scalar(1.0));
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// make the right-hand side of constraint DOFs zero
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residual_[constraintDofIdx] = 0.0;
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}
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}
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static bool enableConstraints_()
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{ return GET_PROP_VALUE(TypeTag, EnableConstraints); }
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Simulator *simulatorPtr_;
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std::vector<ElementContext*> elementCtx_;
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// The constraint equations (only non-empty if the
|
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// EnableConstraints property is true)
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std::map<unsigned, Constraints> constraintsMap_;
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|
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// the jacobian matrix
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std::unique_ptr<SparseMatrixAdapter> jacobian_;
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// the right-hand side
|
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GlobalEqVector residual_;
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std::mutex globalMatrixMutex_;
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|
};
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} // namespace Opm
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#endif
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