Chombo + EB + MF  3.2
Public Member Functions | Public Attributes | List of all members
BiCGStabSolver< T > Class Template Reference

#include <BiCGStabSolver.H>

Inheritance diagram for BiCGStabSolver< T >:
Inheritance graph
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Public Member Functions

 BiCGStabSolver ()
 
virtual ~BiCGStabSolver ()
 
virtual void setHomogeneous (bool a_homogeneous)
 
virtual void define (LinearOp< T > *a_op, bool a_homogeneous)
 
virtual void solve (T &a_phi, const T &a_rhs)
 solve the equation. More...
 
virtual void setConvergenceMetrics (Real a_metric, Real a_tolerance)
 Set a convergence metric, along with solver tolerance, if desired. More...
 
- Public Member Functions inherited from LinearSolver< T >
virtual ~LinearSolver ()
 

Public Attributes

bool m_homogeneous
 
LinearOp< T > * m_op
 
int m_imax
 
int m_verbosity
 
Real m_eps
 
Real m_reps
 
Real m_convergenceMetric
 
Real m_hang
 
int m_exitStatus
 
Real m_small
 
int m_numRestarts
 
int m_normType
 

Detailed Description

template<class T>
class BiCGStabSolver< T >

Elliptic solver using the BiCGStab algorithm.

Constructor & Destructor Documentation

template<class T >
BiCGStabSolver< T >::BiCGStabSolver ( )
template<class T >
BiCGStabSolver< T >::~BiCGStabSolver ( )
virtual

Member Function Documentation

template<class T>
virtual void BiCGStabSolver< T >::setHomogeneous ( bool  a_homogeneous)
inlinevirtual

reset whether the solver is homogeneous.

Implements LinearSolver< T >.

Reimplemented in MergeSolver< T >.

template<class T>
void BiCGStabSolver< T >::define ( LinearOp< T > *  a_op,
bool  a_homogeneous 
)
virtual

define the solver. a_op is the linear operator. a_homogeneous is whether the solver uses homogeneous boundary conditions.

Implements LinearSolver< T >.

Reimplemented in MergeSolver< T >.

template<class T>
void BiCGStabSolver< T >::solve ( T &  a_phi,
const T &  a_rhs 
)
virtual

solve the equation.

Implements LinearSolver< T >.

Reimplemented in MergeSolver< T >.

References Abs(), CH_assert, CH_START, CH_STOP, CH_TIME, CH_TIMER, CH_TIMERS, norm(), and pout().

template<class T >
void BiCGStabSolver< T >::setConvergenceMetrics ( Real  a_metric,
Real  a_tolerance 
)
virtual

Set a convergence metric, along with solver tolerance, if desired.

Default implementation does nothing, since there are probably cases (liked direct solves), where this has no real meaning.

Reimplemented from LinearSolver< T >.

Reimplemented in MergeSolver< T >.

Member Data Documentation

template<class T>
bool BiCGStabSolver< T >::m_homogeneous

public member data: whether the solver is restricted to homogeneous boundary conditions

Referenced by BiCGStabSolver< LevelData< T > >::setHomogeneous().

template<class T>
LinearOp<T>* BiCGStabSolver< T >::m_op

public member data: operator to solve.

template<class T>
int BiCGStabSolver< T >::m_imax

public member data: maximum number of iterations

template<class T>
int BiCGStabSolver< T >::m_verbosity

public member data: how much screen out put the user wants. set = 0 for no output.

Referenced by MultilevelLinearOp< T >::define().

template<class T>
Real BiCGStabSolver< T >::m_eps

public member data: solver tolerance

template<class T>
Real BiCGStabSolver< T >::m_reps

public member data: relative solver tolerance

template<class T>
Real BiCGStabSolver< T >::m_convergenceMetric

public member data: solver convergence metric – if negative, use initial residual; if positive, then use m_convergenceMetric

template<class T>
Real BiCGStabSolver< T >::m_hang

public member data: minium norm of solution should change per iterations

template<class T>
int BiCGStabSolver< T >::m_exitStatus

public member data: set = -1 if solver exited for an unknown reason set = 1 if solver converged to tolerance set = 2 if rho = 0 set = 3 if max number of restarts was reached

template<class T>
Real BiCGStabSolver< T >::m_small

public member data: what the algorithm should consider "close to zero"

template<class T>
int BiCGStabSolver< T >::m_numRestarts

public member data: number of times the algorithm can restart

template<class T>
int BiCGStabSolver< T >::m_normType

public member data: norm to be used when evaluation convergence. 0 is max norm, 1 is L(1), 2 is L(2) and so on.


The documentation for this class was generated from the following file: