1 | /*
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2 | Copyright (c) 2011, Intel Corporation. All rights reserved.
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3 |
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4 | Redistribution and use in source and binary forms, with or without modification,
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5 | are permitted provided that the following conditions are met:
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6 |
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7 | * Redistributions of source code must retain the above copyright notice, this
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8 | list of conditions and the following disclaimer.
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9 | * Redistributions in binary form must reproduce the above copyright notice,
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10 | this list of conditions and the following disclaimer in the documentation
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11 | and/or other materials provided with the distribution.
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12 | * Neither the name of Intel Corporation nor the names of its contributors may
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13 | be used to endorse or promote products derived from this software without
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14 | specific prior written permission.
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15 |
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16 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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17 | ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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18 | WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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19 | DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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20 | ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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21 | (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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22 | LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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23 | ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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24 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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25 | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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26 |
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27 | ********************************************************************************
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28 | * Content : Eigen bindings to Intel(R) MKL
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29 | * Selfadjoint matrix-vector product functionality based on ?SYMV/HEMV.
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30 | ********************************************************************************
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31 | */
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32 |
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33 | #ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
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34 | #define EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
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35 |
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36 | namespace Eigen {
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37 |
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38 | namespace internal {
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39 |
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40 | /**********************************************************************
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41 | * This file implements selfadjoint matrix-vector multiplication using BLAS
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42 | **********************************************************************/
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43 |
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44 | // symv/hemv specialization
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45 |
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46 | template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
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47 | struct selfadjoint_matrix_vector_product_symv :
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48 | selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn> {};
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49 |
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50 | #define EIGEN_MKL_SYMV_SPECIALIZE(Scalar) \
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51 | template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
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52 | struct selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Specialized> { \
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53 | static void run( \
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54 | Index size, const Scalar* lhs, Index lhsStride, \
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55 | const Scalar* _rhs, Index rhsIncr, Scalar* res, Scalar alpha) { \
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56 | enum {\
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57 | IsColMajor = StorageOrder==ColMajor \
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58 | }; \
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59 | if (IsColMajor == ConjugateLhs) {\
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60 | selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn>::run( \
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61 | size, lhs, lhsStride, _rhs, rhsIncr, res, alpha); \
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62 | } else {\
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63 | selfadjoint_matrix_vector_product_symv<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs>::run( \
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64 | size, lhs, lhsStride, _rhs, rhsIncr, res, alpha); \
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65 | }\
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66 | } \
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67 | }; \
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68 |
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69 | EIGEN_MKL_SYMV_SPECIALIZE(double)
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70 | EIGEN_MKL_SYMV_SPECIALIZE(float)
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71 | EIGEN_MKL_SYMV_SPECIALIZE(dcomplex)
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72 | EIGEN_MKL_SYMV_SPECIALIZE(scomplex)
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73 |
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74 | #define EIGEN_MKL_SYMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLFUNC) \
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75 | template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
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76 | struct selfadjoint_matrix_vector_product_symv<EIGTYPE,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs> \
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77 | { \
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78 | typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> SYMVVector;\
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79 | \
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80 | static void run( \
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81 | Index size, const EIGTYPE* lhs, Index lhsStride, \
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82 | const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* res, EIGTYPE alpha) \
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83 | { \
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84 | enum {\
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85 | IsRowMajor = StorageOrder==RowMajor ? 1 : 0, \
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86 | IsLower = UpLo == Lower ? 1 : 0 \
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87 | }; \
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88 | MKL_INT n=size, lda=lhsStride, incx=rhsIncr, incy=1; \
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89 | MKLTYPE alpha_, beta_; \
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90 | const EIGTYPE *x_ptr, myone(1); \
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91 | char uplo=(IsRowMajor) ? (IsLower ? 'U' : 'L') : (IsLower ? 'L' : 'U'); \
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92 | assign_scalar_eig2mkl(alpha_, alpha); \
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93 | assign_scalar_eig2mkl(beta_, myone); \
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94 | SYMVVector x_tmp; \
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95 | if (ConjugateRhs) { \
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96 | Map<const SYMVVector, 0, InnerStride<> > map_x(_rhs,size,1,InnerStride<>(incx)); \
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97 | x_tmp=map_x.conjugate(); \
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98 | x_ptr=x_tmp.data(); \
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99 | incx=1; \
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100 | } else x_ptr=_rhs; \
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101 | MKLFUNC(&uplo, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \
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102 | }\
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103 | };
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104 |
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105 | EIGEN_MKL_SYMV_SPECIALIZATION(double, double, dsymv)
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106 | EIGEN_MKL_SYMV_SPECIALIZATION(float, float, ssymv)
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107 | EIGEN_MKL_SYMV_SPECIALIZATION(dcomplex, MKL_Complex16, zhemv)
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108 | EIGEN_MKL_SYMV_SPECIALIZATION(scomplex, MKL_Complex8, chemv)
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109 |
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110 | } // end namespace internal
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111 |
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112 | } // end namespace Eigen
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113 |
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114 | #endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
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