mirror of
https://github.com/OPM/opm-simulators.git
synced 2024-12-28 02:00:59 -06:00
1031 lines
33 KiB
C++
1031 lines
33 KiB
C++
/*
|
|
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/simulators/linalg/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;
|
|
|
|
#if DUNE_VERSION_NEWER(DUNE_ISTL, 2, 7)
|
|
typedef std::shared_ptr< T > ParallelOverlappingILU0Pointer;
|
|
#else
|
|
typedef T* ParallelOverlappingILU0Pointer;
|
|
#endif
|
|
|
|
static inline ParallelOverlappingILU0Pointer construct(Arguments& args)
|
|
{
|
|
return ParallelOverlappingILU0Pointer(
|
|
new T(args.getMatrix(),
|
|
args.getComm(),
|
|
args.getArgs().getN(),
|
|
args.getArgs().relaxationFactor,
|
|
args.getArgs().getMilu()) );
|
|
}
|
|
|
|
#if ! DUNE_VERSION_NEWER(DUNE_ISTL, 2, 7)
|
|
// this method is not needed anymore in 2.7 since std::shared_ptr is used
|
|
static inline void deconstruct(T* bp)
|
|
{
|
|
delete bp;
|
|
}
|
|
#endif
|
|
|
|
};
|
|
|
|
} // end namespace Amg
|
|
|
|
|
|
|
|
} // end namespace Dune
|
|
|
|
namespace Opm
|
|
{
|
|
namespace detail
|
|
{
|
|
struct Reorderer
|
|
{
|
|
virtual std::size_t operator[](std::size_t i) const = 0;
|
|
virtual ~Reorderer() {}
|
|
};
|
|
|
|
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];
|
|
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() );
|
|
|
|
// Count the lower and upper matrix entries.
|
|
size_type numLower = 0;
|
|
size_type numUpper = 0;
|
|
const auto endi = A.end();
|
|
for (auto i = A.begin(); i != endi; ++i) {
|
|
const size_type iIndex = i.index();
|
|
size_type numLowerRow = 0;
|
|
for (auto j = (*i).begin(); j.index() < iIndex; ++j) {
|
|
++numLowerRow;
|
|
}
|
|
numLower += numLowerRow;
|
|
numUpper += (*i).size() - numLowerRow - 1;
|
|
}
|
|
assert(numLower + numUpper + A.N() == A.nonzeroes());
|
|
|
|
lower.reserveAdditional( numLower );
|
|
|
|
// implement left looking variant with stored inverse
|
|
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();
|
|
|
|
// 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;
|
|
}
|
|
|
|
assert(colcount == numLower);
|
|
|
|
const auto rendi = A.beforeBegin();
|
|
row = 0;
|
|
colcount = 0;
|
|
upper.rows_[ 0 ] = colcount ;
|
|
|
|
upper.reserveAdditional( numUpper );
|
|
|
|
// 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();
|
|
|
|
// 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;
|
|
}
|
|
assert(colcount == numUpper);
|
|
}
|
|
} // 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:
|
|
Dune::SolverCategory::Category category() const override
|
|
{
|
|
return std::is_same<ParallelInfoT, Dune::Amg::SequentialInformation>::value ?
|
|
Dune::SolverCategory::sequential : Dune::SolverCategory::overlapping;
|
|
}
|
|
|
|
/*! \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) override
|
|
{
|
|
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) override
|
|
{
|
|
Range& md = reorderD(d);
|
|
Domain& mv = reorderV(v);
|
|
|
|
// 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
|
|
}
|
|
|
|
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) override
|
|
{
|
|
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
|