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 | * Singular Value Decomposition - SVD.
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30 | ********************************************************************************
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31 | */
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32 |
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33 | #ifndef EIGEN_JACOBISVD_MKL_H
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34 | #define EIGEN_JACOBISVD_MKL_H
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35 |
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36 | #include "Eigen/src/Core/util/MKL_support.h"
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37 |
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38 | namespace Eigen {
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39 |
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40 | /** \internal Specialization for the data types supported by MKL */
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41 |
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42 | #define EIGEN_MKL_SVD(EIGTYPE, MKLTYPE, MKLRTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
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43 | template<> inline \
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44 | JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>& \
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45 | JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) \
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46 | { \
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47 | typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
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48 | /*typedef MatrixType::Scalar Scalar;*/ \
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49 | /*typedef MatrixType::RealScalar RealScalar;*/ \
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50 | allocate(matrix.rows(), matrix.cols(), computationOptions); \
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51 | \
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52 | /*const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();*/ \
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53 | m_nonzeroSingularValues = m_diagSize; \
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54 | \
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55 | lapack_int lda = matrix.outerStride(), ldu, ldvt; \
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56 | lapack_int matrix_order = MKLCOLROW; \
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57 | char jobu, jobvt; \
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58 | MKLTYPE *u, *vt, dummy; \
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59 | jobu = (m_computeFullU) ? 'A' : (m_computeThinU) ? 'S' : 'N'; \
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60 | jobvt = (m_computeFullV) ? 'A' : (m_computeThinV) ? 'S' : 'N'; \
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61 | if (computeU()) { \
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62 | ldu = m_matrixU.outerStride(); \
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63 | u = (MKLTYPE*)m_matrixU.data(); \
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64 | } else { ldu=1; u=&dummy; }\
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65 | MatrixType localV; \
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66 | ldvt = (m_computeFullV) ? m_cols : (m_computeThinV) ? m_diagSize : 1; \
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67 | if (computeV()) { \
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68 | localV.resize(ldvt, m_cols); \
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69 | vt = (MKLTYPE*)localV.data(); \
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70 | } else { ldvt=1; vt=&dummy; }\
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71 | Matrix<MKLRTYPE, Dynamic, Dynamic> superb; superb.resize(m_diagSize, 1); \
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72 | MatrixType m_temp; m_temp = matrix; \
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73 | LAPACKE_##MKLPREFIX##gesvd( matrix_order, jobu, jobvt, m_rows, m_cols, (MKLTYPE*)m_temp.data(), lda, (MKLRTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \
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74 | if (computeV()) m_matrixV = localV.adjoint(); \
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75 | /* for(int i=0;i<m_diagSize;i++) if (m_singularValues.coeffRef(i) < precision) { m_nonzeroSingularValues--; m_singularValues.coeffRef(i)=RealScalar(0);}*/ \
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76 | m_isInitialized = true; \
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77 | return *this; \
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78 | }
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79 |
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80 | EIGEN_MKL_SVD(double, double, double, d, ColMajor, LAPACK_COL_MAJOR)
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81 | EIGEN_MKL_SVD(float, float, float , s, ColMajor, LAPACK_COL_MAJOR)
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82 | EIGEN_MKL_SVD(dcomplex, MKL_Complex16, double, z, ColMajor, LAPACK_COL_MAJOR)
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83 | EIGEN_MKL_SVD(scomplex, MKL_Complex8, float , c, ColMajor, LAPACK_COL_MAJOR)
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84 |
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85 | EIGEN_MKL_SVD(double, double, double, d, RowMajor, LAPACK_ROW_MAJOR)
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86 | EIGEN_MKL_SVD(float, float, float , s, RowMajor, LAPACK_ROW_MAJOR)
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87 | EIGEN_MKL_SVD(dcomplex, MKL_Complex16, double, z, RowMajor, LAPACK_ROW_MAJOR)
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88 | EIGEN_MKL_SVD(scomplex, MKL_Complex8, float , c, RowMajor, LAPACK_ROW_MAJOR)
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89 |
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90 | } // end namespace Eigen
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91 |
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92 | #endif // EIGEN_JACOBISVD_MKL_H
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