| /* |
| Copyright (c) 2011, Intel Corporation. All rights reserved. |
| |
| Redistribution and use in source and binary forms, with or without modification, |
| are permitted provided that the following conditions are met: |
| |
| * Redistributions of source code must retain the above copyright notice, this |
| list of conditions and the following disclaimer. |
| * Redistributions in binary form must reproduce the above copyright notice, |
| this list of conditions and the following disclaimer in the documentation |
| and/or other materials provided with the distribution. |
| * Neither the name of Intel Corporation nor the names of its contributors may |
| be used to endorse or promote products derived from this software without |
| specific prior written permission. |
| |
| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND |
| ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED |
| WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE |
| DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR |
| ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES |
| (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; |
| LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON |
| ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
| (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS |
| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| |
| ******************************************************************************** |
| * 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 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 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 |