GeneralMatrixVector_MKL.h
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27  ********************************************************************************
28  * Content : Eigen bindings to Intel(R) MKL
29  * General matrix-vector product functionality based on ?GEMV.
30  ********************************************************************************
31 */
32 
33 #ifndef EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
34 #define EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
35 
36 namespace Eigen {
37 
38 namespace internal {
39 
40 /**********************************************************************
41 * This file implements general matrix-vector multiplication using BLAS
42 * gemv function via partial specialization of
43 * general_matrix_vector_product::run(..) method for float, double,
44 * std::complex<float> and std::complex<double> types
45 **********************************************************************/
46 
47 // gemv specialization
48 
49 template<typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs>
51  general_matrix_vector_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,ConjugateRhs,BuiltIn> {};
52 
53 #define EIGEN_MKL_GEMV_SPECIALIZE(Scalar) \
54 template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
55 struct general_matrix_vector_product<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
56 static void run( \
57  Index rows, Index cols, \
58  const Scalar* lhs, Index lhsStride, \
59  const Scalar* rhs, Index rhsIncr, \
60  Scalar* res, Index resIncr, Scalar alpha) \
61 { \
62  if (ConjugateLhs) { \
63  general_matrix_vector_product<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs,BuiltIn>::run( \
64  rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
65  } else { \
66  general_matrix_vector_product_gemv<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
67  rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
68  } \
69 } \
70 }; \
71 template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
72 struct general_matrix_vector_product<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
73 static void run( \
74  Index rows, Index cols, \
75  const Scalar* lhs, Index lhsStride, \
76  const Scalar* rhs, Index rhsIncr, \
77  Scalar* res, Index resIncr, Scalar alpha) \
78 { \
79  general_matrix_vector_product_gemv<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
80  rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
81 } \
82 }; \
83 
88 
89 #define EIGEN_MKL_GEMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLPREFIX) \
90 template<typename Index, int LhsStorageOrder, bool ConjugateLhs, bool ConjugateRhs> \
91 struct general_matrix_vector_product_gemv<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,ConjugateRhs> \
92 { \
93 typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> GEMVVector;\
94 \
95 static void run( \
96  Index rows, Index cols, \
97  const EIGTYPE* lhs, Index lhsStride, \
98  const EIGTYPE* rhs, Index rhsIncr, \
99  EIGTYPE* res, Index resIncr, EIGTYPE alpha) \
100 { \
101  MKL_INT m=rows, n=cols, lda=lhsStride, incx=rhsIncr, incy=resIncr; \
102  MKLTYPE alpha_, beta_; \
103  const EIGTYPE *x_ptr, myone(1); \
104  char trans=(LhsStorageOrder==ColMajor) ? 'N' : (ConjugateLhs) ? 'C' : 'T'; \
105  if (LhsStorageOrder==RowMajor) { \
106  m=cols; \
107  n=rows; \
108  }\
109  assign_scalar_eig2mkl(alpha_, alpha); \
110  assign_scalar_eig2mkl(beta_, myone); \
111  GEMVVector x_tmp; \
112  if (ConjugateRhs) { \
113  Map<const GEMVVector, 0, InnerStride<> > map_x(rhs,cols,1,InnerStride<>(incx)); \
114  x_tmp=map_x.conjugate(); \
115  x_ptr=x_tmp.data(); \
116  incx=1; \
117  } else x_ptr=rhs; \
118  MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \
119 }\
120 };
121 
122 EIGEN_MKL_GEMV_SPECIALIZATION(double, double, d)
123 EIGEN_MKL_GEMV_SPECIALIZATION(float, float, s)
124 EIGEN_MKL_GEMV_SPECIALIZATION(dcomplex, MKL_Complex16, z)
125 EIGEN_MKL_GEMV_SPECIALIZATION(scomplex, MKL_Complex8, c)
126 
127 } // end namespase internal
128 
129 } // end namespace Eigen
130 
131 #endif // EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
#define EIGEN_MKL_GEMV_SPECIALIZATION(EIGTYPE, MKLTYPE, MKLPREFIX)
iterative scaling algorithm to equilibrate rows and column norms in matrices
Definition: matrix.hpp:471
#define EIGEN_MKL_GEMV_SPECIALIZE(Scalar)


acado
Author(s): Milan Vukov, Rien Quirynen
autogenerated on Mon Jun 10 2019 12:34:38