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      1 /*
      2  Copyright (c) 2011, Intel Corporation. All rights reserved.
      3 
      4  Redistribution and use in source and binary forms, with or without modification,
      5  are permitted provided that the following conditions are met:
      6 
      7  * Redistributions of source code must retain the above copyright notice, this
      8    list of conditions and the following disclaimer.
      9  * Redistributions in binary form must reproduce the above copyright notice,
     10    this list of conditions and the following disclaimer in the documentation
     11    and/or other materials provided with the distribution.
     12  * Neither the name of Intel Corporation nor the names of its contributors may
     13    be used to endorse or promote products derived from this software without
     14    specific prior written permission.
     15 
     16  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
     17  ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
     18  WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
     19  DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
     20  ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
     21  (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
     22  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
     23  ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
     24  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
     25  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
     26 
     27  ********************************************************************************
     28  *   Content : Eigen bindings to Intel(R) MKL
     29  *   Triangular matrix-vector product functionality based on ?TRMV.
     30  ********************************************************************************
     31 */
     32 
     33 #ifndef EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
     34 #define EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
     35 
     36 namespace Eigen {
     37 
     38 namespace internal {
     39 
     40 /**********************************************************************
     41 * This file implements triangular matrix-vector multiplication using BLAS
     42 **********************************************************************/
     43 
     44 // trmv/hemv specialization
     45 
     46 template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
     47 struct triangular_matrix_vector_product_trmv :
     48   triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,StorageOrder,BuiltIn> {};
     49 
     50 #define EIGEN_MKL_TRMV_SPECIALIZE(Scalar) \
     51 template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
     52 struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor,Specialized> { \
     53  static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
     54                                      const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
     55       triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor>::run( \
     56         _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
     57   } \
     58 }; \
     59 template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
     60 struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor,Specialized> { \
     61  static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
     62                                      const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
     63       triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor>::run( \
     64         _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
     65   } \
     66 };
     67 
     68 EIGEN_MKL_TRMV_SPECIALIZE(double)
     69 EIGEN_MKL_TRMV_SPECIALIZE(float)
     70 EIGEN_MKL_TRMV_SPECIALIZE(dcomplex)
     71 EIGEN_MKL_TRMV_SPECIALIZE(scomplex)
     72 
     73 // implements col-major: res += alpha * op(triangular) * vector
     74 #define EIGEN_MKL_TRMV_CM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
     75 template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
     76 struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor> { \
     77   enum { \
     78     IsLower = (Mode&Lower) == Lower, \
     79     SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
     80     IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
     81     IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
     82     LowUp = IsLower ? Lower : Upper \
     83   }; \
     84  static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
     85                              const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
     86  { \
     87    if (ConjLhs || IsZeroDiag) { \
     88      triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor,BuiltIn>::run( \
     89        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
     90      return; \
     91    }\
     92    Index size = (std::min)(_rows,_cols); \
     93    Index rows = IsLower ? _rows : size; \
     94    Index cols = IsLower ? size : _cols; \
     95 \
     96    typedef VectorX##EIGPREFIX VectorRhs; \
     97    EIGTYPE *x, *y;\
     98 \
     99 /* Set x*/ \
    100    Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
    101    VectorRhs x_tmp; \
    102    if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
    103    x = x_tmp.data(); \
    104 \
    105 /* Square part handling */\
    106 \
    107    char trans, uplo, diag; \
    108    MKL_INT m, n, lda, incx, incy; \
    109    EIGTYPE const *a; \
    110    MKLTYPE alpha_, beta_; \
    111    assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
    112    assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
    113 \
    114 /* Set m, n */ \
    115    n = (MKL_INT)size; \
    116    lda = lhsStride; \
    117    incx = 1; \
    118    incy = resIncr; \
    119 \
    120 /* Set uplo, trans and diag*/ \
    121    trans = 'N'; \
    122    uplo = IsLower ? 'L' : 'U'; \
    123    diag = IsUnitDiag ? 'U' : 'N'; \
    124 \
    125 /* call ?TRMV*/ \
    126    MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
    127 \
    128 /* Add op(a_tr)rhs into res*/ \
    129    MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
    130 /* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
    131    if (size<(std::max)(rows,cols)) { \
    132      typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
    133      if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
    134      x = x_tmp.data(); \
    135      if (size<rows) { \
    136        y = _res + size*resIncr; \
    137        a = _lhs + size; \
    138        m = rows-size; \
    139        n = size; \
    140      } \
    141      else { \
    142        x += size; \
    143        y = _res; \
    144        a = _lhs + size*lda; \
    145        m = size; \
    146        n = cols-size; \
    147      } \
    148      MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
    149    } \
    150   } \
    151 };
    152 
    153 EIGEN_MKL_TRMV_CM(double, double, d, d)
    154 EIGEN_MKL_TRMV_CM(dcomplex, MKL_Complex16, cd, z)
    155 EIGEN_MKL_TRMV_CM(float, float, f, s)
    156 EIGEN_MKL_TRMV_CM(scomplex, MKL_Complex8, cf, c)
    157 
    158 // implements row-major: res += alpha * op(triangular) * vector
    159 #define EIGEN_MKL_TRMV_RM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
    160 template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
    161 struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor> { \
    162   enum { \
    163     IsLower = (Mode&Lower) == Lower, \
    164     SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
    165     IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
    166     IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
    167     LowUp = IsLower ? Lower : Upper \
    168   }; \
    169  static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
    170                              const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
    171  { \
    172    if (IsZeroDiag) { \
    173      triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor,BuiltIn>::run( \
    174        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
    175      return; \
    176    }\
    177    Index size = (std::min)(_rows,_cols); \
    178    Index rows = IsLower ? _rows : size; \
    179    Index cols = IsLower ? size : _cols; \
    180 \
    181    typedef VectorX##EIGPREFIX VectorRhs; \
    182    EIGTYPE *x, *y;\
    183 \
    184 /* Set x*/ \
    185    Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
    186    VectorRhs x_tmp; \
    187    if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
    188    x = x_tmp.data(); \
    189 \
    190 /* Square part handling */\
    191 \
    192    char trans, uplo, diag; \
    193    MKL_INT m, n, lda, incx, incy; \
    194    EIGTYPE const *a; \
    195    MKLTYPE alpha_, beta_; \
    196    assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
    197    assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
    198 \
    199 /* Set m, n */ \
    200    n = (MKL_INT)size; \
    201    lda = lhsStride; \
    202    incx = 1; \
    203    incy = resIncr; \
    204 \
    205 /* Set uplo, trans and diag*/ \
    206    trans = ConjLhs ? 'C' : 'T'; \
    207    uplo = IsLower ? 'U' : 'L'; \
    208    diag = IsUnitDiag ? 'U' : 'N'; \
    209 \
    210 /* call ?TRMV*/ \
    211    MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
    212 \
    213 /* Add op(a_tr)rhs into res*/ \
    214    MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
    215 /* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
    216    if (size<(std::max)(rows,cols)) { \
    217      typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
    218      if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
    219      x = x_tmp.data(); \
    220      if (size<rows) { \
    221        y = _res + size*resIncr; \
    222        a = _lhs + size*lda; \
    223        m = rows-size; \
    224        n = size; \
    225      } \
    226      else { \
    227        x += size; \
    228        y = _res; \
    229        a = _lhs + size; \
    230        m = size; \
    231        n = cols-size; \
    232      } \
    233      MKLPREFIX##gemv(&trans, &n, &m, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
    234    } \
    235   } \
    236 };
    237 
    238 EIGEN_MKL_TRMV_RM(double, double, d, d)
    239 EIGEN_MKL_TRMV_RM(dcomplex, MKL_Complex16, cd, z)
    240 EIGEN_MKL_TRMV_RM(float, float, f, s)
    241 EIGEN_MKL_TRMV_RM(scomplex, MKL_Complex8, cf, c)
    242 
    243 } // end namespase internal
    244 
    245 } // end namespace Eigen
    246 
    247 #endif // EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
    248