diff options
Diffstat (limited to 'runtimes/nn/depend/external/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h')
| -rw-r--r-- | runtimes/nn/depend/external/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h | 2149 |
1 files changed, 0 insertions, 2149 deletions
diff --git a/runtimes/nn/depend/external/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/runtimes/nn/depend/external/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h deleted file mode 100644 index 45230bce5..000000000 --- a/runtimes/nn/depend/external/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h +++ /dev/null @@ -1,2149 +0,0 @@ -// 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_BLOCK_PANEL_H -#define EIGEN_GENERAL_BLOCK_PANEL_H - - -namespace Eigen { - -namespace internal { - -template<typename _LhsScalar, typename _RhsScalar, bool _ConjLhs=false, bool _ConjRhs=false> -class gebp_traits; - - -/** \internal \returns b if a<=0, and returns a otherwise. */ -inline std::ptrdiff_t manage_caching_sizes_helper(std::ptrdiff_t a, std::ptrdiff_t b) -{ - return a<=0 ? b : a; -} - -#if EIGEN_ARCH_i386_OR_x86_64 -const std::ptrdiff_t defaultL1CacheSize = 32*1024; -const std::ptrdiff_t defaultL2CacheSize = 256*1024; -const std::ptrdiff_t defaultL3CacheSize = 2*1024*1024; -#else -const std::ptrdiff_t defaultL1CacheSize = 16*1024; -const std::ptrdiff_t defaultL2CacheSize = 512*1024; -const std::ptrdiff_t defaultL3CacheSize = 512*1024; -#endif - -/** \internal */ -struct CacheSizes { - CacheSizes(): m_l1(-1),m_l2(-1),m_l3(-1) { - int l1CacheSize, l2CacheSize, l3CacheSize; - queryCacheSizes(l1CacheSize, l2CacheSize, l3CacheSize); - m_l1 = manage_caching_sizes_helper(l1CacheSize, defaultL1CacheSize); - m_l2 = manage_caching_sizes_helper(l2CacheSize, defaultL2CacheSize); - m_l3 = manage_caching_sizes_helper(l3CacheSize, defaultL3CacheSize); - } - - std::ptrdiff_t m_l1; - std::ptrdiff_t m_l2; - std::ptrdiff_t m_l3; -}; - - -/** \internal */ -inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1, std::ptrdiff_t* l2, std::ptrdiff_t* l3) -{ - static CacheSizes m_cacheSizes; - - if(action==SetAction) - { - // set the cpu cache size and cache all block sizes from a global cache size in byte - eigen_internal_assert(l1!=0 && l2!=0); - m_cacheSizes.m_l1 = *l1; - m_cacheSizes.m_l2 = *l2; - m_cacheSizes.m_l3 = *l3; - } - else if(action==GetAction) - { - eigen_internal_assert(l1!=0 && l2!=0); - *l1 = m_cacheSizes.m_l1; - *l2 = m_cacheSizes.m_l2; - *l3 = m_cacheSizes.m_l3; - } - else - { - eigen_internal_assert(false); - } -} - -/* Helper for computeProductBlockingSizes. - * - * Given a m x k times k x n matrix product of scalar types \c LhsScalar and \c RhsScalar, - * this function computes the blocking size parameters along the respective dimensions - * for matrix products and related algorithms. The blocking sizes depends on various - * parameters: - * - the L1 and L2 cache sizes, - * - the register level blocking sizes defined by gebp_traits, - * - the number of scalars that fit into a packet (when vectorization is enabled). - * - * \sa setCpuCacheSizes */ - -template<typename LhsScalar, typename RhsScalar, int KcFactor, typename Index> -void evaluateProductBlockingSizesHeuristic(Index& k, Index& m, Index& n, Index num_threads = 1) -{ - typedef gebp_traits<LhsScalar,RhsScalar> Traits; - - // Explanations: - // Let's recall that the product algorithms form mc x kc vertical panels A' on the lhs and - // kc x nc blocks B' on the rhs. B' has to fit into L2/L3 cache. Moreover, A' is processed - // per mr x kc horizontal small panels where mr is the blocking size along the m dimension - // at the register level. This small horizontal panel has to stay within L1 cache. - std::ptrdiff_t l1, l2, l3; - manage_caching_sizes(GetAction, &l1, &l2, &l3); - - if (num_threads > 1) { - typedef typename Traits::ResScalar ResScalar; - enum { - kdiv = KcFactor * (Traits::mr * sizeof(LhsScalar) + Traits::nr * sizeof(RhsScalar)), - ksub = Traits::mr * Traits::nr * sizeof(ResScalar), - kr = 8, - mr = Traits::mr, - nr = Traits::nr - }; - // Increasing k gives us more time to prefetch the content of the "C" - // registers. However once the latency is hidden there is no point in - // increasing the value of k, so we'll cap it at 320 (value determined - // experimentally). - const Index k_cache = (numext::mini<Index>)((l1-ksub)/kdiv, 320); - if (k_cache < k) { - k = k_cache - (k_cache % kr); - eigen_internal_assert(k > 0); - } - - const Index n_cache = (l2-l1) / (nr * sizeof(RhsScalar) * k); - const Index n_per_thread = numext::div_ceil(n, num_threads); - if (n_cache <= n_per_thread) { - // Don't exceed the capacity of the l2 cache. - eigen_internal_assert(n_cache >= static_cast<Index>(nr)); - n = n_cache - (n_cache % nr); - eigen_internal_assert(n > 0); - } else { - n = (numext::mini<Index>)(n, (n_per_thread + nr - 1) - ((n_per_thread + nr - 1) % nr)); - } - - if (l3 > l2) { - // l3 is shared between all cores, so we'll give each thread its own chunk of l3. - const Index m_cache = (l3-l2) / (sizeof(LhsScalar) * k * num_threads); - const Index m_per_thread = numext::div_ceil(m, num_threads); - if(m_cache < m_per_thread && m_cache >= static_cast<Index>(mr)) { - m = m_cache - (m_cache % mr); - eigen_internal_assert(m > 0); - } else { - m = (numext::mini<Index>)(m, (m_per_thread + mr - 1) - ((m_per_thread + mr - 1) % mr)); - } - } - } - else { - // In unit tests we do not want to use extra large matrices, - // so we reduce the cache size to check the blocking strategy is not flawed -#ifdef EIGEN_DEBUG_SMALL_PRODUCT_BLOCKS - l1 = 9*1024; - l2 = 32*1024; - l3 = 512*1024; -#endif - - // Early return for small problems because the computation below are time consuming for small problems. - // Perhaps it would make more sense to consider k*n*m?? - // Note that for very tiny problem, this function should be bypassed anyway - // because we use the coefficient-based implementation for them. - if((numext::maxi)(k,(numext::maxi)(m,n))<48) - return; - - typedef typename Traits::ResScalar ResScalar; - enum { - k_peeling = 8, - k_div = KcFactor * (Traits::mr * sizeof(LhsScalar) + Traits::nr * sizeof(RhsScalar)), - k_sub = Traits::mr * Traits::nr * sizeof(ResScalar) - }; - - // ---- 1st level of blocking on L1, yields kc ---- - - // Blocking on the third dimension (i.e., k) is chosen so that an horizontal panel - // of size mr x kc of the lhs plus a vertical panel of kc x nr of the rhs both fits within L1 cache. - // We also include a register-level block of the result (mx x nr). - // (In an ideal world only the lhs panel would stay in L1) - // Moreover, kc has to be a multiple of 8 to be compatible with loop peeling, leading to a maximum blocking size of: - const Index max_kc = numext::maxi<Index>(((l1-k_sub)/k_div) & (~(k_peeling-1)),1); - const Index old_k = k; - if(k>max_kc) - { - // We are really blocking on the third dimension: - // -> reduce blocking size to make sure the last block is as large as possible - // while keeping the same number of sweeps over the result. - k = (k%max_kc)==0 ? max_kc - : max_kc - k_peeling * ((max_kc-1-(k%max_kc))/(k_peeling*(k/max_kc+1))); - - eigen_internal_assert(((old_k/k) == (old_k/max_kc)) && "the number of sweeps has to remain the same"); - } - - // ---- 2nd level of blocking on max(L2,L3), yields nc ---- - - // TODO find a reliable way to get the actual amount of cache per core to use for 2nd level blocking, that is: - // actual_l2 = max(l2, l3/nb_core_sharing_l3) - // The number below is quite conservative: it is better to underestimate the cache size rather than overestimating it) - // For instance, it corresponds to 6MB of L3 shared among 4 cores. - #ifdef EIGEN_DEBUG_SMALL_PRODUCT_BLOCKS - const Index actual_l2 = l3; - #else - const Index actual_l2 = 1572864; // == 1.5 MB - #endif - - // Here, nc is chosen such that a block of kc x nc of the rhs fit within half of L2. - // The second half is implicitly reserved to access the result and lhs coefficients. - // When k<max_kc, then nc can arbitrarily growth. In practice, it seems to be fruitful - // to limit this growth: we bound nc to growth by a factor x1.5. - // However, if the entire lhs block fit within L1, then we are not going to block on the rows at all, - // and it becomes fruitful to keep the packed rhs blocks in L1 if there is enough remaining space. - Index max_nc; - const Index lhs_bytes = m * k * sizeof(LhsScalar); - const Index remaining_l1 = l1- k_sub - lhs_bytes; - if(remaining_l1 >= Index(Traits::nr*sizeof(RhsScalar))*k) - { - // L1 blocking - max_nc = remaining_l1 / (k*sizeof(RhsScalar)); - } - else - { - // L2 blocking - max_nc = (3*actual_l2)/(2*2*max_kc*sizeof(RhsScalar)); - } - // WARNING Below, we assume that Traits::nr is a power of two. - Index nc = numext::mini<Index>(actual_l2/(2*k*sizeof(RhsScalar)), max_nc) & (~(Traits::nr-1)); - if(n>nc) - { - // We are really blocking over the columns: - // -> reduce blocking size to make sure the last block is as large as possible - // while keeping the same number of sweeps over the packed lhs. - // Here we allow one more sweep if this gives us a perfect match, thus the commented "-1" - n = (n%nc)==0 ? nc - : (nc - Traits::nr * ((nc/*-1*/-(n%nc))/(Traits::nr*(n/nc+1)))); - } - else if(old_k==k) - { - // So far, no blocking at all, i.e., kc==k, and nc==n. - // In this case, let's perform a blocking over the rows such that the packed lhs data is kept in cache L1/L2 - // TODO: part of this blocking strategy is now implemented within the kernel itself, so the L1-based heuristic here should be obsolete. - Index problem_size = k*n*sizeof(LhsScalar); - Index actual_lm = actual_l2; - Index max_mc = m; - if(problem_size<=1024) - { - // problem is small enough to keep in L1 - // Let's choose m such that lhs's block fit in 1/3 of L1 - actual_lm = l1; - } - else if(l3!=0 && problem_size<=32768) - { - // we have both L2 and L3, and problem is small enough to be kept in L2 - // Let's choose m such that lhs's block fit in 1/3 of L2 - actual_lm = l2; - max_mc = (numext::mini<Index>)(576,max_mc); - } - Index mc = (numext::mini<Index>)(actual_lm/(3*k*sizeof(LhsScalar)), max_mc); - if (mc > Traits::mr) mc -= mc % Traits::mr; - else if (mc==0) return; - m = (m%mc)==0 ? mc - : (mc - Traits::mr * ((mc/*-1*/-(m%mc))/(Traits::mr*(m/mc+1)))); - } - } -} - -template <typename Index> -inline bool useSpecificBlockingSizes(Index& k, Index& m, Index& n) -{ -#ifdef EIGEN_TEST_SPECIFIC_BLOCKING_SIZES - if (EIGEN_TEST_SPECIFIC_BLOCKING_SIZES) { - k = numext::mini<Index>(k, EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_K); - m = numext::mini<Index>(m, EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_M); - n = numext::mini<Index>(n, EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_N); - return true; - } -#else - EIGEN_UNUSED_VARIABLE(k) - EIGEN_UNUSED_VARIABLE(m) - EIGEN_UNUSED_VARIABLE(n) -#endif - return false; -} - -/** \brief Computes the blocking parameters for a m x k times k x n matrix product - * - * \param[in,out] k Input: the third dimension of the product. Output: the blocking size along the same dimension. - * \param[in,out] m Input: the number of rows of the left hand side. Output: the blocking size along the same dimension. - * \param[in,out] n Input: the number of columns of the right hand side. Output: the blocking size along the same dimension. - * - * Given a m x k times k x n matrix product of scalar types \c LhsScalar and \c RhsScalar, - * this function computes the blocking size parameters along the respective dimensions - * for matrix products and related algorithms. - * - * The blocking size parameters may be evaluated: - * - either by a heuristic based on cache sizes; - * - or using fixed prescribed values (for testing purposes). - * - * \sa setCpuCacheSizes */ - -template<typename LhsScalar, typename RhsScalar, int KcFactor, typename Index> -void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads = 1) -{ - if (!useSpecificBlockingSizes(k, m, n)) { - evaluateProductBlockingSizesHeuristic<LhsScalar, RhsScalar, KcFactor, Index>(k, m, n, num_threads); - } -} - -template<typename LhsScalar, typename RhsScalar, typename Index> -inline void computeProductBlockingSizes(Index& k, Index& m, Index& n, Index num_threads = 1) -{ - computeProductBlockingSizes<LhsScalar,RhsScalar,1,Index>(k, m, n, num_threads); -} - -#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_CJMADD - #define CJMADD(CJ,A,B,C,T) C = CJ.pmadd(A,B,C); -#else - - // FIXME (a bit overkill maybe ?) - - template<typename CJ, typename A, typename B, typename C, typename T> struct gebp_madd_selector { - EIGEN_ALWAYS_INLINE static void run(const CJ& cj, A& a, B& b, C& c, T& /*t*/) - { - c = cj.pmadd(a,b,c); - } - }; - - template<typename CJ, typename T> struct gebp_madd_selector<CJ,T,T,T,T> { - EIGEN_ALWAYS_INLINE static void run(const CJ& cj, T& a, T& b, T& c, T& t) - { - t = b; t = cj.pmul(a,t); c = padd(c,t); - } - }; - - template<typename CJ, typename A, typename B, typename C, typename T> - EIGEN_STRONG_INLINE void gebp_madd(const CJ& cj, A& a, B& b, C& c, T& t) - { - gebp_madd_selector<CJ,A,B,C,T>::run(cj,a,b,c,t); - } - - #define CJMADD(CJ,A,B,C,T) gebp_madd(CJ,A,B,C,T); -// #define CJMADD(CJ,A,B,C,T) T = B; T = CJ.pmul(A,T); C = padd(C,T); -#endif - -/* Vectorization logic - * real*real: unpack rhs to constant packets, ... - * - * cd*cd : unpack rhs to (b_r,b_r), (b_i,b_i), mul to get (a_r b_r,a_i b_r) (a_r b_i,a_i b_i), - * storing each res packet into two packets (2x2), - * at the end combine them: swap the second and addsub them - * cf*cf : same but with 2x4 blocks - * cplx*real : unpack rhs to constant packets, ... - * real*cplx : load lhs as (a0,a0,a1,a1), and mul as usual - */ -template<typename _LhsScalar, typename _RhsScalar, bool _ConjLhs, bool _ConjRhs> -class gebp_traits -{ -public: - typedef _LhsScalar LhsScalar; - typedef _RhsScalar RhsScalar; - typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar; - - enum { - ConjLhs = _ConjLhs, - ConjRhs = _ConjRhs, - Vectorizable = packet_traits<LhsScalar>::Vectorizable && packet_traits<RhsScalar>::Vectorizable, - LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1, - RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1, - ResPacketSize = Vectorizable ? packet_traits<ResScalar>::size : 1, - - NumberOfRegisters = EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS, - - // register block size along the N direction must be 1 or 4 - nr = 4, - - // register block size along the M direction (currently, this one cannot be modified) - default_mr = (EIGEN_PLAIN_ENUM_MIN(16,NumberOfRegisters)/2/nr)*LhsPacketSize, -#if defined(EIGEN_HAS_SINGLE_INSTRUCTION_MADD) && !defined(EIGEN_VECTORIZE_ALTIVEC) && !defined(EIGEN_VECTORIZE_VSX) - // we assume 16 registers - // See bug 992, if the scalar type is not vectorizable but that EIGEN_HAS_SINGLE_INSTRUCTION_MADD is defined, - // then using 3*LhsPacketSize triggers non-implemented paths in syrk. - mr = Vectorizable ? 3*LhsPacketSize : default_mr, -#else - mr = default_mr, -#endif - - LhsProgress = LhsPacketSize, - RhsProgress = 1 - }; - - typedef typename packet_traits<LhsScalar>::type _LhsPacket; - typedef typename packet_traits<RhsScalar>::type _RhsPacket; - typedef typename packet_traits<ResScalar>::type _ResPacket; - - typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket; - typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket; - typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket; - - typedef ResPacket AccPacket; - - EIGEN_STRONG_INLINE void initAcc(AccPacket& p) - { - p = pset1<ResPacket>(ResScalar(0)); - } - - EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3) - { - pbroadcast4(b, b0, b1, b2, b3); - } - -// EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1) -// { -// pbroadcast2(b, b0, b1); -// } - - template<typename RhsPacketType> - EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, RhsPacketType& dest) const - { - dest = pset1<RhsPacketType>(*b); - } - - EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, RhsPacket& dest) const - { - dest = ploadquad<RhsPacket>(b); - } - - template<typename LhsPacketType> - EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacketType& dest) const - { - dest = pload<LhsPacketType>(a); - } - - template<typename LhsPacketType> - EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacketType& dest) const - { - dest = ploadu<LhsPacketType>(a); - } - - template<typename LhsPacketType, typename RhsPacketType, typename AccPacketType> - EIGEN_STRONG_INLINE void madd(const LhsPacketType& a, const RhsPacketType& b, AccPacketType& c, AccPacketType& tmp) const - { - conj_helper<LhsPacketType,RhsPacketType,ConjLhs,ConjRhs> cj; - // It would be a lot cleaner to call pmadd all the time. Unfortunately if we - // let gcc allocate the register in which to store the result of the pmul - // (in the case where there is no FMA) gcc fails to figure out how to avoid - // spilling register. -#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_MADD - EIGEN_UNUSED_VARIABLE(tmp); - c = cj.pmadd(a,b,c); -#else - tmp = b; tmp = cj.pmul(a,tmp); c = padd(c,tmp); -#endif - } - - EIGEN_STRONG_INLINE void acc(const AccPacket& c, const ResPacket& alpha, ResPacket& r) const - { - r = pmadd(c,alpha,r); - } - - template<typename ResPacketHalf> - EIGEN_STRONG_INLINE void acc(const ResPacketHalf& c, const ResPacketHalf& alpha, ResPacketHalf& r) const - { - r = pmadd(c,alpha,r); - } - -}; - -template<typename RealScalar, bool _ConjLhs> -class gebp_traits<std::complex<RealScalar>, RealScalar, _ConjLhs, false> -{ -public: - typedef std::complex<RealScalar> LhsScalar; - typedef RealScalar RhsScalar; - typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar; - - enum { - ConjLhs = _ConjLhs, - ConjRhs = false, - Vectorizable = packet_traits<LhsScalar>::Vectorizable && packet_traits<RhsScalar>::Vectorizable, - LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1, - RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1, - ResPacketSize = Vectorizable ? packet_traits<ResScalar>::size : 1, - - NumberOfRegisters = EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS, - nr = 4, -#if defined(EIGEN_HAS_SINGLE_INSTRUCTION_MADD) && !defined(EIGEN_VECTORIZE_ALTIVEC) && !defined(EIGEN_VECTORIZE_VSX) - // we assume 16 registers - mr = 3*LhsPacketSize, -#else - mr = (EIGEN_PLAIN_ENUM_MIN(16,NumberOfRegisters)/2/nr)*LhsPacketSize, -#endif - - LhsProgress = LhsPacketSize, - RhsProgress = 1 - }; - - typedef typename packet_traits<LhsScalar>::type _LhsPacket; - typedef typename packet_traits<RhsScalar>::type _RhsPacket; - typedef typename packet_traits<ResScalar>::type _ResPacket; - - typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket; - typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket; - typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket; - - typedef ResPacket AccPacket; - - EIGEN_STRONG_INLINE void initAcc(AccPacket& p) - { - p = pset1<ResPacket>(ResScalar(0)); - } - - EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, RhsPacket& dest) const - { - dest = pset1<RhsPacket>(*b); - } - - EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, RhsPacket& dest) const - { - dest = pset1<RhsPacket>(*b); - } - - EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacket& dest) const - { - dest = pload<LhsPacket>(a); - } - - EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacket& dest) const - { - dest = ploadu<LhsPacket>(a); - } - - EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3) - { - pbroadcast4(b, b0, b1, b2, b3); - } - -// EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1) -// { -// pbroadcast2(b, b0, b1); -// } - - EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp) const - { - madd_impl(a, b, c, tmp, typename conditional<Vectorizable,true_type,false_type>::type()); - } - - EIGEN_STRONG_INLINE void madd_impl(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp, const true_type&) const - { -#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_MADD - EIGEN_UNUSED_VARIABLE(tmp); - c.v = pmadd(a.v,b,c.v); -#else - tmp = b; tmp = pmul(a.v,tmp); c.v = padd(c.v,tmp); -#endif - } - - EIGEN_STRONG_INLINE void madd_impl(const LhsScalar& a, const RhsScalar& b, ResScalar& c, RhsScalar& /*tmp*/, const false_type&) const - { - c += a * b; - } - - EIGEN_STRONG_INLINE void acc(const AccPacket& c, const ResPacket& alpha, ResPacket& r) const - { - r = cj.pmadd(c,alpha,r); - } - -protected: - conj_helper<ResPacket,ResPacket,ConjLhs,false> cj; -}; - -template<typename Packet> -struct DoublePacket -{ - Packet first; - Packet second; -}; - -template<typename Packet> -DoublePacket<Packet> padd(const DoublePacket<Packet> &a, const DoublePacket<Packet> &b) -{ - DoublePacket<Packet> res; - res.first = padd(a.first, b.first); - res.second = padd(a.second,b.second); - return res; -} - -template<typename Packet> -const DoublePacket<Packet>& predux_downto4(const DoublePacket<Packet> &a) -{ - return a; -} - -template<typename Packet> struct unpacket_traits<DoublePacket<Packet> > { typedef DoublePacket<Packet> half; }; -// template<typename Packet> -// DoublePacket<Packet> pmadd(const DoublePacket<Packet> &a, const DoublePacket<Packet> &b) -// { -// DoublePacket<Packet> res; -// res.first = padd(a.first, b.first); -// res.second = padd(a.second,b.second); -// return res; -// } - -template<typename RealScalar, bool _ConjLhs, bool _ConjRhs> -class gebp_traits<std::complex<RealScalar>, std::complex<RealScalar>, _ConjLhs, _ConjRhs > -{ -public: - typedef std::complex<RealScalar> Scalar; - typedef std::complex<RealScalar> LhsScalar; - typedef std::complex<RealScalar> RhsScalar; - typedef std::complex<RealScalar> ResScalar; - - enum { - ConjLhs = _ConjLhs, - ConjRhs = _ConjRhs, - Vectorizable = packet_traits<RealScalar>::Vectorizable - && packet_traits<Scalar>::Vectorizable, - RealPacketSize = Vectorizable ? packet_traits<RealScalar>::size : 1, - ResPacketSize = Vectorizable ? packet_traits<ResScalar>::size : 1, - LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1, - RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1, - - // FIXME: should depend on NumberOfRegisters - nr = 4, - mr = ResPacketSize, - - LhsProgress = ResPacketSize, - RhsProgress = 1 - }; - - typedef typename packet_traits<RealScalar>::type RealPacket; - typedef typename packet_traits<Scalar>::type ScalarPacket; - typedef DoublePacket<RealPacket> DoublePacketType; - - typedef typename conditional<Vectorizable,RealPacket, Scalar>::type LhsPacket; - typedef typename conditional<Vectorizable,DoublePacketType,Scalar>::type RhsPacket; - typedef typename conditional<Vectorizable,ScalarPacket,Scalar>::type ResPacket; - typedef typename conditional<Vectorizable,DoublePacketType,Scalar>::type AccPacket; - - EIGEN_STRONG_INLINE void initAcc(Scalar& p) { p = Scalar(0); } - - EIGEN_STRONG_INLINE void initAcc(DoublePacketType& p) - { - p.first = pset1<RealPacket>(RealScalar(0)); - p.second = pset1<RealPacket>(RealScalar(0)); - } - - // Scalar path - EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, ResPacket& dest) const - { - dest = pset1<ResPacket>(*b); - } - - // Vectorized path - EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, DoublePacketType& dest) const - { - dest.first = pset1<RealPacket>(real(*b)); - dest.second = pset1<RealPacket>(imag(*b)); - } - - EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, ResPacket& dest) const - { - loadRhs(b,dest); - } - EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, DoublePacketType& dest) const - { - eigen_internal_assert(unpacket_traits<ScalarPacket>::size<=4); - loadRhs(b,dest); - } - - EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3) - { - // FIXME not sure that's the best way to implement it! - loadRhs(b+0, b0); - loadRhs(b+1, b1); - loadRhs(b+2, b2); - loadRhs(b+3, b3); - } - - // Vectorized path - EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, DoublePacketType& b0, DoublePacketType& b1) - { - // FIXME not sure that's the best way to implement it! - loadRhs(b+0, b0); - loadRhs(b+1, b1); - } - - // Scalar path - EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsScalar& b0, RhsScalar& b1) - { - // FIXME not sure that's the best way to implement it! - loadRhs(b+0, b0); - loadRhs(b+1, b1); - } - - // nothing special here - EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacket& dest) const - { - dest = pload<LhsPacket>((const typename unpacket_traits<LhsPacket>::type*)(a)); - } - - EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacket& dest) const - { - dest = ploadu<LhsPacket>((const typename unpacket_traits<LhsPacket>::type*)(a)); - } - - EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, DoublePacketType& c, RhsPacket& /*tmp*/) const - { - c.first = padd(pmul(a,b.first), c.first); - c.second = padd(pmul(a,b.second),c.second); - } - - EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, ResPacket& c, RhsPacket& /*tmp*/) const - { - c = cj.pmadd(a,b,c); - } - - EIGEN_STRONG_INLINE void acc(const Scalar& c, const Scalar& alpha, Scalar& r) const { r += alpha * c; } - - EIGEN_STRONG_INLINE void acc(const DoublePacketType& c, const ResPacket& alpha, ResPacket& r) const - { - // assemble c - ResPacket tmp; - if((!ConjLhs)&&(!ConjRhs)) - { - tmp = pcplxflip(pconj(ResPacket(c.second))); - tmp = padd(ResPacket(c.first),tmp); - } - else if((!ConjLhs)&&(ConjRhs)) - { - tmp = pconj(pcplxflip(ResPacket(c.second))); - tmp = padd(ResPacket(c.first),tmp); - } - else if((ConjLhs)&&(!ConjRhs)) - { - tmp = pcplxflip(ResPacket(c.second)); - tmp = padd(pconj(ResPacket(c.first)),tmp); - } - else if((ConjLhs)&&(ConjRhs)) - { - tmp = pcplxflip(ResPacket(c.second)); - tmp = psub(pconj(ResPacket(c.first)),tmp); - } - - r = pmadd(tmp,alpha,r); - } - -protected: - conj_helper<LhsScalar,RhsScalar,ConjLhs,ConjRhs> cj; -}; - -template<typename RealScalar, bool _ConjRhs> -class gebp_traits<RealScalar, std::complex<RealScalar>, false, _ConjRhs > -{ -public: - typedef std::complex<RealScalar> Scalar; - typedef RealScalar LhsScalar; - typedef Scalar RhsScalar; - typedef Scalar ResScalar; - - enum { - ConjLhs = false, - ConjRhs = _ConjRhs, - Vectorizable = packet_traits<RealScalar>::Vectorizable - && packet_traits<Scalar>::Vectorizable, - LhsPacketSize = Vectorizable ? packet_traits<LhsScalar>::size : 1, - RhsPacketSize = Vectorizable ? packet_traits<RhsScalar>::size : 1, - ResPacketSize = Vectorizable ? packet_traits<ResScalar>::size : 1, - - NumberOfRegisters = EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS, - // FIXME: should depend on NumberOfRegisters - nr = 4, - mr = (EIGEN_PLAIN_ENUM_MIN(16,NumberOfRegisters)/2/nr)*ResPacketSize, - - LhsProgress = ResPacketSize, - RhsProgress = 1 - }; - - typedef typename packet_traits<LhsScalar>::type _LhsPacket; - typedef typename packet_traits<RhsScalar>::type _RhsPacket; - typedef typename packet_traits<ResScalar>::type _ResPacket; - - typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket; - typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket; - typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket; - - typedef ResPacket AccPacket; - - EIGEN_STRONG_INLINE void initAcc(AccPacket& p) - { - p = pset1<ResPacket>(ResScalar(0)); - } - - EIGEN_STRONG_INLINE void loadRhs(const RhsScalar* b, RhsPacket& dest) const - { - dest = pset1<RhsPacket>(*b); - } - - void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1, RhsPacket& b2, RhsPacket& b3) - { - pbroadcast4(b, b0, b1, b2, b3); - } - -// EIGEN_STRONG_INLINE void broadcastRhs(const RhsScalar* b, RhsPacket& b0, RhsPacket& b1) -// { -// // FIXME not sure that's the best way to implement it! -// b0 = pload1<RhsPacket>(b+0); -// b1 = pload1<RhsPacket>(b+1); -// } - - EIGEN_STRONG_INLINE void loadLhs(const LhsScalar* a, LhsPacket& dest) const - { - dest = ploaddup<LhsPacket>(a); - } - - EIGEN_STRONG_INLINE void loadRhsQuad(const RhsScalar* b, RhsPacket& dest) const - { - eigen_internal_assert(unpacket_traits<RhsPacket>::size<=4); - loadRhs(b,dest); - } - - EIGEN_STRONG_INLINE void loadLhsUnaligned(const LhsScalar* a, LhsPacket& dest) const - { - dest = ploaddup<LhsPacket>(a); - } - - EIGEN_STRONG_INLINE void madd(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp) const - { - madd_impl(a, b, c, tmp, typename conditional<Vectorizable,true_type,false_type>::type()); - } - - EIGEN_STRONG_INLINE void madd_impl(const LhsPacket& a, const RhsPacket& b, AccPacket& c, RhsPacket& tmp, const true_type&) const - { -#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_MADD - EIGEN_UNUSED_VARIABLE(tmp); - c.v = pmadd(a,b.v,c.v); -#else - tmp = b; tmp.v = pmul(a,tmp.v); c = padd(c,tmp); -#endif - - } - - EIGEN_STRONG_INLINE void madd_impl(const LhsScalar& a, const RhsScalar& b, ResScalar& c, RhsScalar& /*tmp*/, const false_type&) const - { - c += a * b; - } - - EIGEN_STRONG_INLINE void acc(const AccPacket& c, const ResPacket& alpha, ResPacket& r) const - { - r = cj.pmadd(alpha,c,r); - } - -protected: - conj_helper<ResPacket,ResPacket,false,ConjRhs> cj; -}; - -/* optimized GEneral packed Block * packed Panel product kernel - * - * Mixing type logic: C += A * B - * | A | B | comments - * |real |cplx | no vectorization yet, would require to pack A with duplication - * |cplx |real | easy vectorization - */ -template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs> -struct gebp_kernel -{ - typedef gebp_traits<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> Traits; - typedef typename Traits::ResScalar ResScalar; - typedef typename Traits::LhsPacket LhsPacket; - typedef typename Traits::RhsPacket RhsPacket; - typedef typename Traits::ResPacket ResPacket; - typedef typename Traits::AccPacket AccPacket; - - typedef gebp_traits<RhsScalar,LhsScalar,ConjugateRhs,ConjugateLhs> SwappedTraits; - typedef typename SwappedTraits::ResScalar SResScalar; - typedef typename SwappedTraits::LhsPacket SLhsPacket; - typedef typename SwappedTraits::RhsPacket SRhsPacket; - typedef typename SwappedTraits::ResPacket SResPacket; - typedef typename SwappedTraits::AccPacket SAccPacket; - - typedef typename DataMapper::LinearMapper LinearMapper; - - enum { - Vectorizable = Traits::Vectorizable, - LhsProgress = Traits::LhsProgress, - RhsProgress = Traits::RhsProgress, - ResPacketSize = Traits::ResPacketSize - }; - - EIGEN_DONT_INLINE - void operator()(const DataMapper& res, const LhsScalar* blockA, const RhsScalar* blockB, - Index rows, Index depth, Index cols, ResScalar alpha, - Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0); -}; - -template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs> -EIGEN_DONT_INLINE -void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,ConjugateRhs> - ::operator()(const DataMapper& res, const LhsScalar* blockA, const RhsScalar* blockB, - Index rows, Index depth, Index cols, ResScalar alpha, - Index strideA, Index strideB, Index offsetA, Index offsetB) - { - Traits traits; - SwappedTraits straits; - - if(strideA==-1) strideA = depth; - if(strideB==-1) strideB = depth; - conj_helper<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> cj; - Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0; - const Index peeled_mc3 = mr>=3*Traits::LhsProgress ? (rows/(3*LhsProgress))*(3*LhsProgress) : 0; - const Index peeled_mc2 = mr>=2*Traits::LhsProgress ? peeled_mc3+((rows-peeled_mc3)/(2*LhsProgress))*(2*LhsProgress) : 0; - const Index peeled_mc1 = mr>=1*Traits::LhsProgress ? (rows/(1*LhsProgress))*(1*LhsProgress) : 0; - enum { pk = 8 }; // NOTE Such a large peeling factor is important for large matrices (~ +5% when >1000 on Haswell) - const Index peeled_kc = depth & ~(pk-1); - const Index prefetch_res_offset = 32/sizeof(ResScalar); -// const Index depth2 = depth & ~1; - - //---------- Process 3 * LhsProgress rows at once ---------- - // This corresponds to 3*LhsProgress x nr register blocks. - // Usually, make sense only with FMA - if(mr>=3*Traits::LhsProgress) - { - // Here, the general idea is to loop on each largest micro horizontal panel of the lhs (3*Traits::LhsProgress x depth) - // and on each largest micro vertical panel of the rhs (depth * nr). - // Blocking sizes, i.e., 'depth' has been computed so that the micro horizontal panel of the lhs fit in L1. - // However, if depth is too small, we can extend the number of rows of these horizontal panels. - // This actual number of rows is computed as follow: - const Index l1 = defaultL1CacheSize; // in Bytes, TODO, l1 should be passed to this function. - // The max(1, ...) here is needed because we may be using blocking params larger than what our known l1 cache size - // suggests we should be using: either because our known l1 cache size is inaccurate (e.g. on Android, we can only guess), - // or because we are testing specific blocking sizes. - const Index actual_panel_rows = (3*LhsProgress) * std::max<Index>(1,( (l1 - sizeof(ResScalar)*mr*nr - depth*nr*sizeof(RhsScalar)) / (depth * sizeof(LhsScalar) * 3*LhsProgress) )); - for(Index i1=0; i1<peeled_mc3; i1+=actual_panel_rows) - { - const Index actual_panel_end = (std::min)(i1+actual_panel_rows, peeled_mc3); - for(Index j2=0; j2<packet_cols4; j2+=nr) - { - for(Index i=i1; i<actual_panel_end; i+=3*LhsProgress) - { - - // We selected a 3*Traits::LhsProgress x nr micro block of res which is entirely - // stored into 3 x nr registers. - - const LhsScalar* blA = &blockA[i*strideA+offsetA*(3*LhsProgress)]; - prefetch(&blA[0]); - - // gets res block as register - AccPacket C0, C1, C2, C3, - C4, C5, C6, C7, - C8, C9, C10, C11; - traits.initAcc(C0); traits.initAcc(C1); traits.initAcc(C2); traits.initAcc(C3); - traits.initAcc(C4); traits.initAcc(C5); traits.initAcc(C6); traits.initAcc(C7); - traits.initAcc(C8); traits.initAcc(C9); traits.initAcc(C10); traits.initAcc(C11); - - LinearMapper r0 = res.getLinearMapper(i, j2 + 0); - LinearMapper r1 = res.getLinearMapper(i, j2 + 1); - LinearMapper r2 = res.getLinearMapper(i, j2 + 2); - LinearMapper r3 = res.getLinearMapper(i, j2 + 3); - - r0.prefetch(0); - r1.prefetch(0); - r2.prefetch(0); - r3.prefetch(0); - - // performs "inner" products - const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr]; - prefetch(&blB[0]); - LhsPacket A0, A1; - - for(Index k=0; k<peeled_kc; k+=pk) - { - EIGEN_ASM_COMMENT("begin gebp micro kernel 3pX4"); - RhsPacket B_0, T0; - LhsPacket A2; - -#define EIGEN_GEBP_ONESTEP(K) \ - do { \ - EIGEN_ASM_COMMENT("begin step of gebp micro kernel 3pX4"); \ - EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \ - internal::prefetch(blA+(3*K+16)*LhsProgress); \ - if (EIGEN_ARCH_ARM) { internal::prefetch(blB+(4*K+16)*RhsProgress); } /* Bug 953 */ \ - traits.loadLhs(&blA[(0+3*K)*LhsProgress], A0); \ - traits.loadLhs(&blA[(1+3*K)*LhsProgress], A1); \ - traits.loadLhs(&blA[(2+3*K)*LhsProgress], A2); \ - traits.loadRhs(blB + (0+4*K)*Traits::RhsProgress, B_0); \ - traits.madd(A0, B_0, C0, T0); \ - traits.madd(A1, B_0, C4, T0); \ - traits.madd(A2, B_0, C8, B_0); \ - traits.loadRhs(blB + (1+4*K)*Traits::RhsProgress, B_0); \ - traits.madd(A0, B_0, C1, T0); \ - traits.madd(A1, B_0, C5, T0); \ - traits.madd(A2, B_0, C9, B_0); \ - traits.loadRhs(blB + (2+4*K)*Traits::RhsProgress, B_0); \ - traits.madd(A0, B_0, C2, T0); \ - traits.madd(A1, B_0, C6, T0); \ - traits.madd(A2, B_0, C10, B_0); \ - traits.loadRhs(blB + (3+4*K)*Traits::RhsProgress, B_0); \ - traits.madd(A0, B_0, C3 , T0); \ - traits.madd(A1, B_0, C7, T0); \ - traits.madd(A2, B_0, C11, B_0); \ - EIGEN_ASM_COMMENT("end step of gebp micro kernel 3pX4"); \ - } while(false) - - internal::prefetch(blB); - EIGEN_GEBP_ONESTEP(0); - EIGEN_GEBP_ONESTEP(1); - EIGEN_GEBP_ONESTEP(2); - EIGEN_GEBP_ONESTEP(3); - EIGEN_GEBP_ONESTEP(4); - EIGEN_GEBP_ONESTEP(5); - EIGEN_GEBP_ONESTEP(6); - EIGEN_GEBP_ONESTEP(7); - - blB += pk*4*RhsProgress; - blA += pk*3*Traits::LhsProgress; - - EIGEN_ASM_COMMENT("end gebp micro kernel 3pX4"); - } - // process remaining peeled loop - for(Index k=peeled_kc; k<depth; k++) - { - RhsPacket B_0, T0; - LhsPacket A2; - EIGEN_GEBP_ONESTEP(0); - blB += 4*RhsProgress; - blA += 3*Traits::LhsProgress; - } - -#undef EIGEN_GEBP_ONESTEP - - ResPacket R0, R1, R2; - ResPacket alphav = pset1<ResPacket>(alpha); - - R0 = r0.loadPacket(0 * Traits::ResPacketSize); - R1 = r0.loadPacket(1 * Traits::ResPacketSize); - R2 = r0.loadPacket(2 * Traits::ResPacketSize); - traits.acc(C0, alphav, R0); - traits.acc(C4, alphav, R1); - traits.acc(C8, alphav, R2); - r0.storePacket(0 * Traits::ResPacketSize, R0); - r0.storePacket(1 * Traits::ResPacketSize, R1); - r0.storePacket(2 * Traits::ResPacketSize, R2); - - R0 = r1.loadPacket(0 * Traits::ResPacketSize); - R1 = r1.loadPacket(1 * Traits::ResPacketSize); - R2 = r1.loadPacket(2 * Traits::ResPacketSize); - traits.acc(C1, alphav, R0); - traits.acc(C5, alphav, R1); - traits.acc(C9, alphav, R2); - r1.storePacket(0 * Traits::ResPacketSize, R0); - r1.storePacket(1 * Traits::ResPacketSize, R1); - r1.storePacket(2 * Traits::ResPacketSize, R2); - - R0 = r2.loadPacket(0 * Traits::ResPacketSize); - R1 = r2.loadPacket(1 * Traits::ResPacketSize); - R2 = r2.loadPacket(2 * Traits::ResPacketSize); - traits.acc(C2, alphav, R0); - traits.acc(C6, alphav, R1); - traits.acc(C10, alphav, R2); - r2.storePacket(0 * Traits::ResPacketSize, R0); - r2.storePacket(1 * Traits::ResPacketSize, R1); - r2.storePacket(2 * Traits::ResPacketSize, R2); - - R0 = r3.loadPacket(0 * Traits::ResPacketSize); - R1 = r3.loadPacket(1 * Traits::ResPacketSize); - R2 = r3.loadPacket(2 * Traits::ResPacketSize); - traits.acc(C3, alphav, R0); - traits.acc(C7, alphav, R1); - traits.acc(C11, alphav, R2); - r3.storePacket(0 * Traits::ResPacketSize, R0); - r3.storePacket(1 * Traits::ResPacketSize, R1); - r3.storePacket(2 * Traits::ResPacketSize, R2); - } - } - - // Deal with remaining columns of the rhs - for(Index j2=packet_cols4; j2<cols; j2++) - { - for(Index i=i1; i<actual_panel_end; i+=3*LhsProgress) - { - // One column at a time - const LhsScalar* blA = &blockA[i*strideA+offsetA*(3*Traits::LhsProgress)]; - prefetch(&blA[0]); - - // gets res block as register - AccPacket C0, C4, C8; - traits.initAcc(C0); - traits.initAcc(C4); - traits.initAcc(C8); - - LinearMapper r0 = res.getLinearMapper(i, j2); - r0.prefetch(0); - - // performs "inner" products - const RhsScalar* blB = &blockB[j2*strideB+offsetB]; - LhsPacket A0, A1, A2; - - for(Index k=0; k<peeled_kc; k+=pk) - { - EIGEN_ASM_COMMENT("begin gebp micro kernel 3pX1"); - RhsPacket B_0; -#define EIGEN_GEBGP_ONESTEP(K) \ - do { \ - EIGEN_ASM_COMMENT("begin step of gebp micro kernel 3pX1"); \ - EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \ - traits.loadLhs(&blA[(0+3*K)*LhsProgress], A0); \ - traits.loadLhs(&blA[(1+3*K)*LhsProgress], A1); \ - traits.loadLhs(&blA[(2+3*K)*LhsProgress], A2); \ - traits.loadRhs(&blB[(0+K)*RhsProgress], B_0); \ - traits.madd(A0, B_0, C0, B_0); \ - traits.madd(A1, B_0, C4, B_0); \ - traits.madd(A2, B_0, C8, B_0); \ - EIGEN_ASM_COMMENT("end step of gebp micro kernel 3pX1"); \ - } while(false) - - EIGEN_GEBGP_ONESTEP(0); - EIGEN_GEBGP_ONESTEP(1); - EIGEN_GEBGP_ONESTEP(2); - EIGEN_GEBGP_ONESTEP(3); - EIGEN_GEBGP_ONESTEP(4); - EIGEN_GEBGP_ONESTEP(5); - EIGEN_GEBGP_ONESTEP(6); - EIGEN_GEBGP_ONESTEP(7); - - blB += pk*RhsProgress; - blA += pk*3*Traits::LhsProgress; - - EIGEN_ASM_COMMENT("end gebp micro kernel 3pX1"); - } - - // process remaining peeled loop - for(Index k=peeled_kc; k<depth; k++) - { - RhsPacket B_0; - EIGEN_GEBGP_ONESTEP(0); - blB += RhsProgress; - blA += 3*Traits::LhsProgress; - } -#undef EIGEN_GEBGP_ONESTEP - ResPacket R0, R1, R2; - ResPacket alphav = pset1<ResPacket>(alpha); - - R0 = r0.loadPacket(0 * Traits::ResPacketSize); - R1 = r0.loadPacket(1 * Traits::ResPacketSize); - R2 = r0.loadPacket(2 * Traits::ResPacketSize); - traits.acc(C0, alphav, R0); - traits.acc(C4, alphav, R1); - traits.acc(C8, alphav, R2); - r0.storePacket(0 * Traits::ResPacketSize, R0); - r0.storePacket(1 * Traits::ResPacketSize, R1); - r0.storePacket(2 * Traits::ResPacketSize, R2); - } - } - } - } - - //---------- Process 2 * LhsProgress rows at once ---------- - if(mr>=2*Traits::LhsProgress) - { - const Index l1 = defaultL1CacheSize; // in Bytes, TODO, l1 should be passed to this function. - // The max(1, ...) here is needed because we may be using blocking params larger than what our known l1 cache size - // suggests we should be using: either because our known l1 cache size is inaccurate (e.g. on Android, we can only guess), - // or because we are testing specific blocking sizes. - Index actual_panel_rows = (2*LhsProgress) * std::max<Index>(1,( (l1 - sizeof(ResScalar)*mr*nr - depth*nr*sizeof(RhsScalar)) / (depth * sizeof(LhsScalar) * 2*LhsProgress) )); - - for(Index i1=peeled_mc3; i1<peeled_mc2; i1+=actual_panel_rows) - { - Index actual_panel_end = (std::min)(i1+actual_panel_rows, peeled_mc2); - for(Index j2=0; j2<packet_cols4; j2+=nr) - { - for(Index i=i1; i<actual_panel_end; i+=2*LhsProgress) - { - - // We selected a 2*Traits::LhsProgress x nr micro block of res which is entirely - // stored into 2 x nr registers. - - const LhsScalar* blA = &blockA[i*strideA+offsetA*(2*Traits::LhsProgress)]; - prefetch(&blA[0]); - - // gets res block as register - AccPacket C0, C1, C2, C3, - C4, C5, C6, C7; - traits.initAcc(C0); traits.initAcc(C1); traits.initAcc(C2); traits.initAcc(C3); - traits.initAcc(C4); traits.initAcc(C5); traits.initAcc(C6); traits.initAcc(C7); - - LinearMapper r0 = res.getLinearMapper(i, j2 + 0); - LinearMapper r1 = res.getLinearMapper(i, j2 + 1); - LinearMapper r2 = res.getLinearMapper(i, j2 + 2); - LinearMapper r3 = res.getLinearMapper(i, j2 + 3); - - r0.prefetch(prefetch_res_offset); - r1.prefetch(prefetch_res_offset); - r2.prefetch(prefetch_res_offset); - r3.prefetch(prefetch_res_offset); - - // performs "inner" products - const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr]; - prefetch(&blB[0]); - LhsPacket A0, A1; - - for(Index k=0; k<peeled_kc; k+=pk) - { - EIGEN_ASM_COMMENT("begin gebp micro kernel 2pX4"); - RhsPacket B_0, B1, B2, B3, T0; - - #define EIGEN_GEBGP_ONESTEP(K) \ - do { \ - EIGEN_ASM_COMMENT("begin step of gebp micro kernel 2pX4"); \ - EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \ - traits.loadLhs(&blA[(0+2*K)*LhsProgress], A0); \ - traits.loadLhs(&blA[(1+2*K)*LhsProgress], A1); \ - traits.broadcastRhs(&blB[(0+4*K)*RhsProgress], B_0, B1, B2, B3); \ - traits.madd(A0, B_0, C0, T0); \ - traits.madd(A1, B_0, C4, B_0); \ - traits.madd(A0, B1, C1, T0); \ - traits.madd(A1, B1, C5, B1); \ - traits.madd(A0, B2, C2, T0); \ - traits.madd(A1, B2, C6, B2); \ - traits.madd(A0, B3, C3, T0); \ - traits.madd(A1, B3, C7, B3); \ - EIGEN_ASM_COMMENT("end step of gebp micro kernel 2pX4"); \ - } while(false) - - internal::prefetch(blB+(48+0)); - EIGEN_GEBGP_ONESTEP(0); - EIGEN_GEBGP_ONESTEP(1); - EIGEN_GEBGP_ONESTEP(2); - EIGEN_GEBGP_ONESTEP(3); - internal::prefetch(blB+(48+16)); - EIGEN_GEBGP_ONESTEP(4); - EIGEN_GEBGP_ONESTEP(5); - EIGEN_GEBGP_ONESTEP(6); - EIGEN_GEBGP_ONESTEP(7); - - blB += pk*4*RhsProgress; - blA += pk*(2*Traits::LhsProgress); - - EIGEN_ASM_COMMENT("end gebp micro kernel 2pX4"); - } - // process remaining peeled loop - for(Index k=peeled_kc; k<depth; k++) - { - RhsPacket B_0, B1, B2, B3, T0; - EIGEN_GEBGP_ONESTEP(0); - blB += 4*RhsProgress; - blA += 2*Traits::LhsProgress; - } -#undef EIGEN_GEBGP_ONESTEP - - ResPacket R0, R1, R2, R3; - ResPacket alphav = pset1<ResPacket>(alpha); - - R0 = r0.loadPacket(0 * Traits::ResPacketSize); - R1 = r0.loadPacket(1 * Traits::ResPacketSize); - R2 = r1.loadPacket(0 * Traits::ResPacketSize); - R3 = r1.loadPacket(1 * Traits::ResPacketSize); - traits.acc(C0, alphav, R0); - traits.acc(C4, alphav, R1); - traits.acc(C1, alphav, R2); - traits.acc(C5, alphav, R3); - r0.storePacket(0 * Traits::ResPacketSize, R0); - r0.storePacket(1 * Traits::ResPacketSize, R1); - r1.storePacket(0 * Traits::ResPacketSize, R2); - r1.storePacket(1 * Traits::ResPacketSize, R3); - - R0 = r2.loadPacket(0 * Traits::ResPacketSize); - R1 = r2.loadPacket(1 * Traits::ResPacketSize); - R2 = r3.loadPacket(0 * Traits::ResPacketSize); - R3 = r3.loadPacket(1 * Traits::ResPacketSize); - traits.acc(C2, alphav, R0); - traits.acc(C6, alphav, R1); - traits.acc(C3, alphav, R2); - traits.acc(C7, alphav, R3); - r2.storePacket(0 * Traits::ResPacketSize, R0); - r2.storePacket(1 * Traits::ResPacketSize, R1); - r3.storePacket(0 * Traits::ResPacketSize, R2); - r3.storePacket(1 * Traits::ResPacketSize, R3); - } - } - - // Deal with remaining columns of the rhs - for(Index j2=packet_cols4; j2<cols; j2++) - { - for(Index i=i1; i<actual_panel_end; i+=2*LhsProgress) - { - // One column at a time - const LhsScalar* blA = &blockA[i*strideA+offsetA*(2*Traits::LhsProgress)]; - prefetch(&blA[0]); - - // gets res block as register - AccPacket C0, C4; - traits.initAcc(C0); - traits.initAcc(C4); - - LinearMapper r0 = res.getLinearMapper(i, j2); - r0.prefetch(prefetch_res_offset); - - // performs "inner" products - const RhsScalar* blB = &blockB[j2*strideB+offsetB]; - LhsPacket A0, A1; - - for(Index k=0; k<peeled_kc; k+=pk) - { - EIGEN_ASM_COMMENT("begin gebp micro kernel 2pX1"); - RhsPacket B_0, B1; - -#define EIGEN_GEBGP_ONESTEP(K) \ - do { \ - EIGEN_ASM_COMMENT("begin step of gebp micro kernel 2pX1"); \ - EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \ - traits.loadLhs(&blA[(0+2*K)*LhsProgress], A0); \ - traits.loadLhs(&blA[(1+2*K)*LhsProgress], A1); \ - traits.loadRhs(&blB[(0+K)*RhsProgress], B_0); \ - traits.madd(A0, B_0, C0, B1); \ - traits.madd(A1, B_0, C4, B_0); \ - EIGEN_ASM_COMMENT("end step of gebp micro kernel 2pX1"); \ - } while(false) - - EIGEN_GEBGP_ONESTEP(0); - EIGEN_GEBGP_ONESTEP(1); - EIGEN_GEBGP_ONESTEP(2); - EIGEN_GEBGP_ONESTEP(3); - EIGEN_GEBGP_ONESTEP(4); - EIGEN_GEBGP_ONESTEP(5); - EIGEN_GEBGP_ONESTEP(6); - EIGEN_GEBGP_ONESTEP(7); - - blB += pk*RhsProgress; - blA += pk*2*Traits::LhsProgress; - - EIGEN_ASM_COMMENT("end gebp micro kernel 2pX1"); - } - - // process remaining peeled loop - for(Index k=peeled_kc; k<depth; k++) - { - RhsPacket B_0, B1; - EIGEN_GEBGP_ONESTEP(0); - blB += RhsProgress; - blA += 2*Traits::LhsProgress; - } -#undef EIGEN_GEBGP_ONESTEP - ResPacket R0, R1; - ResPacket alphav = pset1<ResPacket>(alpha); - - R0 = r0.loadPacket(0 * Traits::ResPacketSize); - R1 = r0.loadPacket(1 * Traits::ResPacketSize); - traits.acc(C0, alphav, R0); - traits.acc(C4, alphav, R1); - r0.storePacket(0 * Traits::ResPacketSize, R0); - r0.storePacket(1 * Traits::ResPacketSize, R1); - } - } - } - } - //---------- Process 1 * LhsProgress rows at once ---------- - if(mr>=1*Traits::LhsProgress) - { - // loops on each largest micro horizontal panel of lhs (1*LhsProgress x depth) - for(Index i=peeled_mc2; i<peeled_mc1; i+=1*LhsProgress) - { - // loops on each largest micro vertical panel of rhs (depth * nr) - for(Index j2=0; j2<packet_cols4; j2+=nr) - { - // We select a 1*Traits::LhsProgress x nr micro block of res which is entirely - // stored into 1 x nr registers. - - const LhsScalar* blA = &blockA[i*strideA+offsetA*(1*Traits::LhsProgress)]; - prefetch(&blA[0]); - - // gets res block as register - AccPacket C0, C1, C2, C3; - traits.initAcc(C0); - traits.initAcc(C1); - traits.initAcc(C2); - traits.initAcc(C3); - - LinearMapper r0 = res.getLinearMapper(i, j2 + 0); - LinearMapper r1 = res.getLinearMapper(i, j2 + 1); - LinearMapper r2 = res.getLinearMapper(i, j2 + 2); - LinearMapper r3 = res.getLinearMapper(i, j2 + 3); - - r0.prefetch(prefetch_res_offset); - r1.prefetch(prefetch_res_offset); - r2.prefetch(prefetch_res_offset); - r3.prefetch(prefetch_res_offset); - - // performs "inner" products - const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr]; - prefetch(&blB[0]); - LhsPacket A0; - - for(Index k=0; k<peeled_kc; k+=pk) - { - EIGEN_ASM_COMMENT("begin gebp micro kernel 1pX4"); - RhsPacket B_0, B1, B2, B3; - -#define EIGEN_GEBGP_ONESTEP(K) \ - do { \ - EIGEN_ASM_COMMENT("begin step of gebp micro kernel 1pX4"); \ - EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \ - traits.loadLhs(&blA[(0+1*K)*LhsProgress], A0); \ - traits.broadcastRhs(&blB[(0+4*K)*RhsProgress], B_0, B1, B2, B3); \ - traits.madd(A0, B_0, C0, B_0); \ - traits.madd(A0, B1, C1, B1); \ - traits.madd(A0, B2, C2, B2); \ - traits.madd(A0, B3, C3, B3); \ - EIGEN_ASM_COMMENT("end step of gebp micro kernel 1pX4"); \ - } while(false) - - internal::prefetch(blB+(48+0)); - EIGEN_GEBGP_ONESTEP(0); - EIGEN_GEBGP_ONESTEP(1); - EIGEN_GEBGP_ONESTEP(2); - EIGEN_GEBGP_ONESTEP(3); - internal::prefetch(blB+(48+16)); - EIGEN_GEBGP_ONESTEP(4); - EIGEN_GEBGP_ONESTEP(5); - EIGEN_GEBGP_ONESTEP(6); - EIGEN_GEBGP_ONESTEP(7); - - blB += pk*4*RhsProgress; - blA += pk*1*LhsProgress; - - EIGEN_ASM_COMMENT("end gebp micro kernel 1pX4"); - } - // process remaining peeled loop - for(Index k=peeled_kc; k<depth; k++) - { - RhsPacket B_0, B1, B2, B3; - EIGEN_GEBGP_ONESTEP(0); - blB += 4*RhsProgress; - blA += 1*LhsProgress; - } -#undef EIGEN_GEBGP_ONESTEP - - ResPacket R0, R1; - ResPacket alphav = pset1<ResPacket>(alpha); - - R0 = r0.loadPacket(0 * Traits::ResPacketSize); - R1 = r1.loadPacket(0 * Traits::ResPacketSize); - traits.acc(C0, alphav, R0); - traits.acc(C1, alphav, R1); - r0.storePacket(0 * Traits::ResPacketSize, R0); - r1.storePacket(0 * Traits::ResPacketSize, R1); - - R0 = r2.loadPacket(0 * Traits::ResPacketSize); - R1 = r3.loadPacket(0 * Traits::ResPacketSize); - traits.acc(C2, alphav, R0); - traits.acc(C3, alphav, R1); - r2.storePacket(0 * Traits::ResPacketSize, R0); - r3.storePacket(0 * Traits::ResPacketSize, R1); - } - - // Deal with remaining columns of the rhs - for(Index j2=packet_cols4; j2<cols; j2++) - { - // One column at a time - const LhsScalar* blA = &blockA[i*strideA+offsetA*(1*Traits::LhsProgress)]; - prefetch(&blA[0]); - - // gets res block as register - AccPacket C0; - traits.initAcc(C0); - - LinearMapper r0 = res.getLinearMapper(i, j2); - - // performs "inner" products - const RhsScalar* blB = &blockB[j2*strideB+offsetB]; - LhsPacket A0; - - for(Index k=0; k<peeled_kc; k+=pk) - { - EIGEN_ASM_COMMENT("begin gebp micro kernel 1pX1"); - RhsPacket B_0; - -#define EIGEN_GEBGP_ONESTEP(K) \ - do { \ - EIGEN_ASM_COMMENT("begin step of gebp micro kernel 1pX1"); \ - EIGEN_ASM_COMMENT("Note: these asm comments work around bug 935!"); \ - traits.loadLhs(&blA[(0+1*K)*LhsProgress], A0); \ - traits.loadRhs(&blB[(0+K)*RhsProgress], B_0); \ - traits.madd(A0, B_0, C0, B_0); \ - EIGEN_ASM_COMMENT("end step of gebp micro kernel 1pX1"); \ - } while(false); - - EIGEN_GEBGP_ONESTEP(0); - EIGEN_GEBGP_ONESTEP(1); - EIGEN_GEBGP_ONESTEP(2); - EIGEN_GEBGP_ONESTEP(3); - EIGEN_GEBGP_ONESTEP(4); - EIGEN_GEBGP_ONESTEP(5); - EIGEN_GEBGP_ONESTEP(6); - EIGEN_GEBGP_ONESTEP(7); - - blB += pk*RhsProgress; - blA += pk*1*Traits::LhsProgress; - - EIGEN_ASM_COMMENT("end gebp micro kernel 1pX1"); - } - - // process remaining peeled loop - for(Index k=peeled_kc; k<depth; k++) - { - RhsPacket B_0; - EIGEN_GEBGP_ONESTEP(0); - blB += RhsProgress; - blA += 1*Traits::LhsProgress; - } -#undef EIGEN_GEBGP_ONESTEP - ResPacket R0; - ResPacket alphav = pset1<ResPacket>(alpha); - R0 = r0.loadPacket(0 * Traits::ResPacketSize); - traits.acc(C0, alphav, R0); - r0.storePacket(0 * Traits::ResPacketSize, R0); - } - } - } - //---------- Process remaining rows, 1 at once ---------- - if(peeled_mc1<rows) - { - // loop on each panel of the rhs - for(Index j2=0; j2<packet_cols4; j2+=nr) - { - // loop on each row of the lhs (1*LhsProgress x depth) - for(Index i=peeled_mc1; i<rows; i+=1) - { - const LhsScalar* blA = &blockA[i*strideA+offsetA]; - prefetch(&blA[0]); - const RhsScalar* blB = &blockB[j2*strideB+offsetB*nr]; - - // The following piece of code wont work for 512 bit registers - // Moreover, if LhsProgress==8 it assumes that there is a half packet of the same size - // as nr (which is currently 4) for the return type. - typedef typename unpacket_traits<SResPacket>::half SResPacketHalf; - if ((SwappedTraits::LhsProgress % 4) == 0 && - (SwappedTraits::LhsProgress <= 8) && - (SwappedTraits::LhsProgress!=8 || unpacket_traits<SResPacketHalf>::size==nr)) - { - SAccPacket C0, C1, C2, C3; - straits.initAcc(C0); - straits.initAcc(C1); - straits.initAcc(C2); - straits.initAcc(C3); - - const Index spk = (std::max)(1,SwappedTraits::LhsProgress/4); - const Index endk = (depth/spk)*spk; - const Index endk4 = (depth/(spk*4))*(spk*4); - - Index k=0; - for(; k<endk4; k+=4*spk) - { - SLhsPacket A0,A1; - SRhsPacket B_0,B_1; - - straits.loadLhsUnaligned(blB+0*SwappedTraits::LhsProgress, A0); - straits.loadLhsUnaligned(blB+1*SwappedTraits::LhsProgress, A1); - - straits.loadRhsQuad(blA+0*spk, B_0); - straits.loadRhsQuad(blA+1*spk, B_1); - straits.madd(A0,B_0,C0,B_0); - straits.madd(A1,B_1,C1,B_1); - - straits.loadLhsUnaligned(blB+2*SwappedTraits::LhsProgress, A0); - straits.loadLhsUnaligned(blB+3*SwappedTraits::LhsProgress, A1); - straits.loadRhsQuad(blA+2*spk, B_0); - straits.loadRhsQuad(blA+3*spk, B_1); - straits.madd(A0,B_0,C2,B_0); - straits.madd(A1,B_1,C3,B_1); - - blB += 4*SwappedTraits::LhsProgress; - blA += 4*spk; - } - C0 = padd(padd(C0,C1),padd(C2,C3)); - for(; k<endk; k+=spk) - { - SLhsPacket A0; - SRhsPacket B_0; - - straits.loadLhsUnaligned(blB, A0); - straits.loadRhsQuad(blA, B_0); - straits.madd(A0,B_0,C0,B_0); - - blB += SwappedTraits::LhsProgress; - blA += spk; - } - if(SwappedTraits::LhsProgress==8) - { - // Special case where we have to first reduce the accumulation register C0 - typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SResPacket>::half,SResPacket>::type SResPacketHalf; - typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SLhsPacket>::half,SLhsPacket>::type SLhsPacketHalf; - typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SLhsPacket>::half,SRhsPacket>::type SRhsPacketHalf; - typedef typename conditional<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SAccPacket>::half,SAccPacket>::type SAccPacketHalf; - - SResPacketHalf R = res.template gatherPacket<SResPacketHalf>(i, j2); - SResPacketHalf alphav = pset1<SResPacketHalf>(alpha); - - if(depth-endk>0) - { - // We have to handle the last row of the rhs which corresponds to a half-packet - SLhsPacketHalf a0; - SRhsPacketHalf b0; - straits.loadLhsUnaligned(blB, a0); - straits.loadRhs(blA, b0); - SAccPacketHalf c0 = predux_downto4(C0); - straits.madd(a0,b0,c0,b0); - straits.acc(c0, alphav, R); - } - else - { - straits.acc(predux_downto4(C0), alphav, R); - } - res.scatterPacket(i, j2, R); - } - else - { - SResPacket R = res.template gatherPacket<SResPacket>(i, j2); - SResPacket alphav = pset1<SResPacket>(alpha); - straits.acc(C0, alphav, R); - res.scatterPacket(i, j2, R); - } - } - else // scalar path - { - // get a 1 x 4 res block as registers - ResScalar C0(0), C1(0), C2(0), C3(0); - - for(Index k=0; k<depth; k++) - { - LhsScalar A0; - RhsScalar B_0, B_1; - - A0 = blA[k]; - - B_0 = blB[0]; - B_1 = blB[1]; - CJMADD(cj,A0,B_0,C0, B_0); - CJMADD(cj,A0,B_1,C1, B_1); - - B_0 = blB[2]; - B_1 = blB[3]; - CJMADD(cj,A0,B_0,C2, B_0); - CJMADD(cj,A0,B_1,C3, B_1); - - blB += 4; - } - res(i, j2 + 0) += alpha * C0; - res(i, j2 + 1) += alpha * C1; - res(i, j2 + 2) += alpha * C2; - res(i, j2 + 3) += alpha * C3; - } - } - } - // remaining columns - for(Index j2=packet_cols4; j2<cols; j2++) - { - // loop on each row of the lhs (1*LhsProgress x depth) - for(Index i=peeled_mc1; i<rows; i+=1) - { - const LhsScalar* blA = &blockA[i*strideA+offsetA]; - prefetch(&blA[0]); - // gets a 1 x 1 res block as registers - ResScalar C0(0); - const RhsScalar* blB = &blockB[j2*strideB+offsetB]; - for(Index k=0; k<depth; k++) - { - LhsScalar A0 = blA[k]; - RhsScalar B_0 = blB[k]; - CJMADD(cj, A0, B_0, C0, B_0); - } - res(i, j2) += alpha * C0; - } - } - } - } - - -#undef CJMADD - -// pack a block of the lhs -// The traversal is as follow (mr==4): -// 0 4 8 12 ... -// 1 5 9 13 ... -// 2 6 10 14 ... -// 3 7 11 15 ... -// -// 16 20 24 28 ... -// 17 21 25 29 ... -// 18 22 26 30 ... -// 19 23 27 31 ... -// -// 32 33 34 35 ... -// 36 36 38 39 ... -template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode> -struct gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, ColMajor, Conjugate, PanelMode> -{ - typedef typename DataMapper::LinearMapper LinearMapper; - EIGEN_DONT_INLINE void operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride=0, Index offset=0); -}; - -template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode> -EIGEN_DONT_INLINE void gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, ColMajor, Conjugate, PanelMode> - ::operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride, Index offset) -{ - typedef typename packet_traits<Scalar>::type Packet; - enum { PacketSize = packet_traits<Scalar>::size }; - - EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK LHS"); - EIGEN_UNUSED_VARIABLE(stride); - EIGEN_UNUSED_VARIABLE(offset); - eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)); - eigen_assert( ((Pack1%PacketSize)==0 && Pack1<=4*PacketSize) || (Pack1<=4) ); - conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj; - Index count = 0; - - const Index peeled_mc3 = Pack1>=3*PacketSize ? (rows/(3*PacketSize))*(3*PacketSize) : 0; - const Index peeled_mc2 = Pack1>=2*PacketSize ? peeled_mc3+((rows-peeled_mc3)/(2*PacketSize))*(2*PacketSize) : 0; - const Index peeled_mc1 = Pack1>=1*PacketSize ? (rows/(1*PacketSize))*(1*PacketSize) : 0; - const Index peeled_mc0 = Pack2>=1*PacketSize ? peeled_mc1 - : Pack2>1 ? (rows/Pack2)*Pack2 : 0; - - Index i=0; - - // Pack 3 packets - if(Pack1>=3*PacketSize) - { - for(; i<peeled_mc3; i+=3*PacketSize) - { - if(PanelMode) count += (3*PacketSize) * offset; - - for(Index k=0; k<depth; k++) - { - Packet A, B, C; - A = lhs.loadPacket(i+0*PacketSize, k); - B = lhs.loadPacket(i+1*PacketSize, k); - C = lhs.loadPacket(i+2*PacketSize, k); - pstore(blockA+count, cj.pconj(A)); count+=PacketSize; - pstore(blockA+count, cj.pconj(B)); count+=PacketSize; - pstore(blockA+count, cj.pconj(C)); count+=PacketSize; - } - if(PanelMode) count += (3*PacketSize) * (stride-offset-depth); - } - } - // Pack 2 packets - if(Pack1>=2*PacketSize) - { - for(; i<peeled_mc2; i+=2*PacketSize) - { - if(PanelMode) count += (2*PacketSize) * offset; - - for(Index k=0; k<depth; k++) - { - Packet A, B; - A = lhs.loadPacket(i+0*PacketSize, k); - B = lhs.loadPacket(i+1*PacketSize, k); - pstore(blockA+count, cj.pconj(A)); count+=PacketSize; - pstore(blockA+count, cj.pconj(B)); count+=PacketSize; - } - if(PanelMode) count += (2*PacketSize) * (stride-offset-depth); - } - } - // Pack 1 packets - if(Pack1>=1*PacketSize) - { - for(; i<peeled_mc1; i+=1*PacketSize) - { - if(PanelMode) count += (1*PacketSize) * offset; - - for(Index k=0; k<depth; k++) - { - Packet A; - A = lhs.loadPacket(i+0*PacketSize, k); - pstore(blockA+count, cj.pconj(A)); - count+=PacketSize; - } - if(PanelMode) count += (1*PacketSize) * (stride-offset-depth); - } - } - // Pack scalars - if(Pack2<PacketSize && Pack2>1) - { - for(; i<peeled_mc0; i+=Pack2) - { - if(PanelMode) count += Pack2 * offset; - - for(Index k=0; k<depth; k++) - for(Index w=0; w<Pack2; w++) - blockA[count++] = cj(lhs(i+w, k)); - - if(PanelMode) count += Pack2 * (stride-offset-depth); - } - } - for(; i<rows; i++) - { - if(PanelMode) count += offset; - for(Index k=0; k<depth; k++) - blockA[count++] = cj(lhs(i, k)); - if(PanelMode) count += (stride-offset-depth); - } -} - -template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode> -struct gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, RowMajor, Conjugate, PanelMode> -{ - typedef typename DataMapper::LinearMapper LinearMapper; - EIGEN_DONT_INLINE void operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride=0, Index offset=0); -}; - -template<typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, bool Conjugate, bool PanelMode> -EIGEN_DONT_INLINE void gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, RowMajor, Conjugate, PanelMode> - ::operator()(Scalar* blockA, const DataMapper& lhs, Index depth, Index rows, Index stride, Index offset) -{ - typedef typename packet_traits<Scalar>::type Packet; - enum { PacketSize = packet_traits<Scalar>::size }; - - EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK LHS"); - EIGEN_UNUSED_VARIABLE(stride); - EIGEN_UNUSED_VARIABLE(offset); - eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)); - conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj; - Index count = 0; - -// const Index peeled_mc3 = Pack1>=3*PacketSize ? (rows/(3*PacketSize))*(3*PacketSize) : 0; -// const Index peeled_mc2 = Pack1>=2*PacketSize ? peeled_mc3+((rows-peeled_mc3)/(2*PacketSize))*(2*PacketSize) : 0; -// const Index peeled_mc1 = Pack1>=1*PacketSize ? (rows/(1*PacketSize))*(1*PacketSize) : 0; - - int pack = Pack1; - Index i = 0; - while(pack>0) - { - Index remaining_rows = rows-i; - Index peeled_mc = i+(remaining_rows/pack)*pack; - for(; i<peeled_mc; i+=pack) - { - if(PanelMode) count += pack * offset; - - const Index peeled_k = (depth/PacketSize)*PacketSize; - Index k=0; - if(pack>=PacketSize) - { - for(; k<peeled_k; k+=PacketSize) - { - for (Index m = 0; m < pack; m += PacketSize) - { - PacketBlock<Packet> kernel; - for (int p = 0; p < PacketSize; ++p) kernel.packet[p] = lhs.loadPacket(i+p+m, k); - ptranspose(kernel); - for (int p = 0; p < PacketSize; ++p) pstore(blockA+count+m+(pack)*p, cj.pconj(kernel.packet[p])); - } - count += PacketSize*pack; - } - } - for(; k<depth; k++) - { - Index w=0; - for(; w<pack-3; w+=4) - { - Scalar a(cj(lhs(i+w+0, k))), - b(cj(lhs(i+w+1, k))), - c(cj(lhs(i+w+2, k))), - d(cj(lhs(i+w+3, k))); - blockA[count++] = a; - blockA[count++] = b; - blockA[count++] = c; - blockA[count++] = d; - } - if(pack%4) - for(;w<pack;++w) - blockA[count++] = cj(lhs(i+w, k)); - } - - if(PanelMode) count += pack * (stride-offset-depth); - } - - pack -= PacketSize; - if(pack<Pack2 && (pack+PacketSize)!=Pack2) - pack = Pack2; - } - - for(; i<rows; i++) - { - if(PanelMode) count += offset; - for(Index k=0; k<depth; k++) - blockA[count++] = cj(lhs(i, k)); - if(PanelMode) count += (stride-offset-depth); - } -} - -// copy a complete panel of the rhs -// this version is optimized for column major matrices -// The traversal order is as follow: (nr==4): -// 0 1 2 3 12 13 14 15 24 27 -// 4 5 6 7 16 17 18 19 25 28 -// 8 9 10 11 20 21 22 23 26 29 -// . . . . . . . . . . -template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode> -struct gemm_pack_rhs<Scalar, Index, DataMapper, nr, ColMajor, Conjugate, PanelMode> -{ - typedef typename packet_traits<Scalar>::type Packet; - typedef typename DataMapper::LinearMapper LinearMapper; - enum { PacketSize = packet_traits<Scalar>::size }; - EIGEN_DONT_INLINE void operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride=0, Index offset=0); -}; - -template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode> -EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, DataMapper, nr, ColMajor, Conjugate, PanelMode> - ::operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride, Index offset) -{ - EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS COLMAJOR"); - EIGEN_UNUSED_VARIABLE(stride); - EIGEN_UNUSED_VARIABLE(offset); - eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)); - conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj; - Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0; - Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0; - Index count = 0; - const Index peeled_k = (depth/PacketSize)*PacketSize; -// if(nr>=8) -// { -// for(Index j2=0; j2<packet_cols8; j2+=8) -// { -// // skip what we have before -// if(PanelMode) count += 8 * offset; -// const Scalar* b0 = &rhs[(j2+0)*rhsStride]; -// const Scalar* b1 = &rhs[(j2+1)*rhsStride]; -// const Scalar* b2 = &rhs[(j2+2)*rhsStride]; -// const Scalar* b3 = &rhs[(j2+3)*rhsStride]; -// const Scalar* b4 = &rhs[(j2+4)*rhsStride]; -// const Scalar* b5 = &rhs[(j2+5)*rhsStride]; -// const Scalar* b6 = &rhs[(j2+6)*rhsStride]; -// const Scalar* b7 = &rhs[(j2+7)*rhsStride]; -// Index k=0; -// if(PacketSize==8) // TODO enbale vectorized transposition for PacketSize==4 -// { -// for(; k<peeled_k; k+=PacketSize) { -// PacketBlock<Packet> kernel; -// for (int p = 0; p < PacketSize; ++p) { -// kernel.packet[p] = ploadu<Packet>(&rhs[(j2+p)*rhsStride+k]); -// } -// ptranspose(kernel); -// for (int p = 0; p < PacketSize; ++p) { -// pstoreu(blockB+count, cj.pconj(kernel.packet[p])); -// count+=PacketSize; -// } -// } -// } -// for(; k<depth; k++) -// { -// blockB[count+0] = cj(b0[k]); -// blockB[count+1] = cj(b1[k]); -// blockB[count+2] = cj(b2[k]); -// blockB[count+3] = cj(b3[k]); -// blockB[count+4] = cj(b4[k]); -// blockB[count+5] = cj(b5[k]); -// blockB[count+6] = cj(b6[k]); -// blockB[count+7] = cj(b7[k]); -// count += 8; -// } -// // skip what we have after -// if(PanelMode) count += 8 * (stride-offset-depth); -// } -// } - - if(nr>=4) - { - for(Index j2=packet_cols8; j2<packet_cols4; j2+=4) - { - // skip what we have before - if(PanelMode) count += 4 * offset; - const LinearMapper dm0 = rhs.getLinearMapper(0, j2 + 0); - const LinearMapper dm1 = rhs.getLinearMapper(0, j2 + 1); - const LinearMapper dm2 = rhs.getLinearMapper(0, j2 + 2); - const LinearMapper dm3 = rhs.getLinearMapper(0, j2 + 3); - - Index k=0; - if((PacketSize%4)==0) // TODO enable vectorized transposition for PacketSize==2 ?? - { - for(; k<peeled_k; k+=PacketSize) { - PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel; - kernel.packet[0] = dm0.loadPacket(k); - kernel.packet[1%PacketSize] = dm1.loadPacket(k); - kernel.packet[2%PacketSize] = dm2.loadPacket(k); - kernel.packet[3%PacketSize] = dm3.loadPacket(k); - ptranspose(kernel); - pstoreu(blockB+count+0*PacketSize, cj.pconj(kernel.packet[0])); - pstoreu(blockB+count+1*PacketSize, cj.pconj(kernel.packet[1%PacketSize])); - pstoreu(blockB+count+2*PacketSize, cj.pconj(kernel.packet[2%PacketSize])); - pstoreu(blockB+count+3*PacketSize, cj.pconj(kernel.packet[3%PacketSize])); - count+=4*PacketSize; - } - } - for(; k<depth; k++) - { - blockB[count+0] = cj(dm0(k)); - blockB[count+1] = cj(dm1(k)); - blockB[count+2] = cj(dm2(k)); - blockB[count+3] = cj(dm3(k)); - count += 4; - } - // skip what we have after - if(PanelMode) count += 4 * (stride-offset-depth); - } - } - - // copy the remaining columns one at a time (nr==1) - for(Index j2=packet_cols4; j2<cols; ++j2) - { - if(PanelMode) count += offset; - const LinearMapper dm0 = rhs.getLinearMapper(0, j2); - for(Index k=0; k<depth; k++) - { - blockB[count] = cj(dm0(k)); - count += 1; - } - if(PanelMode) count += (stride-offset-depth); - } -} - -// this version is optimized for row major matrices -template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode> -struct gemm_pack_rhs<Scalar, Index, DataMapper, nr, RowMajor, Conjugate, PanelMode> -{ - typedef typename packet_traits<Scalar>::type Packet; - typedef typename DataMapper::LinearMapper LinearMapper; - enum { PacketSize = packet_traits<Scalar>::size }; - EIGEN_DONT_INLINE void operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride=0, Index offset=0); -}; - -template<typename Scalar, typename Index, typename DataMapper, int nr, bool Conjugate, bool PanelMode> -EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, DataMapper, nr, RowMajor, Conjugate, PanelMode> - ::operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride, Index offset) -{ - EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS ROWMAJOR"); - EIGEN_UNUSED_VARIABLE(stride); - EIGEN_UNUSED_VARIABLE(offset); - eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)); - conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj; - Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0; - Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0; - Index count = 0; - -// if(nr>=8) -// { -// for(Index j2=0; j2<packet_cols8; j2+=8) -// { -// // skip what we have before -// if(PanelMode) count += 8 * offset; -// for(Index k=0; k<depth; k++) -// { -// if (PacketSize==8) { -// Packet A = ploadu<Packet>(&rhs[k*rhsStride + j2]); -// pstoreu(blockB+count, cj.pconj(A)); -// } else if (PacketSize==4) { -// Packet A = ploadu<Packet>(&rhs[k*rhsStride + j2]); -// Packet B = ploadu<Packet>(&rhs[k*rhsStride + j2 + PacketSize]); -// pstoreu(blockB+count, cj.pconj(A)); -// pstoreu(blockB+count+PacketSize, cj.pconj(B)); -// } else { -// const Scalar* b0 = &rhs[k*rhsStride + j2]; -// blockB[count+0] = cj(b0[0]); -// blockB[count+1] = cj(b0[1]); -// blockB[count+2] = cj(b0[2]); -// blockB[count+3] = cj(b0[3]); -// blockB[count+4] = cj(b0[4]); -// blockB[count+5] = cj(b0[5]); -// blockB[count+6] = cj(b0[6]); -// blockB[count+7] = cj(b0[7]); -// } -// count += 8; -// } -// // skip what we have after -// if(PanelMode) count += 8 * (stride-offset-depth); -// } -// } - if(nr>=4) - { - for(Index j2=packet_cols8; j2<packet_cols4; j2+=4) - { - // skip what we have before - if(PanelMode) count += 4 * offset; - for(Index k=0; k<depth; k++) - { - if (PacketSize==4) { - Packet A = rhs.loadPacket(k, j2); - pstoreu(blockB+count, cj.pconj(A)); - count += PacketSize; - } else { - const LinearMapper dm0 = rhs.getLinearMapper(k, j2); - blockB[count+0] = cj(dm0(0)); - blockB[count+1] = cj(dm0(1)); - blockB[count+2] = cj(dm0(2)); - blockB[count+3] = cj(dm0(3)); - count += 4; - } - } - // skip what we have after - if(PanelMode) count += 4 * (stride-offset-depth); - } - } - // copy the remaining columns one at a time (nr==1) - for(Index j2=packet_cols4; j2<cols; ++j2) - { - if(PanelMode) count += offset; - for(Index k=0; k<depth; k++) - { - blockB[count] = cj(rhs(k, j2)); - count += 1; - } - if(PanelMode) count += stride-offset-depth; - } -} - -} // end namespace internal - -/** \returns the currently set level 1 cpu cache size (in bytes) used to estimate the ideal blocking size parameters. - * \sa setCpuCacheSize */ -inline std::ptrdiff_t l1CacheSize() -{ - std::ptrdiff_t l1, l2, l3; - internal::manage_caching_sizes(GetAction, &l1, &l2, &l3); - return l1; -} - -/** \returns the currently set level 2 cpu cache size (in bytes) used to estimate the ideal blocking size parameters. - * \sa setCpuCacheSize */ -inline std::ptrdiff_t l2CacheSize() -{ - std::ptrdiff_t l1, l2, l3; - internal::manage_caching_sizes(GetAction, &l1, &l2, &l3); - return l2; -} - -/** \returns the currently set level 3 cpu cache size (in bytes) used to estimate the ideal blocking size paramete\ -rs. -* \sa setCpuCacheSize */ -inline std::ptrdiff_t l3CacheSize() -{ - std::ptrdiff_t l1, l2, l3; - internal::manage_caching_sizes(GetAction, &l1, &l2, &l3); - return l3; -} - -/** Set the cpu L1 and L2 cache sizes (in bytes). - * These values are use to adjust the size of the blocks - * for the algorithms working per blocks. - * - * \sa computeProductBlockingSizes */ -inline void setCpuCacheSizes(std::ptrdiff_t l1, std::ptrdiff_t l2, std::ptrdiff_t l3) -{ - internal::manage_caching_sizes(SetAction, &l1, &l2, &l3); -} - -} // end namespace Eigen - -#endif // EIGEN_GENERAL_BLOCK_PANEL_H |