/usr/include/trilinos/Trilinos_Details_LinearSolver.hpp is in libtrilinos-teuchos-dev 12.4.2-2.
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#ifndef TRILINOS_DETAILS_LINEARSOLVER_HPP
#define TRILINOS_DETAILS_LINEARSOLVER_HPP
/// \file Trilinos_Details_LinearSolver.hpp
/// \brief Declaration of linear solver interface.
///
/// \warning This header file is NOT currently part of the public
/// interface of Trilinos. It or its contents may change or
/// disappear at any time.
///
/// \note To developers: The LinearSolver interface must live in the
/// bottom-most (most upstream) package from all solvers that depend
/// on it.
#include "TeuchosRemainder_config.h"
#include "Teuchos_RCP.hpp"
namespace Teuchos {
// Forward declaration of ParameterList. If you actually want to
// _use_ ParameterList, you MUST include Teuchos_ParameterList.hpp.
class ParameterList;
} // namespace Teuchos
/// \namespace Trilinos
/// \brief Namespace of things generally useful to many Trilinos packages
namespace Trilinos {
/// \namespace Details
/// \brief Namespace of implementation details
///
/// \warning This namespace, and anything in it, is an implementation
/// detail of Trilinos. Do not rely on this namespace or its
/// contents. They may change or disappear at any time.
namespace Details {
/// \brief Interface for a method for solving linear system(s) AX=B.
///
/// \tparam MV Type of a (multi)vector, representing either the
/// solution(s) X or the right-hand side(s) B of a linear system
/// AX=B. For example, with Tpetra, use a Tpetra::MultiVector
/// specialization. A <i>multivector</i> is a single data structure
/// containing zero or more vectors with the same dimensions and
/// layout.
///
/// \tparam OP Type of a matrix or linear operator that this
/// LinearSolver understands. For example, for Tpetra, use a
/// Tpetra::Operator specialization.
///
/// \tparam NormType Type of the norm of a vector (see \c MV); in
/// particular, the type of the norm of a <i>residual</i>
/// \f$b - A \tilde{x}\f$, where \f$\tilde{x}\f$ is an approximate
/// solution of the linear system \f$Ax = b\f$. For
/// <tt>MV = Tpetra::MultiVector</tt>, use
/// <tt>NormType = MV::mag_type</tt>. In general, if the entries
/// of \c MV have type \c double, and the solver uses the
/// Euclidean norm (i.e., the 2-norm), then
/// <tt>NormType = double</tt>. If the entries of \c MV have type
/// <tt>std::complex<float></tt>, then <tt>NormType = float</tt>.
///
/// A LinearSolver knows how to solve linear systems AX=B, where A is
/// a linear operator ("matrix") and B the right-hand side(s).
///
/// This interface separates "setup" from "solves." "Setup" depends
/// only on the matrix A, while solves also depend on the right-hand
/// side(s) B and possibly also on initial guess(es). "Setup" may be
/// more expensive than solve, but it can be reused for different
/// right-hand side(s) and initial guess(es). The LinearSolver
/// interface further divides setup into two phases: "symbolic" and
/// "numeric."
///
/// The "symbolic" phase depends only on the "structure" of the
/// matrix, and not its values. By "structure," we mean
/// <ul>
/// <li> its dimensions, </li>
/// <li> its distribution over parallel processes, and most
/// specifically, </li>
/// <li> the pattern of which entries in the matrix are
/// nonzero. <li>
/// </ul>
///
/// The distinction between "structure" and "values" matters most for
/// sparse matrices. If the structure of a matrix does not change,
/// LinearSolver can reuse the "symbolic" setup phase for multiple
/// solves, even if the values in the matrix change between solves.
/// If the structure of a matrix changes, you must ask LinearSolver to
/// recompute the symbolic setup.
///
/// The "numeric" setup phase depends on both the matrix's structure,
/// and the values of its entries. If the values in the matrix
/// change, you must ask the solver to recompute the numeric setup.
/// If only the values changed but not the matrix's structure, then
/// you do <i>not</i> need to ask the solver to recompute the symbolic
/// setup. The symbolic setup must be done before the numeric setup.
///
/// \note To implementers: For the \c OP template parameter, you
/// should <i>consistently</i> use the most abstract base class that
/// makes sense. For example, with Tpetra, use Tpetra::Operator,
/// and for Epetra, use Epetra_Operator. Implementations should use
/// dynamic_cast to get the subclass that they want, and throw an
/// exception if the dynamic_cast fails. I emphasized
/// "consistently," because this makes explicit template
/// instantiation (ETI) easier, and helps keep build times and
/// library sizes small.
template<class MV, class OP, class NormType>
class LinearSolver {
public:
//! Destructor (virtual for memory safety of derived classes).
virtual ~LinearSolver () {}
/// \brief Set the solver's matrix.
///
/// \param A [in] Pointer to the matrix A in the linear system(s)
/// AX=B to solve.
///
/// This LinearSolver instance keeps the matrix (by pointer) given
/// to it by this method, and does not modify it. The solver stores
/// any additional data needed for solves separately from the
/// matrix.
///
/// Calling this method resets the solver's state. After calling
/// this method, you must call symbolic() and numeric() before you
/// may call solve().
///
/// You are allowed to change the structure and/or numerical values
/// in the matrix that this LinearSolver instance holds. If you do
/// so, you do NOT need to call this method. If you change the
/// graph structure of the matrix, you must call symbolic() and
/// numeric() before you may call solve(). If you change the
/// numerical values but not the graph structure of the matrix, you
/// must call numeric() before you may call solve().
///
/// Teuchos::RCP is just like std::shared_ptr. It uses reference
/// counting for automatic deallocation. Passing in a "const OP"
/// implies that the solver may not modify A.
virtual void setMatrix (const Teuchos::RCP<const OP>& A) = 0;
/// \brief Get a pointer to this solver's matrix.
///
/// If this LinearSolver instance does not (yet) have a matrix, this
/// method will return Teuchos::null. The solver <i>must</i> have a
/// matrix before you may call solve().
///
/// Teuchos::RCP is just like std::shared_ptr. It uses reference
/// counting for automatic deallocation. Returning a "const OP"
/// implies that the caller may not modify A.
virtual Teuchos::RCP<const OP> getMatrix () const = 0;
/// \brief Solve the linear system(s) AX=B.
///
/// \param X [in/out] On input: (multi)vector that is allocated and
/// ready for output. The solver may choose to read the contents
/// as the initial guess(es). On output: the solution vector(s).
///
/// \param B [in] Right-hand side(s) of the linear system(s).
///
/// Solves may fail. "Failure" depends on the accuracy that the
/// specific solver promises. The caller is responsible for
/// determining whether the solve succeeded. This may require a
/// dynamic cast to ask the specific kind of solver whether it
/// succeeded, or testing some error metric (like the the residual
/// 2-norm).
virtual void solve (MV& X, const MV& B) = 0;
/// \brief Set this solver's parameters.
///
/// Depending on the solver and which parameters you set or changed,
/// you may have to recompute the symbolic or numeric setup (by
/// calling symbolic() resp. numeric()) after calling
/// setParameters(), before you may call solve() again.
///
/// Different solver implementations have different ideas about how
/// to treat parameters. Some of them (like those in Ifpack2) treat
/// the input parameter list as a complete snapshot of the desired
/// state. Many that do this also fill the input list with
/// unspecified parameters set to default values. Other solvers
/// (like those in Belos) treat the input list as a "delta" -- a set
/// of changes from the current state -- and thus generally do not
/// fill in the input list.
///
/// This interface is compatible with either variant. The solver
/// reserves the right to modify the input list, or to keep a
/// pointer to the input list. Callers are responsible for copying
/// the list if they don't want the solver to see changes, or if the
/// Teuchos::RCP is nonowning. Users are responsible for knowing
/// how the different solvers behave.
virtual void setParameters (const Teuchos::RCP<Teuchos::ParameterList>& params) = 0;
/// \brief Set up any part of the solve that depends on the
/// structure of the input matrix, but not its numerical values.
///
/// If the structure of the matrix has changed, or if you have not
/// yet called this method on this LinearSolver instance, then you
/// must call this method before you may call numeric() or solve().
///
/// There is no way that the solver can tell users whether the
/// symbolic factorization is "done," because the solver may have no
/// way to know whether the structure of the matrix has changed.
/// Users are responsible for notifying the solver of structure
/// changes, by calling symbolic(). (This is why there is no
/// "symbolicDone" Boolean method.)
///
/// \note To developers: If you find it necessary to separate
/// "preordering" from the symbolic factorization, you may use a
/// mix-in for that.
virtual void symbolic () = 0;
/// \brief Set up any part of the solve that depends on both the
/// structure and the numerical values of the input matrix.
///
/// If any values in the matrix have changed, or if you have not yet
/// called this method on this LinearSolver instance, then you must
/// call this method before you may call solve().
///
/// There is no way that the solver can tell users whether the
/// numeric factorization is "done," because the solver may have no
/// way to know whether the values of the matrix has changed. Users
/// are responsible for notifying the solver of changes to values,
/// by calling numeric(). (This is why there is no "numericDone"
/// Boolean method.)
virtual void numeric () = 0;
};
} // namespace Details
} // namespace Trilinos
#endif // TRILINOS_DETAILS_LINEARSOLVER_HPP
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