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Diffstat (limited to 'src/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h')
-rw-r--r-- | src/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h | 517 |
1 files changed, 517 insertions, 0 deletions
diff --git a/src/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h b/src/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h new file mode 100644 index 000000000..caa65fccc --- /dev/null +++ b/src/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h @@ -0,0 +1,517 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr> +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_GENERAL_MATRIX_MATRIX_H +#define EIGEN_GENERAL_MATRIX_MATRIX_H + +namespace Eigen { + +namespace internal { + +template<typename _LhsScalar, typename _RhsScalar> class level3_blocking; + +/* Specialization for a row-major destination matrix => simple transposition of the product */ +template< + typename Index, + typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, + typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, + int ResInnerStride> +struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor,ResInnerStride> +{ + typedef gebp_traits<RhsScalar,LhsScalar> Traits; + + typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar; + static EIGEN_STRONG_INLINE void run( + Index rows, Index cols, Index depth, + const LhsScalar* lhs, Index lhsStride, + const RhsScalar* rhs, Index rhsStride, + ResScalar* res, Index resIncr, Index resStride, + ResScalar alpha, + level3_blocking<RhsScalar,LhsScalar>& blocking, + GemmParallelInfo<Index>* info = 0) + { + // transpose the product such that the result is column major + general_matrix_matrix_product<Index, + RhsScalar, RhsStorageOrder==RowMajor ? ColMajor : RowMajor, ConjugateRhs, + LhsScalar, LhsStorageOrder==RowMajor ? ColMajor : RowMajor, ConjugateLhs, + ColMajor,ResInnerStride> + ::run(cols,rows,depth,rhs,rhsStride,lhs,lhsStride,res,resIncr,resStride,alpha,blocking,info); + } +}; + +/* Specialization for a col-major destination matrix + * => Blocking algorithm following Goto's paper */ +template< + typename Index, + typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, + typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, + int ResInnerStride> +struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor,ResInnerStride> +{ + +typedef gebp_traits<LhsScalar,RhsScalar> Traits; + +typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar; +static void run(Index rows, Index cols, Index depth, + const LhsScalar* _lhs, Index lhsStride, + const RhsScalar* _rhs, Index rhsStride, + ResScalar* _res, Index resIncr, Index resStride, + ResScalar alpha, + level3_blocking<LhsScalar,RhsScalar>& blocking, + GemmParallelInfo<Index>* info = 0) +{ + typedef const_blas_data_mapper<LhsScalar, Index, LhsStorageOrder> LhsMapper; + typedef const_blas_data_mapper<RhsScalar, Index, RhsStorageOrder> RhsMapper; + typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor,Unaligned,ResInnerStride> ResMapper; + LhsMapper lhs(_lhs, lhsStride); + RhsMapper rhs(_rhs, rhsStride); + ResMapper res(_res, resStride, resIncr); + + Index kc = blocking.kc(); // cache block size along the K direction + Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction + Index nc = (std::min)(cols,blocking.nc()); // cache block size along the N direction + + gemm_pack_lhs<LhsScalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, typename Traits::LhsPacket4Packing, LhsStorageOrder> pack_lhs; + gemm_pack_rhs<RhsScalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs; + gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp; + +#ifdef EIGEN_HAS_OPENMP + if(info) + { + // this is the parallel version! + int tid = omp_get_thread_num(); + int threads = omp_get_num_threads(); + + LhsScalar* blockA = blocking.blockA(); + eigen_internal_assert(blockA!=0); + + std::size_t sizeB = kc*nc; + ei_declare_aligned_stack_constructed_variable(RhsScalar, blockB, sizeB, 0); + + // For each horizontal panel of the rhs, and corresponding vertical panel of the lhs... + for(Index k=0; k<depth; k+=kc) + { + const Index actual_kc = (std::min)(k+kc,depth)-k; // => rows of B', and cols of the A' + + // In order to reduce the chance that a thread has to wait for the other, + // let's start by packing B'. + pack_rhs(blockB, rhs.getSubMapper(k,0), actual_kc, nc); + + // Pack A_k to A' in a parallel fashion: + // each thread packs the sub block A_k,i to A'_i where i is the thread id. + + // However, before copying to A'_i, we have to make sure that no other thread is still using it, + // i.e., we test that info[tid].users equals 0. + // Then, we set info[tid].users to the number of threads to mark that all other threads are going to use it. + while(info[tid].users!=0) {} + info[tid].users = threads; + + pack_lhs(blockA+info[tid].lhs_start*actual_kc, lhs.getSubMapper(info[tid].lhs_start,k), actual_kc, info[tid].lhs_length); + + // Notify the other threads that the part A'_i is ready to go. + info[tid].sync = k; + + // Computes C_i += A' * B' per A'_i + for(int shift=0; shift<threads; ++shift) + { + int i = (tid+shift)%threads; + + // At this point we have to make sure that A'_i has been updated by the thread i, + // we use testAndSetOrdered to mimic a volatile access. + // However, no need to wait for the B' part which has been updated by the current thread! + if (shift>0) { + while(info[i].sync!=k) { + } + } + + gebp(res.getSubMapper(info[i].lhs_start, 0), blockA+info[i].lhs_start*actual_kc, blockB, info[i].lhs_length, actual_kc, nc, alpha); + } + + // Then keep going as usual with the remaining B' + for(Index j=nc; j<cols; j+=nc) + { + const Index actual_nc = (std::min)(j+nc,cols)-j; + + // pack B_k,j to B' + pack_rhs(blockB, rhs.getSubMapper(k,j), actual_kc, actual_nc); + + // C_j += A' * B' + gebp(res.getSubMapper(0, j), blockA, blockB, rows, actual_kc, actual_nc, alpha); + } + + // Release all the sub blocks A'_i of A' for the current thread, + // i.e., we simply decrement the number of users by 1 + for(Index i=0; i<threads; ++i) +#if !EIGEN_HAS_CXX11_ATOMIC + #pragma omp atomic +#endif + info[i].users -= 1; + } + } + else +#endif // EIGEN_HAS_OPENMP + { + EIGEN_UNUSED_VARIABLE(info); + + // this is the sequential version! + std::size_t sizeA = kc*mc; + std::size_t sizeB = kc*nc; + + ei_declare_aligned_stack_constructed_variable(LhsScalar, blockA, sizeA, blocking.blockA()); + ei_declare_aligned_stack_constructed_variable(RhsScalar, blockB, sizeB, blocking.blockB()); + + const bool pack_rhs_once = mc!=rows && kc==depth && nc==cols; + + // For each horizontal panel of the rhs, and corresponding panel of the lhs... + for(Index i2=0; i2<rows; i2+=mc) + { + const Index actual_mc = (std::min)(i2+mc,rows)-i2; + + for(Index k2=0; k2<depth; k2+=kc) + { + const Index actual_kc = (std::min)(k2+kc,depth)-k2; + + // OK, here we have selected one horizontal panel of rhs and one vertical panel of lhs. + // => Pack lhs's panel into a sequential chunk of memory (L2/L3 caching) + // Note that this panel will be read as many times as the number of blocks in the rhs's + // horizontal panel which is, in practice, a very low number. + pack_lhs(blockA, lhs.getSubMapper(i2,k2), actual_kc, actual_mc); + + // For each kc x nc block of the rhs's horizontal panel... + for(Index j2=0; j2<cols; j2+=nc) + { + const Index actual_nc = (std::min)(j2+nc,cols)-j2; + + // We pack the rhs's block into a sequential chunk of memory (L2 caching) + // Note that this block will be read a very high number of times, which is equal to the number of + // micro horizontal panel of the large rhs's panel (e.g., rows/12 times). + if((!pack_rhs_once) || i2==0) + pack_rhs(blockB, rhs.getSubMapper(k2,j2), actual_kc, actual_nc); + + // Everything is packed, we can now call the panel * block kernel: + gebp(res.getSubMapper(i2, j2), blockA, blockB, actual_mc, actual_kc, actual_nc, alpha); + } + } + } + } +} + +}; + +/********************************************************************************* +* Specialization of generic_product_impl for "large" GEMM, i.e., +* implementation of the high level wrapper to general_matrix_matrix_product +**********************************************************************************/ + +template<typename Scalar, typename Index, typename Gemm, typename Lhs, typename Rhs, typename Dest, typename BlockingType> +struct gemm_functor +{ + gemm_functor(const Lhs& lhs, const Rhs& rhs, Dest& dest, const Scalar& actualAlpha, BlockingType& blocking) + : m_lhs(lhs), m_rhs(rhs), m_dest(dest), m_actualAlpha(actualAlpha), m_blocking(blocking) + {} + + void initParallelSession(Index num_threads) const + { + m_blocking.initParallel(m_lhs.rows(), m_rhs.cols(), m_lhs.cols(), num_threads); + m_blocking.allocateA(); + } + + void operator() (Index row, Index rows, Index col=0, Index cols=-1, GemmParallelInfo<Index>* info=0) const + { + if(cols==-1) + cols = m_rhs.cols(); + + Gemm::run(rows, cols, m_lhs.cols(), + &m_lhs.coeffRef(row,0), m_lhs.outerStride(), + &m_rhs.coeffRef(0,col), m_rhs.outerStride(), + (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), + m_actualAlpha, m_blocking, info); + } + + typedef typename Gemm::Traits Traits; + + protected: + const Lhs& m_lhs; + const Rhs& m_rhs; + Dest& m_dest; + Scalar m_actualAlpha; + BlockingType& m_blocking; +}; + +template<int StorageOrder, typename LhsScalar, typename RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor=1, +bool FiniteAtCompileTime = MaxRows!=Dynamic && MaxCols!=Dynamic && MaxDepth != Dynamic> class gemm_blocking_space; + +template<typename _LhsScalar, typename _RhsScalar> +class level3_blocking +{ + typedef _LhsScalar LhsScalar; + typedef _RhsScalar RhsScalar; + + protected: + LhsScalar* m_blockA; + RhsScalar* m_blockB; + + Index m_mc; + Index m_nc; + Index m_kc; + + public: + + level3_blocking() + : m_blockA(0), m_blockB(0), m_mc(0), m_nc(0), m_kc(0) + {} + + inline Index mc() const { return m_mc; } + inline Index nc() const { return m_nc; } + inline Index kc() const { return m_kc; } + + inline LhsScalar* blockA() { return m_blockA; } + inline RhsScalar* blockB() { return m_blockB; } +}; + +template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor> +class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, true /* == FiniteAtCompileTime */> + : public level3_blocking< + typename conditional<StorageOrder==RowMajor,_RhsScalar,_LhsScalar>::type, + typename conditional<StorageOrder==RowMajor,_LhsScalar,_RhsScalar>::type> +{ + enum { + Transpose = StorageOrder==RowMajor, + ActualRows = Transpose ? MaxCols : MaxRows, + ActualCols = Transpose ? MaxRows : MaxCols + }; + typedef typename conditional<Transpose,_RhsScalar,_LhsScalar>::type LhsScalar; + typedef typename conditional<Transpose,_LhsScalar,_RhsScalar>::type RhsScalar; + typedef gebp_traits<LhsScalar,RhsScalar> Traits; + enum { + SizeA = ActualRows * MaxDepth, + SizeB = ActualCols * MaxDepth + }; + +#if EIGEN_MAX_STATIC_ALIGN_BYTES >= EIGEN_DEFAULT_ALIGN_BYTES + EIGEN_ALIGN_MAX LhsScalar m_staticA[SizeA]; + EIGEN_ALIGN_MAX RhsScalar m_staticB[SizeB]; +#else + EIGEN_ALIGN_MAX char m_staticA[SizeA * sizeof(LhsScalar) + EIGEN_DEFAULT_ALIGN_BYTES-1]; + EIGEN_ALIGN_MAX char m_staticB[SizeB * sizeof(RhsScalar) + EIGEN_DEFAULT_ALIGN_BYTES-1]; +#endif + + public: + + gemm_blocking_space(Index /*rows*/, Index /*cols*/, Index /*depth*/, Index /*num_threads*/, bool /*full_rows = false*/) + { + this->m_mc = ActualRows; + this->m_nc = ActualCols; + this->m_kc = MaxDepth; +#if EIGEN_MAX_STATIC_ALIGN_BYTES >= EIGEN_DEFAULT_ALIGN_BYTES + this->m_blockA = m_staticA; + this->m_blockB = m_staticB; +#else + this->m_blockA = reinterpret_cast<LhsScalar*>((internal::UIntPtr(m_staticA) + (EIGEN_DEFAULT_ALIGN_BYTES-1)) & ~std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1)); + this->m_blockB = reinterpret_cast<RhsScalar*>((internal::UIntPtr(m_staticB) + (EIGEN_DEFAULT_ALIGN_BYTES-1)) & ~std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1)); +#endif + } + + void initParallel(Index, Index, Index, Index) + {} + + inline void allocateA() {} + inline void allocateB() {} + inline void allocateAll() {} +}; + +template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor> +class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, false> + : public level3_blocking< + typename conditional<StorageOrder==RowMajor,_RhsScalar,_LhsScalar>::type, + typename conditional<StorageOrder==RowMajor,_LhsScalar,_RhsScalar>::type> +{ + enum { + Transpose = StorageOrder==RowMajor + }; + typedef typename conditional<Transpose,_RhsScalar,_LhsScalar>::type LhsScalar; + typedef typename conditional<Transpose,_LhsScalar,_RhsScalar>::type RhsScalar; + typedef gebp_traits<LhsScalar,RhsScalar> Traits; + + Index m_sizeA; + Index m_sizeB; + + public: + + gemm_blocking_space(Index rows, Index cols, Index depth, Index num_threads, bool l3_blocking) + { + this->m_mc = Transpose ? cols : rows; + this->m_nc = Transpose ? rows : cols; + this->m_kc = depth; + + if(l3_blocking) + { + computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, this->m_nc, num_threads); + } + else // no l3 blocking + { + Index n = this->m_nc; + computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, n, num_threads); + } + + m_sizeA = this->m_mc * this->m_kc; + m_sizeB = this->m_kc * this->m_nc; + } + + void initParallel(Index rows, Index cols, Index depth, Index num_threads) + { + this->m_mc = Transpose ? cols : rows; + this->m_nc = Transpose ? rows : cols; + this->m_kc = depth; + + eigen_internal_assert(this->m_blockA==0 && this->m_blockB==0); + Index m = this->m_mc; + computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, m, this->m_nc, num_threads); + m_sizeA = this->m_mc * this->m_kc; + m_sizeB = this->m_kc * this->m_nc; + } + + void allocateA() + { + if(this->m_blockA==0) + this->m_blockA = aligned_new<LhsScalar>(m_sizeA); + } + + void allocateB() + { + if(this->m_blockB==0) + this->m_blockB = aligned_new<RhsScalar>(m_sizeB); + } + + void allocateAll() + { + allocateA(); + allocateB(); + } + + ~gemm_blocking_space() + { + aligned_delete(this->m_blockA, m_sizeA); + aligned_delete(this->m_blockB, m_sizeB); + } +}; + +} // end namespace internal + +namespace internal { + +template<typename Lhs, typename Rhs> +struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct> + : generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct> > +{ + typedef typename Product<Lhs,Rhs>::Scalar Scalar; + typedef typename Lhs::Scalar LhsScalar; + typedef typename Rhs::Scalar RhsScalar; + + typedef internal::blas_traits<Lhs> LhsBlasTraits; + typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType; + typedef typename internal::remove_all<ActualLhsType>::type ActualLhsTypeCleaned; + + typedef internal::blas_traits<Rhs> RhsBlasTraits; + typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType; + typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned; + + enum { + MaxDepthAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(Lhs::MaxColsAtCompileTime,Rhs::MaxRowsAtCompileTime) + }; + + typedef generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode> lazyproduct; + + template<typename Dst> + static void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + { + // See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=404 for a discussion and helper program + // to determine the following heuristic. + // EIGEN_GEMM_TO_COEFFBASED_THRESHOLD is typically defined to 20 in GeneralProduct.h, + // unless it has been specialized by the user or for a given architecture. + // Note that the condition rhs.rows()>0 was required because lazy product is (was?) not happy with empty inputs. + // I'm not sure it is still required. + if((rhs.rows()+dst.rows()+dst.cols())<EIGEN_GEMM_TO_COEFFBASED_THRESHOLD && rhs.rows()>0) + lazyproduct::eval_dynamic(dst, lhs, rhs, internal::assign_op<typename Dst::Scalar,Scalar>()); + else + { + dst.setZero(); + scaleAndAddTo(dst, lhs, rhs, Scalar(1)); + } + } + + template<typename Dst> + static void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + { + if((rhs.rows()+dst.rows()+dst.cols())<EIGEN_GEMM_TO_COEFFBASED_THRESHOLD && rhs.rows()>0) + lazyproduct::eval_dynamic(dst, lhs, rhs, internal::add_assign_op<typename Dst::Scalar,Scalar>()); + else + scaleAndAddTo(dst,lhs, rhs, Scalar(1)); + } + + template<typename Dst> + static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + { + if((rhs.rows()+dst.rows()+dst.cols())<EIGEN_GEMM_TO_COEFFBASED_THRESHOLD && rhs.rows()>0) + lazyproduct::eval_dynamic(dst, lhs, rhs, internal::sub_assign_op<typename Dst::Scalar,Scalar>()); + else + scaleAndAddTo(dst, lhs, rhs, Scalar(-1)); + } + + template<typename Dest> + static void scaleAndAddTo(Dest& dst, const Lhs& a_lhs, const Rhs& a_rhs, const Scalar& alpha) + { + eigen_assert(dst.rows()==a_lhs.rows() && dst.cols()==a_rhs.cols()); + if(a_lhs.cols()==0 || a_lhs.rows()==0 || a_rhs.cols()==0) + return; + + if (dst.cols() == 1) + { + // Fallback to GEMV if either the lhs or rhs is a runtime vector + typename Dest::ColXpr dst_vec(dst.col(0)); + return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct> + ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); + } + else if (dst.rows() == 1) + { + // Fallback to GEMV if either the lhs or rhs is a runtime vector + typename Dest::RowXpr dst_vec(dst.row(0)); + return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct> + ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); + } + + typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs); + typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs); + + Scalar actualAlpha = combine_scalar_factors(alpha, a_lhs, a_rhs); + + typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,LhsScalar,RhsScalar, + Dest::MaxRowsAtCompileTime,Dest::MaxColsAtCompileTime,MaxDepthAtCompileTime> BlockingType; + + typedef internal::gemm_functor< + Scalar, Index, + internal::general_matrix_matrix_product< + Index, + LhsScalar, (ActualLhsTypeCleaned::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(LhsBlasTraits::NeedToConjugate), + RhsScalar, (ActualRhsTypeCleaned::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(RhsBlasTraits::NeedToConjugate), + (Dest::Flags&RowMajorBit) ? RowMajor : ColMajor, + Dest::InnerStrideAtCompileTime>, + ActualLhsTypeCleaned, ActualRhsTypeCleaned, Dest, BlockingType> GemmFunctor; + + BlockingType blocking(dst.rows(), dst.cols(), lhs.cols(), 1, true); + internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> + (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_GENERAL_MATRIX_MATRIX_H |