| // 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 |
| |
| // IWYU pragma: private |
| #include "../InternalHeaderCheck.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; |
| |
| #if defined(EIGEN_HAS_OPENMP) || defined(EIGEN_GEMM_THREADPOOL) |
| if (info) { |
| // this is the parallel version! |
| int tid = info->logical_thread_id; |
| int threads = info->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->task_info[tid].users equals 0. |
| // Then, we set info->task_info[tid].users to the number of threads to mark that all other threads are going to |
| // use it. |
| while (info->task_info[tid].users != 0) { |
| } |
| info->task_info[tid].users = threads; |
| |
| pack_lhs(blockA + info->task_info[tid].lhs_start * actual_kc, |
| lhs.getSubMapper(info->task_info[tid].lhs_start, k), actual_kc, info->task_info[tid].lhs_length); |
| |
| // Notify the other threads that the part A'_i is ready to go. |
| info->task_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->task_info[i].sync != k) { |
| } |
| } |
| |
| gebp(res.getSubMapper(info->task_info[i].lhs_start, 0), blockA + info->task_info[i].lhs_start * actual_kc, |
| blockB, info->task_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) info->task_info[i].users -= 1; |
| } |
| } else |
| #endif // defined(EIGEN_HAS_OPENMP) || defined(EIGEN_GEMM_THREADPOOL) |
| { |
| 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<std::conditional_t<StorageOrder == RowMajor, RhsScalar_, LhsScalar_>, |
| std::conditional_t<StorageOrder == RowMajor, LhsScalar_, RhsScalar_>> { |
| enum { |
| Transpose = StorageOrder == RowMajor, |
| ActualRows = Transpose ? MaxCols : MaxRows, |
| ActualCols = Transpose ? MaxRows : MaxCols |
| }; |
| typedef std::conditional_t<Transpose, RhsScalar_, LhsScalar_> LhsScalar; |
| typedef std::conditional_t<Transpose, LhsScalar_, RhsScalar_> RhsScalar; |
| 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*>((std::uintptr_t(m_staticA) + (EIGEN_DEFAULT_ALIGN_BYTES - 1)) & |
| ~std::size_t(EIGEN_DEFAULT_ALIGN_BYTES - 1)); |
| this->m_blockB = reinterpret_cast<RhsScalar*>((std::uintptr_t(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<std::conditional_t<StorageOrder == RowMajor, RhsScalar_, LhsScalar_>, |
| std::conditional_t<StorageOrder == RowMajor, LhsScalar_, RhsScalar_>> { |
| enum { Transpose = StorageOrder == RowMajor }; |
| typedef std::conditional_t<Transpose, RhsScalar_, LhsScalar_> LhsScalar; |
| typedef std::conditional_t<Transpose, LhsScalar_, RhsScalar_> RhsScalar; |
| |
| 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 internal::remove_all_t<ActualLhsType> ActualLhsTypeCleaned; |
| |
| typedef internal::blas_traits<Rhs> RhsBlasTraits; |
| typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType; |
| typedef internal::remove_all_t<ActualRhsType> ActualRhsTypeCleaned; |
| |
| enum { MaxDepthAtCompileTime = min_size_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); |
| } |
| |
| add_const_on_value_type_t<ActualLhsType> lhs = LhsBlasTraits::extract(a_lhs); |
| add_const_on_value_type_t<ActualRhsType> 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 |
