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Intel(R) MKL support added.
* * * License disclaimer changed to BSD license for MKL_support.h * * * Pardiso support fixed, test added. blas/lapack tests fixed: Scalar parameter was added in Cholesky, product_matrix_vector_triangular remaned to triangular_matrix_vector_product. * * * PARDISO test was added physically.
This commit is contained in:
karturov
90
Eigen/src/Eigenvalues/ComplexSchur_MKL.h
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90
Eigen/src/Eigenvalues/ComplexSchur_MKL.h
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/*
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Copyright (c) 2011, Intel Corporation. All rights reserved.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of Intel Corporation nor the names of its contributors may
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be used to endorse or promote products derived from this software without
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specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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********************************************************************************
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* Content : Eigen bindings to Intel(R) MKL
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* Complex Schur needed to complex unsymmetrical eigenvalues/eigenvectors.
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********************************************************************************
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*/
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#ifndef EIGEN_COMPLEX_SCHUR_MKL_H
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#define EIGEN_COMPLEX_SCHUR_MKL_H
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#include "Eigen/src/Core/util/MKL_support.h"
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/** \internal Specialization for the data types supported by MKL */
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#define EIGEN_MKL_SCHUR_COMPLEX(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
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template<> \
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ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
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ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
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{ \
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typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> MatrixType; \
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typedef MatrixType::Scalar Scalar; \
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typedef MatrixType::RealScalar RealScalar; \
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typedef std::complex<RealScalar> ComplexScalar; \
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\
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assert(matrix.cols() == matrix.rows()); \
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\
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m_matUisUptodate = false; \
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if(matrix.cols() == 1) \
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{ \
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m_matT = matrix.cast<ComplexScalar>(); \
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if(computeU) m_matU = ComplexMatrixType::Identity(1,1); \
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m_info = Success; \
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m_isInitialized = true; \
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m_matUisUptodate = computeU; \
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return *this; \
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} \
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lapack_int n = matrix.cols(), sdim, info; \
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lapack_int lda = matrix.outerStride(); \
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lapack_int matrix_order = MKLCOLROW; \
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char jobvs, sort='N'; \
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LAPACK_##MKLPREFIX_U##_SELECT1 select; \
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jobvs = (computeU) ? 'V' : 'N'; \
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m_matU.resize(n, n); \
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lapack_int ldvs = m_matU.outerStride(); \
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m_matT = matrix; \
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Matrix<EIGTYPE, Dynamic, Dynamic> w; \
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w.resize(n, 1);\
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info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)w.data(), (MKLTYPE*)m_matU.data(), ldvs ); \
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if(info == 0) \
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m_info = Success; \
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else \
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m_info = NoConvergence; \
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\
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m_isInitialized = true; \
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m_matUisUptodate = computeU; \
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return *this; \
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\
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}
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EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8, c, C, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, RowMajor, LAPACK_ROW_MAJOR)
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EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8, c, C, RowMajor, LAPACK_ROW_MAJOR)
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#endif // EIGEN_COMPLEX_SCHUR_MKL_H
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79
Eigen/src/Eigenvalues/RealSchur_MKL.h
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79
Eigen/src/Eigenvalues/RealSchur_MKL.h
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/*
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Copyright (c) 2011, Intel Corporation. All rights reserved.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of Intel Corporation nor the names of its contributors may
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be used to endorse or promote products derived from this software without
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specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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********************************************************************************
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* Content : Eigen bindings to Intel(R) MKL
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* Real Schur needed to real unsymmetrical eigenvalues/eigenvectors.
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********************************************************************************
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*/
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#ifndef EIGEN_REAL_SCHUR_MKL_H
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#define EIGEN_REAL_SCHUR_MKL_H
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#include "Eigen/src/Core/util/MKL_support.h"
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/** \internal Specialization for the data types supported by MKL */
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#define EIGEN_MKL_SCHUR_REAL(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
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template<> \
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RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
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RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
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{ \
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typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> MatrixType; \
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typedef MatrixType::Scalar Scalar; \
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typedef MatrixType::RealScalar RealScalar; \
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\
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assert(matrix.cols() == matrix.rows()); \
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\
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lapack_int n = matrix.cols(), sdim, info; \
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lapack_int lda = matrix.outerStride(); \
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lapack_int matrix_order = MKLCOLROW; \
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char jobvs, sort='N'; \
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LAPACK_##MKLPREFIX_U##_SELECT2 select; \
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jobvs = (computeU) ? 'V' : 'N'; \
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m_matU.resize(n, n); \
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lapack_int ldvs = m_matU.outerStride(); \
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m_matT = matrix; \
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Matrix<EIGTYPE, Dynamic, Dynamic> wr, wi; \
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wr.resize(n, 1); wi.resize(n, 1); \
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info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)wr.data(), (MKLTYPE*)wi.data(), (MKLTYPE*)m_matU.data(), ldvs ); \
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if(info == 0) \
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m_info = Success; \
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else \
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m_info = NoConvergence; \
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\
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m_isInitialized = true; \
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m_matUisUptodate = computeU; \
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return *this; \
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\
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}
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EIGEN_MKL_SCHUR_REAL(double, double, d, D, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_SCHUR_REAL(float, float, s, S, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_SCHUR_REAL(double, double, d, D, RowMajor, LAPACK_ROW_MAJOR)
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EIGEN_MKL_SCHUR_REAL(float, float, s, S, RowMajor, LAPACK_ROW_MAJOR)
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#endif // EIGEN_REAL_SCHUR_MKL_H
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89
Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
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89
Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
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@@ -0,0 +1,89 @@
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/*
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Copyright (c) 2011, Intel Corporation. All rights reserved.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of Intel Corporation nor the names of its contributors may
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be used to endorse or promote products derived from this software without
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specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
|
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ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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||||
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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********************************************************************************
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* Content : Eigen bindings to Intel(R) MKL
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* Self-adjoint eigenvalues/eigenvectors.
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********************************************************************************
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*/
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#ifndef EIGEN_SAEIGENSOLVER_MKL_H
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#define EIGEN_SAEIGENSOLVER_MKL_H
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#include "Eigen/src/Core/util/MKL_support.h"
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/** \internal Specialization for the data types supported by MKL */
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#define EIGEN_MKL_EIG_SELFADJ(EIGTYPE, MKLTYPE, MKLRTYPE, MKLNAME, EIGCOLROW, MKLCOLROW ) \
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template<> \
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SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
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SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, int options) \
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{ \
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eigen_assert(matrix.cols() == matrix.rows()); \
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eigen_assert((options&~(EigVecMask|GenEigMask))==0 \
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&& (options&EigVecMask)!=EigVecMask \
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&& "invalid option parameter"); \
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bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \
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lapack_int n = matrix.cols(), lda, matrix_order, info; \
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m_eivalues.resize(n,1); \
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m_subdiag.resize(n-1); \
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m_eivec = matrix; \
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\
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if(n==1) \
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{ \
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m_eivalues.coeffRef(0,0) = internal::real(matrix.coeff(0,0)); \
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if(computeEigenvectors) m_eivec.setOnes(n,n); \
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m_info = Success; \
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m_isInitialized = true; \
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m_eigenvectorsOk = computeEigenvectors; \
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return *this; \
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} \
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\
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lda = matrix.outerStride(); \
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matrix_order=MKLCOLROW; \
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char jobz, uplo='L', range='A'; \
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jobz = computeEigenvectors ? 'V' : 'N'; \
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\
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info = LAPACKE_##MKLNAME( matrix_order, jobz, uplo, n, (MKLTYPE*)m_eivec.data(), lda, (MKLRTYPE*)m_eivalues.data() ); \
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m_info = (info==0) ? Success : NoConvergence; \
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m_isInitialized = true; \
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m_eigenvectorsOk = computeEigenvectors; \
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return *this; \
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}
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EIGEN_MKL_EIG_SELFADJ(double, double, double, dsyev, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_EIG_SELFADJ(float, float, float, ssyev, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8, float, cheev, ColMajor, LAPACK_COL_MAJOR)
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EIGEN_MKL_EIG_SELFADJ(double, double, double, dsyev, RowMajor, LAPACK_ROW_MAJOR)
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EIGEN_MKL_EIG_SELFADJ(float, float, float, ssyev, RowMajor, LAPACK_ROW_MAJOR)
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EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, RowMajor, LAPACK_ROW_MAJOR)
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EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8, float, cheev, RowMajor, LAPACK_ROW_MAJOR)
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#endif // EIGEN_SAEIGENSOLVER_H
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