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// Teko: A package for block and physics based preconditioning
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#ifndef __Teko_LSCStrategy_hpp__
#define __Teko_LSCStrategy_hpp__
#include "Teuchos_RCP.hpp"
#include "Thyra_LinearOpBase.hpp"
#include "Teko_Utilities.hpp"
#include "Teko_InverseFactory.hpp"
#include "Teko_BlockPreconditionerFactory.hpp"
namespace Teko {
namespace NS {
class LSCPrecondState; // forward declaration
/** \brief Strategy for driving LSCPreconditionerFactory.
*
* Strategy for driving the LSCPreconditionerFactory. This
* class provides all the pieces required by the LSC preconditioner.
* The intent is that the user can overide them and build
* there own implementation. Though a fairly substantial implementation
* is provided in <code>InvLSCStrategy</code>.
*
* The basics of this method can be found in
*
* [1] Elman, Howle, Shadid, Silvester, and Tuminaro, "Least Squares Preconditioners
* for Stabilized Discretizations of the Navier-Stokes Euqations," SISC-2007.
*
* [2] Elman, and Tuminaro, "Boundary Conditions in Approximate Commutator
* Preconditioners for the Navier-Stokes Equations," In press (8/2009)?
*
* The Least Squares Commuator preconditioner provides a (nearly) Algebraic approximation
* of the Schur complement of the (Navier-)Stokes system
*
* \f$ A = \left[\begin{array}{cc}
* F & B^T \\
* B & C
* \end{array}\right] \f$
*
* The approximation to the Schur complement is
*
* \f$ C - B F^{-1} B^T \approx (B \hat{Q}_u^{-1} B^T - \gamma C)^{-1}
* (B \hat{Q}_u^{-1} F H B^T+C_I) (B H B^T - \gamma C)^{-1}
* + C_O \f$.
*
* Where \f$\hat{Q}_u\f$ is typically a diagonal approximation of the mass matrix,
* and \f$H\f$ is an appropriate diagonal scaling matrix (see [2] for details).
* The scalars \f$\alpha\f$ and \f$\gamma\f$ are chosen to stabilize an unstable
* discretization (for the case of \f$C\neq 0\f$). If the system is stable then
* they can be set to \f$0\f$ (see [1] for more details).
*
* In order to approximate \f$A\f$ two decompositions can be chosen, a full LU
* decomposition and a purely upper triangular version. A full LU decomposition
* requires that the velocity convection-diffusion operator (\f$F\f$) is inverted
* twice, while an upper triangular approximation requires only a single inverse.
*
* The methods of this strategy provide the different pieces. For instance
* <code>getInvF</code> provides \f$F^{-1}\f$. Similarly there are calls to get
* the inverses of \f$B \hat{Q}_u^{-1} B^T - \gamma C\f$,
* \f$B \hat{Q}_u^{-1} B^T - \gamma C\f$, and \f$\hat{Q}_u^{-1}\f$ as well as
* the \f$H\f$ operator. All these methods are required by the
* <code>LSCPreconditionerFactory</code>. Additionally there is a
* <code>buildState</code> method that is called everytime a preconditiner is
* (re)constructed. This is to allow for any preprocessing neccessary to be
* handled.
*
* The final set of methods help construct a LSCStrategy object, they are
* primarily used by the parameter list construction inteface. They are
* more advanced and can be ignored by initial implementations of this
* class.
*/
class LSCStrategy {
public:
virtual ~LSCStrategy() {}
/** This informs the strategy object to build the state associated
* with this operator.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*/
virtual void buildState(BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
/** Get the inverse of \f$B Q_u^{-1} B^T - \gamma C\f$.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns An (approximate) inverse of \f$B Q_u^{-1} B^T - \gamma C\f$.
*/
virtual LinearOp getInvBQBt(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
/** Get the inverse of \f$B H B^T - \gamma C\f$.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns An (approximate) inverse of \f$B H B^T - \gamma C\f$.
*/
virtual LinearOp getInvBHBt(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
/** Get the inverse of the \f$F\f$ block.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns An (approximate) inverse of \f$F\f$.
*/
virtual LinearOp getInvF(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
#if 0
/** Get the inverse for stabilizing the whole Schur complement approximation.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns The operator to stabilize the whole Schur complement (\f$\alpha D^{-1} \f$).
*/
virtual LinearOp getInvAlphaD(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
#endif
/** Get the inverse to stablized stabilizing the Schur complement approximation using
* a placement on the ``outside''. That is what is the value for \f$C_O\f$. This quantity
* may be null.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns The operator to stabilize the whole Schur complement (originally \f$\alpha D^{-1} \f$).
*/
virtual LinearOp getOuterStabilization(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
/** Get the inverse to stablized stabilizing the Schur complement approximation using
* a placement on the ``inside''. That is what is the value for \f$C_I\f$. This quantity
* may be null.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns The operator to stabilize the whole Schur complement.
*/
virtual LinearOp getInnerStabilization(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
/** Get the inverse mass matrix.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns The inverse of the mass matrix \f$Q_u\f$.
*/
virtual LinearOp getInvMass(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
/** Get the \f$H\f$ scaling matrix.
*
* \param[in] A The linear operator to be preconditioned by LSC.
* \param[in] state State object for storying reusable information about
* the operator A.
*
* \returns The \f$H\f$ scaling matrix.
*/
virtual LinearOp getHScaling(const BlockedLinearOp & A,BlockPreconditionerState & state) const = 0;
/** Should the approximation of the inverse use a full LDU decomposition, or
* is a upper triangular approximation sufficient.
*
* \returns True if the full LDU decomposition should be used, otherwise
* only an upper triangular version is used.
*/
virtual bool useFullLDU() const = 0;
/** Tell strategy that this operator is supposed to be symmetric.
* Behavior of LSC is slightly different for non-symmetric case.
*
* \param[in] isSymmetric Is this operator symmetric?
*/
virtual void setSymmetric(bool isSymmetric) = 0;
//! Initialize from a parameter list
virtual void initializeFromParameterList(const Teuchos::ParameterList & pl,const InverseLibrary & invLib) {}
//! For assiting in construction of the preconditioner
virtual Teuchos::RCP<Teuchos::ParameterList> getRequestedParameters() const { return Teuchos::null;}
//! For assiting in construction of the preconditioner
virtual bool updateRequestedParameters(const Teuchos::ParameterList & pl) { return true; }
//! This method sets the request handler for this object
void setRequestHandler(const Teuchos::RCP<RequestHandler> & rh)
{ requestHandler_ = rh; }
//! This method gets the request handler uses by this object
Teuchos::RCP<RequestHandler> getRequestHandler() const
{ return requestHandler_; }
private:
Teuchos::RCP<RequestHandler> requestHandler_;
};
} // end namespace NS
} // end namespace Teko
#endif
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