source: branches/HeuristicLab.Problems.GaussianProcessTuning/HeuristicLab.Eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h @ 9562

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 ********************************************************************************
 *   Content : Eigen bindings to Intel(R) MKL
 *   Selfadjoint matrix-vector product functionality based on ?SYMV/HEMV.
 ********************************************************************************
*/

#ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
#define EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H

namespace Eigen { 

namespace internal {

/**********************************************************************
* This file implements selfadjoint matrix-vector multiplication using BLAS
**********************************************************************/

// symv/hemv specialization

template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
struct selfadjoint_matrix_vector_product_symv :
  selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn> {};

#define EIGEN_MKL_SYMV_SPECIALIZE(Scalar) \
template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
struct selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Specialized> { \
static EIGEN_DONT_INLINE void run( \
  Index size, const Scalar*  lhs, Index lhsStride, \
  const Scalar* _rhs, Index rhsIncr, Scalar* res, Scalar alpha) { \
    enum {\
      IsColMajor = StorageOrder==ColMajor \
    }; \
    if (IsColMajor == ConjugateLhs) {\
      selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn>::run( \
        size, lhs, lhsStride, _rhs, rhsIncr, res, alpha);  \
    } else {\
      selfadjoint_matrix_vector_product_symv<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs>::run( \
        size, lhs, lhsStride, _rhs, rhsIncr, res, alpha);  \
    }\
  } \
}; \

EIGEN_MKL_SYMV_SPECIALIZE(double)
EIGEN_MKL_SYMV_SPECIALIZE(float)
EIGEN_MKL_SYMV_SPECIALIZE(dcomplex)
EIGEN_MKL_SYMV_SPECIALIZE(scomplex)

#define EIGEN_MKL_SYMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLFUNC) \
template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
struct selfadjoint_matrix_vector_product_symv<EIGTYPE,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs> \
{ \
typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> SYMVVector;\
\
static EIGEN_DONT_INLINE void run( \
Index size, const EIGTYPE*  lhs, Index lhsStride, \
const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* res, EIGTYPE alpha) \
{ \
  enum {\
    IsRowMajor = StorageOrder==RowMajor ? 1 : 0, \
    IsLower = UpLo == Lower ? 1 : 0 \
  }; \
  MKL_INT n=size, lda=lhsStride, incx=rhsIncr, incy=1; \
  MKLTYPE alpha_, beta_; \
  const EIGTYPE *x_ptr, myone(1); \
  char uplo=(IsRowMajor) ? (IsLower ? 'U' : 'L') : (IsLower ? 'L' : 'U'); \
  assign_scalar_eig2mkl(alpha_, alpha); \
  assign_scalar_eig2mkl(beta_, myone); \
  SYMVVector x_tmp; \
  if (ConjugateRhs) { \
    Map<const SYMVVector, 0, InnerStride<> > map_x(_rhs,size,1,InnerStride<>(incx)); \
    x_tmp=map_x.conjugate(); \
    x_ptr=x_tmp.data(); \
    incx=1; \
  } else x_ptr=_rhs; \
  MKLFUNC(&uplo, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \
}\
};

EIGEN_MKL_SYMV_SPECIALIZATION(double,   double,        dsymv)
EIGEN_MKL_SYMV_SPECIALIZATION(float,    float,         ssymv)
EIGEN_MKL_SYMV_SPECIALIZATION(dcomplex, MKL_Complex16, zhemv)
EIGEN_MKL_SYMV_SPECIALIZATION(scomplex, MKL_Complex8,  chemv)

} // end namespace internal

} // end namespace Eigen

#endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H