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#ifndef ROCALUTION_KRYLOV_FCG_HPP_
#define ROCALUTION_KRYLOV_FCG_HPP_

#include "../solver.hpp"
#include "export.hpp"

#include <vector>

namespace rocalution
{

    /** \ingroup solver_module
  * \class FCG
  * \brief Flexible Conjugate Gradient Method
  * \details
  * The Flexible Conjugate Gradient method is an iterative method for solving sparse
  * symmetric positive definite linear systems \f$Ax=b\f$. It is similar to the Conjugate
  * Gradient method with the only difference, that it allows the preconditioner
  * \f$M^{-1}\f$ to be not a constant operator. This can be especially helpful if the
  * operation \f$M^{-1}x\f$ is the result of another iterative process and not a constant
  * operator.
  * \cite fcg
  *
  * \tparam OperatorType - can be LocalMatrix or GlobalMatrix
  * \tparam VectorType - can be LocalVector or GlobalVector
  * \tparam ValueType - can be float, double, std::complex<float> or std::complex<double>
  */
    template <class OperatorType, class VectorType, typename ValueType>
    class FCG : public IterativeLinearSolver<OperatorType, VectorType, ValueType>
    {
    public:
        ROCALUTION_EXPORT
        FCG();
        ROCALUTION_EXPORT
        virtual ~FCG();

        ROCALUTION_EXPORT
        virtual void Print(void) const;

        ROCALUTION_EXPORT
        virtual void Build(void);
        ROCALUTION_EXPORT
        virtual void ReBuildNumeric(void);
        ROCALUTION_EXPORT
        virtual void Clear(void);

    protected:
        virtual void SolveNonPrecond_(const VectorType& rhs, VectorType* x);
        virtual void SolvePrecond_(const VectorType& rhs, VectorType* x);

        virtual void PrintStart_(void) const;
        virtual void PrintEnd_(void) const;

        virtual void MoveToHostLocalData_(void);
        virtual void MoveToAcceleratorLocalData_(void);

    private:
        VectorType r_, w_, z_;
        VectorType p_, q_;
    };

} // namespace rocalution

#endif // ROCALUTION_KRYLOV_FCG_HPP_