opm-simulators/opm/autodiff/ParallelOverlappingILU0.hpp

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/*
Copyright 2015 Dr. Blatt - HPC-Simulation-Software & Services
Copyright 2015 Statoil AS
This file is part of the Open Porous Media project (OPM).
OPM is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
OPM is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with OPM. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef OPM_PARALLELOVERLAPPINGILU0_HEADER_INCLUDED
#define OPM_PARALLELOVERLAPPINGILU0_HEADER_INCLUDED
#include <opm/autodiff/GraphColoring.hpp>
#include <opm/common/Exceptions.hpp>
#include <opm/common/ErrorMacros.hpp>
#include <dune/common/version.hh>
#include <dune/istl/preconditioner.hh>
#include <dune/istl/paamg/smoother.hh>
#include <dune/istl/paamg/graph.hh>
#include <dune/istl/paamg/pinfo.hh>
#include <type_traits>
#include <numeric>
#include <limits>
#include <cstddef>
#include <string>
namespace Opm
{
//template<class M, class X, class Y, class C>
//class ParallelOverlappingILU0;
template<class Matrix, class Domain, class Range, class ParallelInfo = Dune::Amg::SequentialInformation>
class ParallelOverlappingILU0;
enum class MILU_VARIANT{
/// \brief Do not perform modified ILU
ILU = 0,
/// \brief \f$U_{ii} = U_{ii} +\f$ sum(dropped entries)
MILU_1 = 1,
/// \brief \f$U_{ii} = U_{ii} + sign(U_{ii}) * \f$ sum(dropped entries)
MILU_2 = 2,
/// \brief \f$U_{ii} = U_{ii} sign(U_{ii}) * \f$ sum(|dropped entries|)
MILU_3 = 3,
/// \brief \f$U_{ii} = U_{ii} + (U_{ii}>0?1:0) * \f$ sum(dropped entries)
MILU_4 = 4
};
inline MILU_VARIANT convertString2Milu(std::string milu)
{
if( 0 == milu.compare("MILU_1") )
{
return MILU_VARIANT::MILU_1;
}
if ( 0 == milu.compare("MILU_2") )
{
return MILU_VARIANT::MILU_2;
}
if ( 0 == milu.compare("MILU_3") )
{
return MILU_VARIANT::MILU_3;
}
return MILU_VARIANT::ILU;
}
template<class F>
class ParallelOverlappingILU0Args
: public Dune::Amg::DefaultSmootherArgs<F>
{
public:
ParallelOverlappingILU0Args(MILU_VARIANT milu = MILU_VARIANT::ILU )
: milu_(milu)
{}
void setMilu(MILU_VARIANT milu)
{
milu_ = milu;
}
MILU_VARIANT getMilu() const
{
return milu_;
}
void setN(int n)
{
n_ = n;
}
int getN() const
{
return n_;
}
private:
MILU_VARIANT milu_;
int n_;
};
} // end namespace Opm
namespace Dune
{
namespace Amg
{
template<class M, class X, class Y, class C>
struct SmootherTraits<Opm::ParallelOverlappingILU0<M,X,Y,C> >
{
using Arguments = Opm::ParallelOverlappingILU0Args<typename M::field_type>;
};
/// \brief Tells AMG how to construct the Opm::ParallelOverlappingILU0 smoother
/// \tparam Matrix The type of the Matrix.
/// \tparam Domain The type of the Vector representing the domain.
/// \tparam Range The type of the Vector representing the range.
/// \tparam ParallelInfo The type of the parallel information object
/// used, e.g. Dune::OwnerOverlapCommunication
template<class Matrix, class Domain, class Range, class ParallelInfo>
struct ConstructionTraits<Opm::ParallelOverlappingILU0<Matrix,Domain,Range,ParallelInfo> >
{
typedef Opm::ParallelOverlappingILU0<Matrix,Domain,Range,ParallelInfo> T;
typedef DefaultParallelConstructionArgs<T,ParallelInfo> Arguments;
static inline Opm::ParallelOverlappingILU0<Matrix,Domain,Range,ParallelInfo>* construct(Arguments& args)
{
return new T(args.getMatrix(),
args.getComm(),
args.getArgs().getN(),
args.getArgs().relaxationFactor,
args.getArgs().getMilu());
}
static inline void deconstruct(T* bp)
{
delete bp;
}
};
} // end namespace Amg
} // end namespace Dune
namespace Opm
{
namespace detail
{
struct Reorderer
{
virtual std::size_t operator[](std::size_t i) const = 0;
};
struct NoReorderer : public Reorderer
{
virtual std::size_t operator[](std::size_t i) const
{
return i;
}
};
struct RealReorderer : public Reorderer
{
RealReorderer(const std::vector<std::size_t>& ordering)
: ordering_(&ordering)
{}
virtual std::size_t operator[](std::size_t i) const
{
return (*ordering_)[i];
}
const std::vector<std::size_t>* ordering_;
};
struct IdentityFunctor
{
template<class T>
T operator()(const T& t)
{
return t;
}
};
struct OneFunctor
{
template<class T>
T operator()(const T&)
{
return 1.0;
}
};
struct SignFunctor
{
template<class T>
double operator()(const T& t)
{
if ( t < 0.0 )
{
return -1;
}
else
{
return 1.0;
}
}
};
struct IsPositiveFunctor
{
template<class T>
double operator()(const T& t)
{
if ( t < 0.0 )
{
return 0;
}
else
{
return 1;
}
}
};
struct AbsFunctor
{
template<class T>
T operator()(const T& t)
{
using std::abs;
return abs(t);
}
};
template<class M, class F1=detail::IdentityFunctor, class F2=detail::OneFunctor >
void milu0_decomposition(M& A, F1 absFunctor = F1(), F2 signFunctor = F2(),
std::vector<typename M::block_type>* diagonal = nullptr)
{
if( diagonal )
{
diagonal->reserve(A.N());
}
for ( auto irow = A.begin(), iend = A.end(); irow != iend; ++irow)
{
auto a_i_end = irow->end();
auto a_ik = irow->begin();
std::array<typename M::field_type, M::block_type::rows> sum_dropped{};
// Eliminate entries in lower triangular matrix
// and store factors for L
for ( ; a_ik.index() < irow.index(); ++a_ik )
{
auto k = a_ik.index();
auto a_kk = A[k].find(k);
// L_ik = A_kk^-1 * A_ik
a_ik->rightmultiply(*a_kk);
// modify the rest of the row, everything right of a_ik
// a_i* -=a_ik * a_k*
auto a_k_end = A[k].end();
auto a_kj = a_kk, a_ij = a_ik;
++a_kj; ++a_ij;
while ( a_kj != a_k_end)
{
auto modifier = *a_kj;
modifier.leftmultiply(*a_ik);
while( a_ij != a_i_end && a_ij.index() < a_kj.index())
{
++a_ij;
}
if ( a_ij != a_i_end && a_ij.index() == a_kj.index() )
{
// Value is not dropped
*a_ij -= modifier;
++a_ij; ++a_kj;
}
else
{
auto entry = sum_dropped.begin();
for( const auto& row: modifier )
{
for( const auto& colEntry: row )
{
*entry += absFunctor(-colEntry);
}
++entry;
}
++a_kj;
}
}
}
if ( a_ik.index() != irow.index() )
OPM_THROW(std::logic_error, "Matrix is missing diagonal for row " << irow.index());
int index = 0;
for(const auto& entry: sum_dropped)
{
auto& bdiag = (*a_ik)[index][index];
if(entry<0)
std::cout << entry << std::endl;
bdiag += signFunctor(bdiag) * entry;
++index;
}
if ( diagonal )
{
diagonal->push_back(*a_ik);
}
a_ik->invert(); // compute inverse of diagonal block
}
}
template<class M>
void milu0_decomposition(M& A,
std::vector<typename M::block_type>* diagonal)
{
milu0_decomposition(A, detail::IdentityFunctor(), detail::OneFunctor(),
diagonal);
}
template<class M>
void milun_decomposition(const M& A, int n, MILU_VARIANT milu, M& ILU,
Reorderer& ordering, Reorderer& inverseOrdering)
{
using Map = std::map<std::size_t, int>;
auto iluRow = ILU.createbegin();
for(std::size_t i = 0, iend = A.N(); i < iend; ++i)
{
auto& orow = A[inverseOrdering[i]];
Map rowPattern;
for ( auto col = orow.begin(), cend = orow.end(); col != cend; ++col)
{
rowPattern[ordering[col.index()]] = 0;
}
for(auto ik = rowPattern.begin(); ik->first < i; ++ik)
{
if ( ik->second < n )
{
auto& rowk = ILU[ik->first];
for ( auto kj = rowk.find(ik->first), endk = rowk.end();
kj != endk; ++kj)
{
// Assume double and block_type FieldMatrix
// first element is misused to store generation number
int generation = (*kj)[0][0];
if(generation < n)
{
auto ij = rowPattern.find(kj.index());
if ( ij == rowPattern.end() )
{
rowPattern[ordering[kj.index()]] = generation + 1;
}
}
}
}
}
// create the row
for(const auto entry: rowPattern)
{
iluRow.insert(entry.first);
}
++iluRow;
// write generation to newly created row.
auto generationPair = rowPattern.begin();
for ( auto col = ILU[i].begin(), cend = ILU[i].end(); col != cend;
++col, ++generationPair)
{
assert(col.index() == generationPair->first);
(*col)[0][0] = generationPair->second;
}
}
// copy Entries from A
for(auto iter=A.begin(), iend = A.end(); iter != iend; ++iter)
{
auto& newRow = ILU[ordering[iter.index()]];
// reset stored generation
for ( auto& col: newRow)
{
col = 0;
}
// copy row.
for(auto col = iter->begin(), cend = iter->end(); col != cend; ++col)
{
newRow[ordering[col.index()]] = *col;
}
}
// call decomposition on pattern
switch ( milu )
{
case MILU_VARIANT::MILU_1:
detail::milu0_decomposition ( ILU);
break;
case MILU_VARIANT::MILU_2:
detail::milu0_decomposition ( ILU, detail::IdentityFunctor(),
detail::SignFunctor() );
break;
case MILU_VARIANT::MILU_3:
detail::milu0_decomposition ( ILU, detail::AbsFunctor(),
detail::SignFunctor() );
break;
case MILU_VARIANT::MILU_4:
detail::milu0_decomposition ( ILU, detail::IdentityFunctor(),
detail::IsPositiveFunctor() );
break;
default:
bilu0_decomposition( ILU );
break;
}
}
//! compute ILU decomposition of A. A is overwritten by its decomposition
template<class M, class CRS, class InvVector>
void convertToCRS(const M& A, CRS& lower, CRS& upper, InvVector& inv )
{
// No need to do anything for 0 rows. Return to prevent indexing a
// a zero sized array.
if ( A.N() == 0 )
{
return;
}
typedef typename M :: size_type size_type;
lower.resize( A.N() );
upper.resize( A.N() );
inv.resize( A.N() );
lower.reserveAdditional( 2*A.N() );
// implement left looking variant with stored inverse
const auto endi = A.end();
size_type row = 0;
size_type colcount = 0;
lower.rows_[ 0 ] = colcount;
for (auto i=A.begin(); i!=endi; ++i, ++row)
{
const size_type iIndex = i.index();
lower.reserveAdditional( (*i).size() );
// eliminate entries left of diagonal; store L factor
for (auto j=(*i).begin(); j.index() < iIndex; ++j )
{
lower.push_back( (*j), j.index() );
++colcount;
}
lower.rows_[ iIndex+1 ] = colcount;
}
const auto rendi = A.beforeBegin();
row = 0;
colcount = 0;
upper.rows_[ 0 ] = colcount ;
upper.reserveAdditional( lower.nonZeros() + A.N() );
// NOTE: upper and inv store entries in reverse order, reverse here
// relative to ILU
for (auto i=A.beforeEnd(); i!=rendi; --i, ++ row )
{
const size_type iIndex = i.index();
upper.reserveAdditional( (*i).size() );
// store in reverse row order
// eliminate entries left of diagonal; store L factor
for (auto j=(*i).beforeEnd(); j.index()>=iIndex; --j )
{
const size_type jIndex = j.index();
if( j.index() == iIndex )
{
inv[ row ] = (*j);
break;
}
else if ( j.index() >= i.index() )
{
upper.push_back( (*j), jIndex );
++colcount ;
}
}
upper.rows_[ row+1 ] = colcount;
}
}
} // end namespace detail
/// \brief A two-step version of an overlapping Schwarz preconditioner using one step ILU0 as
///
/// This preconditioner differs from a ParallelRestrictedOverlappingSchwarz with
/// Dune:SeqILU0 in the follwing way:
/// During apply we make sure that the current residual is consistent (i.e.
/// each process knows the same value for each index. The we solve
/// Ly= d for y and make y consistent again. Last we solve Ux = y and
/// make sure that x is consistent.
/// In contrast for ParallelRestrictedOverlappingSchwarz we solve (LU)x = d for x
/// without forcing consistency between the two steps.
/// \tparam Matrix The type of the Matrix.
/// \tparam Domain The type of the Vector representing the domain.
/// \tparam Range The type of the Vector representing the range.
/// \tparam ParallelInfo The type of the parallel information object
/// used, e.g. Dune::OwnerOverlapCommunication
template<class Matrix, class Domain, class Range, class ParallelInfoT>
class ParallelOverlappingILU0
: public Dune::Preconditioner<Domain,Range>
{
typedef ParallelInfoT ParallelInfo;
public:
//! \brief The matrix type the preconditioner is for.
typedef typename std::remove_const<Matrix>::type matrix_type;
//! \brief The domain type of the preconditioner.
typedef Domain domain_type;
//! \brief The range type of the preconditioner.
typedef Range range_type;
//! \brief The field type of the preconditioner.
typedef typename Domain::field_type field_type;
typedef typename matrix_type::block_type block_type;
typedef typename matrix_type::size_type size_type;
protected:
struct CRS
{
CRS() : nRows_( 0 ) {}
size_type rows() const { return nRows_; }
size_type nonZeros() const
{
assert( rows_[ rows() ] != size_type(-1) );
return rows_[ rows() ];
}
void resize( const size_type nRows )
{
if( nRows_ != nRows )
{
nRows_ = nRows ;
rows_.resize( nRows_+1, size_type(-1) );
}
}
void reserveAdditional( const size_type nonZeros )
{
const size_type needed = values_.size() + nonZeros ;
if( values_.capacity() < needed )
{
const size_type estimate = needed * 1.1;
values_.reserve( estimate );
cols_.reserve( estimate );
}
}
void push_back( const block_type& value, const size_type index )
{
values_.push_back( value );
cols_.push_back( index );
}
std::vector< size_type > rows_;
std::vector< block_type > values_;
std::vector< size_type > cols_;
size_type nRows_;
};
public:
#if DUNE_VERSION_NEWER(DUNE_ISTL, 2, 6)
Dune::SolverCategory::Category category() const override
{
return std::is_same<ParallelInfoT, Dune::Amg::SequentialInformation>::value ?
Dune::SolverCategory::sequential : Dune::SolverCategory::overlapping;
}
#else
// define the category
enum {
//! \brief The category the preconditioner is part of.
category = std::is_same<ParallelInfoT, Dune::Amg::SequentialInformation>::value ?
Dune::SolverCategory::sequential : Dune::SolverCategory::overlapping
};
#endif
/*! \brief Constructor.
Constructor gets all parameters to operate the prec.
\param A The matrix to operate on.
\param n ILU fill in level (for testing). This does not work in parallel.
\param w The relaxation factor.
\param milu The modified ILU variant to use. 0 means traditional ILU. \see MILU_VARIANT.
\param redblack Whether to use a red-black ordering.
\param reorder_sphere If true, we start the reordering at a root node.
The vertices on each layer aound it (same distance) are
ordered consecutivly. If false, we preserver the order of
the vertices with the same color.
*/
template<class BlockType, class Alloc>
ParallelOverlappingILU0 (const Dune::BCRSMatrix<BlockType,Alloc>& A,
const int n, const field_type w,
MILU_VARIANT milu, bool redblack=false,
bool reorder_sphere=true)
: lower_(),
upper_(),
inv_(),
comm_(nullptr), w_(w),
relaxation_( std::abs( w - 1.0 ) > 1e-15 )
{
// BlockMatrix is a Subclass of FieldMatrix that just adds
// methods. Therefore this cast should be safe.
init( reinterpret_cast<const Matrix&>(A), n, milu, redblack,
reorder_sphere );
}
/*! \brief Constructor gets all parameters to operate the prec.
\param A The matrix to operate on.
\param comm communication object, e.g. Dune::OwnerOverlapCopyCommunication
\param n ILU fill in level (for testing). This does not work in parallel.
\param w The relaxation factor.
\param milu The modified ILU variant to use. 0 means traditional ILU. \see MILU_VARIANT.
\param redblack Whether to use a red-black ordering.
\param reorder_sphere If true, we start the reordering at a root node.
The vertices on each layer aound it (same distance) are
ordered consecutivly. If false, we preserver the order of
the vertices with the same color.
*/
template<class BlockType, class Alloc>
ParallelOverlappingILU0 (const Dune::BCRSMatrix<BlockType,Alloc>& A,
const ParallelInfo& comm, const int n, const field_type w,
MILU_VARIANT milu, bool redblack=false,
bool reorder_sphere=true)
: lower_(),
upper_(),
inv_(),
comm_(&comm), w_(w),
relaxation_( std::abs( w - 1.0 ) > 1e-15 )
{
// BlockMatrix is a Subclass of FieldMatrix that just adds
// methods. Therefore this cast should be safe.
init( reinterpret_cast<const Matrix&>(A), n, milu, redblack,
reorder_sphere );
}
/*! \brief Constructor.
Constructor gets all parameters to operate the prec.
\param A The matrix to operate on.
\param w The relaxation factor.
\param milu The modified ILU variant to use. 0 means traditional ILU. \see MILU_VARIANT.
\param redblack Whether to use a red-black ordering.
\param reorder_sphere If true, we start the reordering at a root node.
The vertices on each layer aound it (same distance) are
ordered consecutivly. If false, we preserver the order of
the vertices with the same color.
*/
template<class BlockType, class Alloc>
ParallelOverlappingILU0 (const Dune::BCRSMatrix<BlockType,Alloc>& A,
const field_type w, MILU_VARIANT milu, bool redblack=false,
bool reorder_sphere=true)
: ParallelOverlappingILU0( A, 0, w, milu, redblack, reorder_sphere )
{
}
/*! \brief Constructor.
Constructor gets all parameters to operate the prec.
\param A The matrix to operate on.
\param comm communication object, e.g. Dune::OwnerOverlapCopyCommunication
\param w The relaxation factor.
\param milu The modified ILU variant to use. 0 means traditional ILU. \see MILU_VARIANT.
\param redblack Whether to use a red-black ordering.
\param reorder_sphere If true, we start the reordering at a root node.
The vertices on each layer aound it (same distance) are
ordered consecutivly. If false, we preserver the order of
the vertices with the same color.
*/
template<class BlockType, class Alloc>
ParallelOverlappingILU0 (const Dune::BCRSMatrix<BlockType,Alloc>& A,
const ParallelInfo& comm, const field_type w,
MILU_VARIANT milu, bool redblack=false,
bool reorder_sphere=true)
: lower_(),
upper_(),
inv_(),
comm_(&comm), w_(w),
relaxation_( std::abs( w - 1.0 ) > 1e-15 )
{
// BlockMatrix is a Subclass of FieldMatrix that just adds
// methods. Therefore this cast should be safe.
init( reinterpret_cast<const Matrix&>(A), 0, milu, redblack,
reorder_sphere );
}
/*!
\brief Prepare the preconditioner.
\copydoc Preconditioner::pre(X&,Y&)
*/
virtual void pre (Domain& x, Range& b)
{
DUNE_UNUSED_PARAMETER(x);
DUNE_UNUSED_PARAMETER(b);
}
/*!
\brief Apply the preconditoner.
\copydoc Preconditioner::apply(X&,const Y&)
*/
virtual void apply (Domain& v, const Range& d)
{
Range& md = reorderD(d);
Domain& mv = reorderV(v);
copyOwnerToAll( md );
// iterator types
typedef typename Range ::block_type dblock;
typedef typename Domain::block_type vblock;
const size_type iEnd = lower_.rows();
const size_type lastRow = iEnd - 1;
if( iEnd != upper_.rows() )
{
OPM_THROW(std::logic_error,"ILU: number of lower and upper rows must be the same");
}
// lower triangular solve
for( size_type i=0; i<iEnd; ++ i )
{
dblock rhs( md[ i ] );
const size_type rowI = lower_.rows_[ i ];
const size_type rowINext = lower_.rows_[ i+1 ];
for( size_type col = rowI; col < rowINext; ++ col )
{
lower_.values_[ col ].mmv( mv[ lower_.cols_[ col ] ], rhs );
}
mv[ i ] = rhs; // Lii = I
}
copyOwnerToAll( mv );
for( size_type i=0; i<iEnd; ++ i )
{
vblock& vBlock = mv[ lastRow - i ];
vblock rhs ( vBlock );
const size_type rowI = upper_.rows_[ i ];
const size_type rowINext = upper_.rows_[ i+1 ];
for( size_type col = rowI; col < rowINext; ++ col )
{
upper_.values_[ col ].mmv( mv[ upper_.cols_[ col ] ], rhs );
}
// apply inverse and store result
inv_[ i ].mv( rhs, vBlock);
}
copyOwnerToAll( mv );
if( relaxation_ ) {
mv *= w_;
}
reorderBack(mv, v);
}
template <class V>
void copyOwnerToAll( V& v ) const
{
if( comm_ ) {
comm_->copyOwnerToAll(v, v);
}
}
/*!
\brief Clean up.
\copydoc Preconditioner::post(X&)
*/
virtual void post (Range& x)
{
DUNE_UNUSED_PARAMETER(x);
}
protected:
void init( const Matrix& A, const int iluIteration, MILU_VARIANT milu, bool redBlack, bool reorderSpheres )
{
// (For older DUNE versions the communicator might be
// invalid if redistribution in AMG happened on the coarset level.
// Therefore we check for nonzero size
if ( comm_ && comm_->communicator().size()<=0 )
{
if ( A.N() > 0 )
{
OPM_THROW(std::logic_error, "Expected a matrix with zero rows for an invalid communicator.");
}
else
{
// simply set the communicator to null
comm_ = nullptr;
}
}
int ilu_setup_successful = 1;
std::string message;
const int rank = ( comm_ ) ? comm_->communicator().rank() : 0;
std::unique_ptr< Matrix > ILU;
if ( redBlack )
{
using Graph = Dune::Amg::MatrixGraph<const Matrix>;
Graph graph(A);
auto colorsTuple = colorVerticesWelshPowell(graph);
const auto& colors = std::get<0>(colorsTuple);
const auto& verticesPerColor = std::get<2>(colorsTuple);
auto noColors = std::get<1>(colorsTuple);
if ( reorderSpheres )
{
ordering_ = reorderVerticesSpheres(colors, noColors, verticesPerColor,
graph, 0);
}
else
{
ordering_ = reorderVerticesPreserving(colors, noColors, verticesPerColor,
graph);
}
}
std::vector<std::size_t> inverseOrdering(ordering_.size());
std::size_t index = 0;
for( auto newIndex: ordering_)
{
inverseOrdering[newIndex] = index++;
}
try
{
if( iluIteration == 0 ) {
// create ILU-0 decomposition
if ( ordering_.empty() )
{
ILU.reset( new Matrix( A ) );
}
else
{
ILU.reset( new Matrix(A.N(), A.M(), A.nonzeroes(), Matrix::row_wise));
auto& newA = *ILU;
// Create sparsity pattern
for(auto iter=newA.createbegin(), iend = newA.createend(); iter != iend; ++iter)
{
const auto& row = A[inverseOrdering[iter.index()]];
for(auto col = row.begin(), cend = row.end(); col != cend; ++col)
{
iter.insert(ordering_[col.index()]);
}
}
// Copy values
for(auto iter = A.begin(), iend = A.end(); iter != iend; ++iter)
{
auto& newRow = newA[ordering_[iter.index()]];
for(auto col = iter->begin(), cend = iter->end(); col != cend; ++col)
{
newRow[ordering_[col.index()]] = *col;
}
}
}
switch ( milu )
{
case MILU_VARIANT::MILU_1:
detail::milu0_decomposition ( *ILU);
break;
case MILU_VARIANT::MILU_2:
detail::milu0_decomposition ( *ILU, detail::IdentityFunctor(),
detail::SignFunctor() );
break;
case MILU_VARIANT::MILU_3:
detail::milu0_decomposition ( *ILU, detail::AbsFunctor(),
detail::SignFunctor() );
break;
case MILU_VARIANT::MILU_4:
detail::milu0_decomposition ( *ILU, detail::IdentityFunctor(),
detail::IsPositiveFunctor() );
break;
default:
bilu0_decomposition( *ILU );
break;
}
}
else {
// create ILU-n decomposition
ILU.reset( new Matrix( A.N(), A.M(), Matrix::row_wise) );
std::unique_ptr<detail::Reorderer> reorderer, inverseReorderer;
if ( ordering_.empty() )
{
reorderer.reset(new detail::NoReorderer());
inverseReorderer.reset(new detail::NoReorderer());
}
else
{
reorderer.reset(new detail::RealReorderer(ordering_));
inverseReorderer.reset(new detail::RealReorderer(inverseOrdering));
}
milun_decomposition( A, iluIteration, milu, *ILU, *reorderer, *inverseReorderer );
}
}
catch ( const Dune::MatrixBlockError& error )
{
message = error.what();
std::cerr<<"Exception occured on process " << rank << " during " <<
"setup of ILU0 preconditioner with message: " <<
message<<std::endl;
ilu_setup_successful = 0;
}
// Check whether there was a problem on some process
const bool parallel_failure = comm_ && comm_->communicator().min(ilu_setup_successful) == 0;
const bool local_failure = ilu_setup_successful == 0;
if ( local_failure || parallel_failure )
{
throw Dune::MatrixBlockError();
}
// store ILU in simple CRS format
detail::convertToCRS( *ILU, lower_, upper_, inv_ );
}
/// \brief Reorder D if needed and return a reference to it.
Range& reorderD(const Range& d)
{
if ( ordering_.empty())
{
// As d is non-const in the apply method of the
// solver casting away constness in this particular
// setting is not undefined. It is ugly though but due
// to the preconditioner interface of dune-istl.
return const_cast<Range&>(d);
}
else
{
reorderedD_.resize(d.size());
std::size_t i = 0;
for(auto index: ordering_)
{
reorderedD_[index]=d[i++];
}
return reorderedD_;
}
}
/// \brief Reorder V if needed and return a reference to it.
Domain& reorderV(Domain& v)
{
if ( ordering_.empty())
{
return v;
}
else
{
reorderedV_.resize(v.size());
std::size_t i = 0;
for(auto index: ordering_)
{
reorderedV_[index]=v[i++];
}
return reorderedV_;
}
}
void reorderBack(const Range& reorderedV, Range& v)
{
if ( !ordering_.empty() )
{
std::size_t i = 0;
for(auto index: ordering_)
{
v[i++] = reorderedV[index];
}
}
}
protected:
//! \brief The ILU0 decomposition of the matrix.
CRS lower_;
CRS upper_;
std::vector< block_type > inv_;
//! \brief the reordering of the unknowns
std::vector< std::size_t > ordering_;
//! \brief The reordered right hand side
Range reorderedD_;
//! \brief The reordered left hand side.
Domain reorderedV_;
const ParallelInfo* comm_;
//! \brief The relaxation factor to use.
const field_type w_;
const bool relaxation_;
};
} // end namespace Opm
#endif