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// ***********************************************************************
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// Ifpack2: Tempated Object-Oriented Algebraic Preconditioner Package
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#ifndef IFPACK2_TRIDICONTAINER_DECL_HPP
#define IFPACK2_TRIDICONTAINER_DECL_HPP
/// \file Ifpack2_TriDiContainer_decl.hpp
/// \brief Ifpack2::TriDiContainer class declaration
#include "Ifpack2_Container.hpp"
#include "Ifpack2_Details_MultiVectorLocalGatherScatter.hpp"
#include "Ifpack2_Details_LapackSupportsScalar.hpp"
#include "Tpetra_MultiVector.hpp"
#include "Tpetra_Map.hpp"
#include "Tpetra_RowMatrix.hpp"
#include "Teuchos_SerialDenseVector.hpp"
#include "Teuchos_SerialTriDiMatrix.hpp"
#include <type_traits>
#include <string>
namespace Ifpack2 {
/// \class TriDiContainer
/// \brief Store and solve a local TriDi linear problem.
/// \tparam MatrixType A specialization of Tpetra::RowMatrix.
///
/// Please refer to the documentation of the Container
/// interface. Currently, Containers are used by BlockRelaxation.
/// Block relaxations need to be able to do two things:
/// <ol>
/// <li> Store the diagonal blocks </li>
/// <li> Solve linear systems with each diagonal block </li>
/// </ol>
/// TriDiContainer stores the diagonal blocks as TriDi matrices, and
/// solves them using LAPACK (for the four Scalar types that it
/// supports)
///
/// As with Ifpack2::Container, MatrixType must be a specialization of
/// Tpetra::RowMatrix. Using a TriDi matrix for each block is a good
/// idea when the blocks are small. For large and / or sparse blocks,
/// it would probably be better to use an implementation of Container
/// that stores the blocks sparsely, in particular SparseContainer.
/// If your matrix is banded but not tridiagonal, use BandedContainer.
///
/// This class may store the TriDi local matrix using values of a
/// different type (\c LocalScalarType) than those in \c MatrixType.
/// You may mix and match so long as implicit conversions are
/// available between \c LocalScalarType and
/// <tt>MatrixType::scalar_type</tt>.
///
/// This class currently assumes the following about the column and
/// row Maps of the input matrix:
/// <ol>
/// <li> On all processes, the column and row Maps begin with the same
/// set of on-process entries, in the same order. That is,
/// on-process row and column indices are the same.</li>
/// <li> On all processes, all off-process indices in the column Map
/// of the input matrix occur after that initial set.</li>
/// </ol>
/// These assumptions may be violated if the input matrix is a
/// Tpetra::CrsMatrix specialization that was constructed with a
/// user-provided column Map. The assumptions are not mathematically
/// necessary and could be relaxed at any time. Implementers who wish
/// to do so will need to modify the extract() method, so that it
/// translates explicitly between local row and column indices,
/// instead of just assuming that they are the same.
template<class MatrixType, class LocalScalarType,
bool lapackSupportsScalar = ::Ifpack2::Details::LapackSupportsScalar<LocalScalarType>::value>
class TriDiContainer;
template<class MatrixType, class LocalScalarType>
class TriDiContainer<MatrixType, LocalScalarType, true> :
public Container<MatrixType> {
//! @name Internal typedefs (private)
//@{
private:
/// \brief The first template parameter of this class.
///
/// This must be a Tpetra::RowMatrix specialization. It may have
/// entirely different template parameters (e.g., \c scalar_type)
/// than \c InverseType.
typedef MatrixType matrix_type;
//! The second template parameter of this class.
typedef LocalScalarType local_scalar_type;
//! The type of entries in the input (global) matrix.
typedef typename Container<MatrixType>::scalar_type scalar_type;
//! The type of local indices in the input (global) matrix.
typedef typename Container<MatrixType>::local_ordinal_type local_ordinal_type;
//! The type of global indices in the input (global) matrix.
typedef typename Container<MatrixType>::global_ordinal_type global_ordinal_type;
//! The Node type of the input (global) matrix.
typedef typename Container<MatrixType>::node_type node_type;
typedef typename Container<MatrixType>::mv_type mv_type;
typedef typename Container<MatrixType>::map_type map_type;
typedef typename Container<MatrixType>::vector_type vector_type;
typedef typename Container<MatrixType>::partitioner_type partitioner_type;
typedef typename Container<MatrixType>::import_type import_type;
typedef typename Container<MatrixType>::HostView HostView;
typedef Tpetra::MultiVector<local_scalar_type, local_ordinal_type, global_ordinal_type, node_type> local_mv_type;
typedef typename Kokkos::View<local_scalar_type**, Kokkos::HostSpace> HostViewLocal;
static_assert (std::is_same<MatrixType, Tpetra::RowMatrix<scalar_type, local_ordinal_type, global_ordinal_type, node_type>>::value,
"Ifpack2::TriDiContainer: MatrixType must be a Tpetra::RowMatrix specialization.");
/// \brief The (base class) type of the input matrix.
///
/// The input matrix to the constructor may be either a
/// Tpetra::RowMatrix specialization or a Tpetra::CrsMatrix
/// specialization. However, we want to make the constructor as
/// general as possible, so we always accept the matrix as a
/// Tpetra::RowMatrix. This typedef is the appropriate
/// specialization of Tpetra::RowMatrix.
typedef typename Container<MatrixType>::row_matrix_type row_matrix_type;
//@}
public:
//! \name Constructor and destructor
//@{
/// \brief Constructor.
///
/// \brief matrix [in] The original input matrix. This Container
/// will construct a local diagonal block from the rows given by
/// <tt>localRows</tt>.
///
/// \param localRows [in] The set of (local) rows assigned to this
/// container. <tt>localRows[i] == j</tt>, where i (from 0 to
/// <tt>getNumRows() - 1</tt>) indicates the SparseContainer's
/// row, and j indicates the local row in the calling process.
/// <tt>localRows.size()</tt> gives the number of rows in the
/// local matrix on each process. This may be different on
/// different processes.
TriDiContainer (const Teuchos::RCP<const row_matrix_type>& matrix,
const Teuchos::Array<Teuchos::Array<local_ordinal_type> >& partitions,
const Teuchos::RCP<const import_type>& importer,
int OverlapLevel,
scalar_type DampingFactor);
TriDiContainer (const Teuchos::RCP<const row_matrix_type>& matrix,
const Teuchos::Array<local_ordinal_type>& localRows);
//! Destructor (declared virtual for memory safety of derived classes).
virtual ~TriDiContainer ();
//@}
//! \name Get and set methods
//@{
//! Whether the container has been successfully initialized.
virtual bool isInitialized() const;
//! Whether the container has been successfully computed.
virtual bool isComputed() const;
//! Set all necessary parameters.
virtual void setParameters(const Teuchos::ParameterList& List);
//@}
//! \name Mathematical functions
//@{
//! Do all set-up operations that only require matrix structure.
virtual void initialize ();
//! Extract the local diagonal block and prepare the solver.
virtual void compute ();
void clearBlocks();
//! Compute <tt>Y := alpha * M^{-1} X + beta*Y</tt>.
virtual void
apply (HostView& X,
HostView& Y,
int blockIndex,
int stride,
Teuchos::ETransp mode = Teuchos::NO_TRANS,
scalar_type alpha = Teuchos::ScalarTraits<scalar_type>::one(),
scalar_type beta = Teuchos::ScalarTraits<scalar_type>::zero()) const;
void applyImpl (HostViewLocal& X,
HostViewLocal& Y,
int blockIndex,
int stride,
Teuchos::ETransp mode,
local_scalar_type alpha,
local_scalar_type beta) const;
//! Compute <tt>Y := alpha * diag(D) * M^{-1} (diag(D) * X) + beta*Y</tt>.
virtual void
weightedApply (HostView& X,
HostView& Y,
HostView& W,
int blockIndex,
int stride,
Teuchos::ETransp mode = Teuchos::NO_TRANS,
scalar_type alpha = Teuchos::ScalarTraits<scalar_type>::one(),
scalar_type beta = Teuchos::ScalarTraits<scalar_type>::zero()) const;
//@}
//! \name Miscellaneous methods
//@{
/// \brief Print information about this object to the given output stream.
///
/// operator<< uses this method.
virtual std::ostream& print (std::ostream& os) const;
//@}
//! @name Implementation of Teuchos::Describable
//@{
//! A one-line description of this object.
virtual std::string description () const;
//! Print the object with some verbosity level to the given FancyOStream.
virtual void
describe (Teuchos::FancyOStream &out,
const Teuchos::EVerbosityLevel verbLevel =
Teuchos::Describable::verbLevel_default) const;
//@}
/// \brief Get the name of this container type for Details::constructContainer()
static std::string getName();
private:
//! Copy constructor: Declared but not implemented, to forbid copy construction.
TriDiContainer (const TriDiContainer<MatrixType, LocalScalarType>& rhs);
//! Extract the submatrix identified by the local indices set by the constructor.
void extract ();
/// \brief Factor the extracted submatrix.
///
/// Call this after calling extract().
void factor ();
//! The local diagonal blocks, which compute() extracts.
std::vector<Teuchos::SerialTriDiMatrix<int, local_scalar_type>> diagBlocks_;
//! Temporary X vector used in apply().
mutable std::vector<HostViewLocal> X_local;
//! Temporary Y vector used in apply().
mutable std::vector<HostViewLocal> Y_local;
//! Permutation array from LAPACK (GETRF).
Teuchos::Array<int> ipiv_;
//! If \c true, the container has been successfully initialized.
bool IsInitialized_;
//! If \c true, the container has been successfully computed.
bool IsComputed_;
//! Scalar data for all blocks
local_scalar_type* scalars_;
//! Offsets in scalars_ array for all blocks
Teuchos::Array<int> scalarOffsets_;
};
template<class MatrixType, class LocalScalarType>
class TriDiContainer<MatrixType, LocalScalarType, false> :
public Container<MatrixType> {
//! @name Internal typedefs (private)
//@{
private:
/// \brief The first template parameter of this class.
///
/// This must be a Tpetra::RowMatrix specialization. It may have
/// entirely different template parameters (e.g., \c scalar_type)
/// than \c InverseType.
typedef MatrixType matrix_type;
//! The second template parameter of this class.
typedef LocalScalarType local_scalar_type;
//! The type of entries in the input (global) matrix.
typedef typename Container<MatrixType>::scalar_type scalar_type;
//! The type of local indices in the input (global) matrix.
typedef typename Container<MatrixType>::local_ordinal_type local_ordinal_type;
//! The type of global indices in the input (global) matrix.
typedef typename Container<MatrixType>::global_ordinal_type global_ordinal_type;
//! The Node type of the input (global) matrix.
typedef typename Container<MatrixType>::node_type node_type;
typedef typename Container<MatrixType>::mv_type mv_type;
typedef typename Container<MatrixType>::map_type map_type;
typedef typename Container<MatrixType>::vector_type vector_type;
typedef typename Container<MatrixType>::partitioner_type partitioner_type;
typedef typename Container<MatrixType>::import_type import_type;
typedef typename Container<MatrixType>::HostView HostView;
typedef Tpetra::MultiVector<local_scalar_type, local_ordinal_type, global_ordinal_type, node_type> local_mv_type;
typedef typename Kokkos::View<local_scalar_type**, Kokkos::HostSpace> HostViewLocal;
static_assert (std::is_same<MatrixType, Tpetra::RowMatrix<scalar_type, local_ordinal_type, global_ordinal_type, node_type>>::value,
"Ifpack2::TriDiContainer: MatrixType must be a Tpetra::RowMatrix specialization.");
/// \brief The (base class) type of the input matrix.
///
/// The input matrix to the constructor may be either a
/// Tpetra::RowMatrix specialization or a Tpetra::CrsMatrix
/// specialization. However, we want to make the constructor as
/// general as possible, so we always accept the matrix as a
/// Tpetra::RowMatrix. This typedef is the appropriate
/// specialization of Tpetra::RowMatrix.
typedef typename Container<MatrixType>::row_matrix_type row_matrix_type;
//@}
public:
//! \name Constructor and destructor
//@{
/// \brief Constructor.
///
/// \brief matrix [in] The original input matrix. This Container
/// will construct a local diagonal block from the rows given by
/// <tt>localRows</tt>.
///
/// \param localRows [in] The set of (local) rows assigned to this
/// container. <tt>localRows[i] == j</tt>, where i (from 0 to
/// <tt>getNumRows() - 1</tt>) indicates the SparseContainer's
/// row, and j indicates the local row in the calling process.
/// <tt>localRows.size()</tt> gives the number of rows in the
/// local matrix on each process. This may be different on
/// different processes.
TriDiContainer (const Teuchos::RCP<const row_matrix_type>& matrix,
const Teuchos::Array<Teuchos::Array<local_ordinal_type> >& partitions,
const Teuchos::RCP<const import_type>& importer,
int OverlapLevel,
scalar_type DampingFactor);
TriDiContainer (const Teuchos::RCP<const row_matrix_type>& matrix,
const Teuchos::Array<local_ordinal_type>& localRows);
//! Destructor (declared virtual for memory safety of derived classes).
virtual ~TriDiContainer ();
//@}
//! \name Get and set methods
//@{
//! Whether the container has been successfully initialized.
virtual bool isInitialized() const;
//! Whether the container has been successfully computed.
virtual bool isComputed() const;
//! Set all necessary parameters.
virtual void setParameters(const Teuchos::ParameterList& List);
//@}
//! \name Mathematical functions
//@{
//! Do all set-up operations that only require matrix structure.
virtual void initialize ();
//! Extract the local diagonal block and prepare the solver.
virtual void compute ();
void clearBlocks();
//! Compute <tt>Y := alpha * M^{-1} X + beta*Y</tt>.
virtual void
apply (HostView& X,
HostView& Y,
int blockIndex,
int stride,
Teuchos::ETransp mode = Teuchos::NO_TRANS,
scalar_type alpha = Teuchos::ScalarTraits<scalar_type>::one(),
scalar_type beta = Teuchos::ScalarTraits<scalar_type>::zero()) const;
void applyImpl (HostViewLocal& X,
HostViewLocal& Y,
int blockIndex,
int stride,
Teuchos::ETransp mode,
local_scalar_type alpha,
local_scalar_type beta) const;
//! Compute <tt>Y := alpha * diag(D) * M^{-1} (diag(D) * X) + beta*Y</tt>.
virtual void
weightedApply (HostView& X,
HostView& Y,
HostView& W,
int blockIndex,
int stride,
Teuchos::ETransp mode = Teuchos::NO_TRANS,
scalar_type alpha = Teuchos::ScalarTraits<scalar_type>::one(),
scalar_type beta = Teuchos::ScalarTraits<scalar_type>::zero()) const;
//@}
//! \name Miscellaneous methods
//@{
/// \brief Print information about this object to the given output stream.
///
/// operator<< uses this method.
virtual std::ostream& print (std::ostream& os) const;
//@}
//! @name Implementation of Teuchos::Describable
//@{
//! A one-line description of this object.
virtual std::string description () const;
//! Print the object with some verbosity level to the given FancyOStream.
virtual void
describe (Teuchos::FancyOStream &out,
const Teuchos::EVerbosityLevel verbLevel =
Teuchos::Describable::verbLevel_default) const;
//@}
/// \brief Get the name of this container type for Details::constructContainer()
static std::string getName();
private:
//! Copy constructor: Declared but not implemented, to forbid copy construction.
TriDiContainer (const TriDiContainer<MatrixType, LocalScalarType>& rhs);
//! Extract the submatrix identified by the local indices set by the constructor.
void extract ();
/// \brief Factor the extracted submatrix.
///
/// Call this after calling extract().
void factor ();
//! The local diagonal blocks, which compute() extracts.
std::vector<Teuchos::SerialTriDiMatrix<int, local_scalar_type>> diagBlocks_;
//! Temporary X vector used in apply().
mutable std::vector<HostViewLocal> X_local;
//! Temporary Y vector used in apply().
mutable std::vector<HostViewLocal> Y_local;
//! Permutation array from LAPACK (GETRF).
Teuchos::Array<int> ipiv_;
//! If \c true, the container has been successfully initialized.
bool IsInitialized_;
//! If \c true, the container has been successfully computed.
bool IsComputed_;
//! Scalar data for all blocks
local_scalar_type* scalars_;
//! Offsets in scalars_ array for all blocks
Teuchos::Array<int> scalarOffsets_;
};
}// namespace Ifpack2
#endif // IFPACK2_TRIDICONTAINER_DECL_HPP
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