mirror of
https://gitlab.com/libeigen/eigen.git
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3036eeca0a
release of tvmet (inactive for 2 years and developer unreachable) as the basis for eigen2, because it provides seemingly good expression template mechanisms, we want that, and it would take years to reinvent that wheel. We'll see. So this commit imports the last tvmet release.
116 lines
3.1 KiB
C++
116 lines
3.1 KiB
C++
/*
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* Tiny Vector Matrix Library
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* Dense Vector Matrix Libary of Tiny size using Expression Templates
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*
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* Copyright (C) 2001 - 2003 Olaf Petzold <opetzold@users.sourceforge.net>
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*
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* This library is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*
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* This library is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with this library; if not, write to the Free Software
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* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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*
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* $Id: Gemtm.h,v 1.5 2004/06/16 09:30:07 opetzold Exp $
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*/
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#ifndef TVMET_LOOP_GEMTM_H
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#define TVMET_LOOP_GEMTM_H
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namespace tvmet {
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namespace loop {
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/**
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* \class gemtm Gemtm.h "tvmet/loop/Gemtm.h"
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* \brief class for matrix-matrix product using loop unrolling.
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* using formula
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* \f[
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* M_1^{T}\,M_2
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* \f]
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* \par Example:
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* \code
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* template<class T, std::size_t Rows1, std::size_t Cols1, std::size_t Cols2>
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* inline
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* void
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* prod(const Matrix<T, Rows1, Cols1>& lhs, const Matrix<T, Rows1, Cols2>& rhs,
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* Matrix<T, Cols2, Cols1>& dest)
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* {
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* for (std::size_t i = 0; i != Cols1; ++i) {
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* for (std::size_t j = 0; j != Cols2; ++j) {
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* dest(i, j) = tvmet::loop::gemtm<Rows1, Cols1, Cols2>::prod(lhs, rhs, i, j);
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* }
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* }
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* }
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* \endcode
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* \note The number of rows of rhs matrix have to be equal rows of rhs matrix,
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* since lhs matrix 1 is transposed.
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* The result is a (Cols1 x Cols2) matrix.
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*/
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template<std::size_t Rows1, std::size_t Cols1,
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std::size_t Cols2>
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class gemtm
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{
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gemtm(const gemtm&);
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gemtm& operator=(const gemtm&);
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private:
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enum {
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count = Cols1,
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N = (count+7)/8
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};
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public:
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gemtm() { }
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public:
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template<class E1, class E2>
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static inline
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typename PromoteTraits<
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typename E1::value_type,
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typename E2::value_type
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>::value_type
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prod(const E1& lhs, const E2& rhs, std::size_t i, std::size_t j) {
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typename PromoteTraits<
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typename E1::value_type,
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typename E2::value_type
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>::value_type sum(0);
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std::size_t k(0);
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std::size_t n(N);
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// Duff's device
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switch(count % 8) {
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case 0: do { sum += lhs(k, i) * rhs(k, j); ++k;
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case 7: sum += lhs(k, i) * rhs(k, j); ++k;
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case 6: sum += lhs(k, i) * rhs(k, j); ++k;
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case 5: sum += lhs(k, i) * rhs(k, j); ++k;
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case 4: sum += lhs(k, i) * rhs(k, j); ++k;
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case 3: sum += lhs(k, i) * rhs(k, j); ++k;
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case 2: sum += lhs(k, i) * rhs(k, j); ++k;
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case 1: sum += lhs(k, i) * rhs(k, j); ++k;
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} while(--n != 0);
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}
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return sum;
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}
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};
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} // namespace loop
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} // namespace tvmet
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#endif /* TVMET_LOOP_GEMTM_H */
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// Local Variables:
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// mode:C++
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// End:
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