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Diffstat (limited to 'Eigen/src/Core/products/GeneralUnrolled.h')
| -rw-r--r-- | Eigen/src/Core/products/GeneralUnrolled.h | 385 |
1 files changed, 385 insertions, 0 deletions
diff --git a/Eigen/src/Core/products/GeneralUnrolled.h b/Eigen/src/Core/products/GeneralUnrolled.h new file mode 100644 index 000000000..7241976a8 --- /dev/null +++ b/Eigen/src/Core/products/GeneralUnrolled.h @@ -0,0 +1,385 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> +// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr> +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see <http://www.gnu.org/licenses/>. + +#ifndef EIGEN_GENERAL_UNROLLED_PRODUCT_H +#define EIGEN_GENERAL_UNROLLED_PRODUCT_H + +/********************************************************************************* +* Specialization of GeneralProduct<> for products with small fixed sizes +*********************************************************************************/ + +/* Since the all the dimensions of the product are small, here we can rely + * on the generic Assign mechanism to evaluate the product per coeff (or packet). + * + * Note that here the inner-loops should always be unrolled. + */ + +template<int VectorizationMode, int Index, typename Lhs, typename Rhs, typename RetScalar> +struct ei_product_coeff_impl; + +template<int StorageOrder, int Index, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode> +struct ei_product_packet_impl; + +template<typename LhsNested, typename RhsNested> +struct ei_traits<GeneralProduct<LhsNested,RhsNested,UnrolledProduct> > +{ + typedef typename ei_cleantype<LhsNested>::type _LhsNested; + typedef typename ei_cleantype<RhsNested>::type _RhsNested; + typedef typename ei_scalar_product_traits<typename _LhsNested::Scalar, typename _RhsNested::Scalar>::ReturnType Scalar; + + enum { + LhsCoeffReadCost = _LhsNested::CoeffReadCost, + RhsCoeffReadCost = _RhsNested::CoeffReadCost, + LhsFlags = _LhsNested::Flags, + RhsFlags = _RhsNested::Flags, + + RowsAtCompileTime = _LhsNested::RowsAtCompileTime, + ColsAtCompileTime = _RhsNested::ColsAtCompileTime, + InnerSize = EIGEN_ENUM_MIN(_LhsNested::ColsAtCompileTime, _RhsNested::RowsAtCompileTime), + + MaxRowsAtCompileTime = _LhsNested::MaxRowsAtCompileTime, + MaxColsAtCompileTime = _RhsNested::MaxColsAtCompileTime, + + LhsRowMajor = LhsFlags & RowMajorBit, + RhsRowMajor = RhsFlags & RowMajorBit, + + CanVectorizeRhs = RhsRowMajor && (RhsFlags & PacketAccessBit) + && (ColsAtCompileTime == Dynamic || (ColsAtCompileTime % ei_packet_traits<Scalar>::size) == 0), + + CanVectorizeLhs = (!LhsRowMajor) && (LhsFlags & PacketAccessBit) + && (RowsAtCompileTime == Dynamic || (RowsAtCompileTime % ei_packet_traits<Scalar>::size) == 0), + + EvalToRowMajor = RhsRowMajor && (!CanVectorizeLhs), + + RemovedBits = ~(EvalToRowMajor ? 0 : RowMajorBit), + + Flags = ((unsigned int)(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits) + | EvalBeforeAssigningBit + | EvalBeforeNestingBit + | (CanVectorizeLhs || CanVectorizeRhs ? PacketAccessBit : 0) + | (LhsFlags & RhsFlags & AlignedBit), + + CoeffReadCost = InnerSize == Dynamic ? Dynamic + : InnerSize * (NumTraits<Scalar>::MulCost + LhsCoeffReadCost + RhsCoeffReadCost) + + (InnerSize - 1) * NumTraits<Scalar>::AddCost, + + /* CanVectorizeInner deserves special explanation. It does not affect the product flags. It is not used outside + * of Product. If the Product itself is not a packet-access expression, there is still a chance that the inner + * loop of the product might be vectorized. This is the meaning of CanVectorizeInner. Since it doesn't affect + * the Flags, it is safe to make this value depend on ActualPacketAccessBit, that doesn't affect the ABI. + */ + CanVectorizeInner = LhsRowMajor && (!RhsRowMajor) && (LhsFlags & RhsFlags & ActualPacketAccessBit) + && (InnerSize % ei_packet_traits<Scalar>::size == 0) + }; +}; + +template<typename LhsNested, typename RhsNested> class GeneralProduct<LhsNested,RhsNested,UnrolledProduct> + : ei_no_assignment_operator, + public MatrixBase<GeneralProduct<LhsNested, RhsNested, UnrolledProduct> > +{ + public: + + EIGEN_GENERIC_PUBLIC_INTERFACE(GeneralProduct) + + private: + + typedef typename ei_traits<GeneralProduct>::_LhsNested _LhsNested; + typedef typename ei_traits<GeneralProduct>::_RhsNested _RhsNested; + + enum { + PacketSize = ei_packet_traits<Scalar>::size, + InnerSize = ei_traits<GeneralProduct>::InnerSize, + Unroll = CoeffReadCost <= EIGEN_UNROLLING_LIMIT, + CanVectorizeInner = ei_traits<GeneralProduct>::CanVectorizeInner + }; + + typedef ei_product_coeff_impl<CanVectorizeInner ? InnerVectorization : NoVectorization, + Unroll ? InnerSize-1 : Dynamic, + _LhsNested, _RhsNested, Scalar> ScalarCoeffImpl; + + public: + + template<typename Lhs, typename Rhs> + inline GeneralProduct(const Lhs& lhs, const Rhs& rhs) + : m_lhs(lhs), m_rhs(rhs) + { + // we don't allow taking products of matrices of different real types, as that wouldn't be vectorizable. + // We still allow to mix T and complex<T>. + EIGEN_STATIC_ASSERT((ei_is_same_type<typename Lhs::RealScalar, typename Rhs::RealScalar>::ret), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + ei_assert(lhs.cols() == rhs.rows() + && "invalid matrix product" + && "if you wanted a coeff-wise or a dot product use the respective explicit functions"); + } + + EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); } + EIGEN_STRONG_INLINE int cols() const { return m_rhs.cols(); } + + EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const + { + Scalar res; + ScalarCoeffImpl::run(row, col, m_lhs, m_rhs, res); + return res; + } + + /* Allow index-based non-packet access. It is impossible though to allow index-based packed access, + * which is why we don't set the LinearAccessBit. + */ + EIGEN_STRONG_INLINE const Scalar coeff(int index) const + { + Scalar res; + const int row = RowsAtCompileTime == 1 ? 0 : index; + const int col = RowsAtCompileTime == 1 ? index : 0; + ScalarCoeffImpl::run(row, col, m_lhs, m_rhs, res); + return res; + } + + template<int LoadMode> + EIGEN_STRONG_INLINE const PacketScalar packet(int row, int col) const + { + PacketScalar res; + ei_product_packet_impl<Flags&RowMajorBit ? RowMajor : ColMajor, + Unroll ? InnerSize-1 : Dynamic, + _LhsNested, _RhsNested, PacketScalar, LoadMode> + ::run(row, col, m_lhs, m_rhs, res); + return res; + } + + protected: + const LhsNested m_lhs; + const RhsNested m_rhs; +}; + + +/*************************************************************************** +* Normal product .coeff() implementation (with meta-unrolling) +***************************************************************************/ + +/************************************** +*** Scalar path - no vectorization *** +**************************************/ + +template<int Index, typename Lhs, typename Rhs, typename RetScalar> +struct ei_product_coeff_impl<NoVectorization, Index, Lhs, Rhs, RetScalar> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) + { + ei_product_coeff_impl<NoVectorization, Index-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, res); + res += lhs.coeff(row, Index) * rhs.coeff(Index, col); + } +}; + +template<typename Lhs, typename Rhs, typename RetScalar> +struct ei_product_coeff_impl<NoVectorization, 0, Lhs, Rhs, RetScalar> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) + { + res = lhs.coeff(row, 0) * rhs.coeff(0, col); + } +}; + +template<typename Lhs, typename Rhs, typename RetScalar> +struct ei_product_coeff_impl<NoVectorization, Dynamic, Lhs, Rhs, RetScalar> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar& res) + { + ei_assert(lhs.cols()>0 && "you are using a non initialized matrix"); + res = lhs.coeff(row, 0) * rhs.coeff(0, col); + for(int i = 1; i < lhs.cols(); ++i) + res += lhs.coeff(row, i) * rhs.coeff(i, col); + } +}; + +// prevent buggy user code from causing an infinite recursion +template<typename Lhs, typename Rhs, typename RetScalar> +struct ei_product_coeff_impl<NoVectorization, -1, Lhs, Rhs, RetScalar> +{ + EIGEN_STRONG_INLINE static void run(int, int, const Lhs&, const Rhs&, RetScalar&) {} +}; + +/******************************************* +*** Scalar path with inner vectorization *** +*******************************************/ + +template<int Index, typename Lhs, typename Rhs, typename PacketScalar> +struct ei_product_coeff_vectorized_unroller +{ + enum { PacketSize = ei_packet_traits<typename Lhs::Scalar>::size }; + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres) + { + ei_product_coeff_vectorized_unroller<Index-PacketSize, Lhs, Rhs, PacketScalar>::run(row, col, lhs, rhs, pres); + pres = ei_padd(pres, ei_pmul( lhs.template packet<Aligned>(row, Index) , rhs.template packet<Aligned>(Index, col) )); + } +}; + +template<typename Lhs, typename Rhs, typename PacketScalar> +struct ei_product_coeff_vectorized_unroller<0, Lhs, Rhs, PacketScalar> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres) + { + pres = ei_pmul(lhs.template packet<Aligned>(row, 0) , rhs.template packet<Aligned>(0, col)); + } +}; + +template<int Index, typename Lhs, typename Rhs, typename RetScalar> +struct ei_product_coeff_impl<InnerVectorization, Index, Lhs, Rhs, RetScalar> +{ + typedef typename Lhs::PacketScalar PacketScalar; + enum { PacketSize = ei_packet_traits<typename Lhs::Scalar>::size }; + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) + { + PacketScalar pres; + ei_product_coeff_vectorized_unroller<Index+1-PacketSize, Lhs, Rhs, PacketScalar>::run(row, col, lhs, rhs, pres); + ei_product_coeff_impl<NoVectorization,Index,Lhs,Rhs,RetScalar>::run(row, col, lhs, rhs, res); + res = ei_predux(pres); + } +}; + +template<typename Lhs, typename Rhs, int LhsRows = Lhs::RowsAtCompileTime, int RhsCols = Rhs::ColsAtCompileTime> +struct ei_product_coeff_vectorized_dyn_selector +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + { + res = ei_dot_impl< + Block<Lhs, 1, ei_traits<Lhs>::ColsAtCompileTime>, + Block<Rhs, ei_traits<Rhs>::RowsAtCompileTime, 1>, + LinearVectorization, NoUnrolling>::run(lhs.row(row), rhs.col(col)); + } +}; + +// NOTE the 3 following specializations are because taking .col(0) on a vector is a bit slower +// NOTE maybe they are now useless since we have a specialization for Block<Matrix> +template<typename Lhs, typename Rhs, int RhsCols> +struct ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,RhsCols> +{ + EIGEN_STRONG_INLINE static void run(int /*row*/, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + { + res = ei_dot_impl< + Lhs, + Block<Rhs, ei_traits<Rhs>::RowsAtCompileTime, 1>, + LinearVectorization, NoUnrolling>::run(lhs, rhs.col(col)); + } +}; + +template<typename Lhs, typename Rhs, int LhsRows> +struct ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs,LhsRows,1> +{ + EIGEN_STRONG_INLINE static void run(int row, int /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + { + res = ei_dot_impl< + Block<Lhs, 1, ei_traits<Lhs>::ColsAtCompileTime>, + Rhs, + LinearVectorization, NoUnrolling>::run(lhs.row(row), rhs); + } +}; + +template<typename Lhs, typename Rhs> +struct ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,1> +{ + EIGEN_STRONG_INLINE static void run(int /*row*/, int /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + { + res = ei_dot_impl< + Lhs, + Rhs, + LinearVectorization, NoUnrolling>::run(lhs, rhs); + } +}; + +template<typename Lhs, typename Rhs, typename RetScalar> +struct ei_product_coeff_impl<InnerVectorization, Dynamic, Lhs, Rhs, RetScalar> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + { + ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs>::run(row, col, lhs, rhs, res); + } +}; + +/******************* +*** Packet path *** +*******************/ + +template<int Index, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode> +struct ei_product_packet_impl<RowMajor, Index, Lhs, Rhs, PacketScalar, LoadMode> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res) + { + ei_product_packet_impl<RowMajor, Index-1, Lhs, Rhs, PacketScalar, LoadMode>::run(row, col, lhs, rhs, res); + res = ei_pmadd(ei_pset1(lhs.coeff(row, Index)), rhs.template packet<LoadMode>(Index, col), res); + } +}; + +template<int Index, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode> +struct ei_product_packet_impl<ColMajor, Index, Lhs, Rhs, PacketScalar, LoadMode> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res) + { + ei_product_packet_impl<ColMajor, Index-1, Lhs, Rhs, PacketScalar, LoadMode>::run(row, col, lhs, rhs, res); + res = ei_pmadd(lhs.template packet<LoadMode>(row, Index), ei_pset1(rhs.coeff(Index, col)), res); + } +}; + +template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode> +struct ei_product_packet_impl<RowMajor, 0, Lhs, Rhs, PacketScalar, LoadMode> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res) + { + res = ei_pmul(ei_pset1(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col)); + } +}; + +template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode> +struct ei_product_packet_impl<ColMajor, 0, Lhs, Rhs, PacketScalar, LoadMode> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res) + { + res = ei_pmul(lhs.template packet<LoadMode>(row, 0), ei_pset1(rhs.coeff(0, col))); + } +}; + +template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode> +struct ei_product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, PacketScalar, LoadMode> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar& res) + { + ei_assert(lhs.cols()>0 && "you are using a non initialized matrix"); + res = ei_pmul(ei_pset1(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col)); + for(int i = 1; i < lhs.cols(); ++i) + res = ei_pmadd(ei_pset1(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res); + } +}; + +template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode> +struct ei_product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, PacketScalar, LoadMode> +{ + EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar& res) + { + ei_assert(lhs.cols()>0 && "you are using a non initialized matrix"); + res = ei_pmul(lhs.template packet<LoadMode>(row, 0), ei_pset1(rhs.coeff(0, col))); + for(int i = 1; i < lhs.cols(); ++i) + res = ei_pmadd(lhs.template packet<LoadMode>(row, i), ei_pset1(rhs.coeff(i, col)), res); + } +}; + +#endif // EIGEN_GENERAL_UNROLLED_PRODUCT_H |