/* * Copyright (c) 2020 ARM Limited. * * SPDX-License-Identifier: MIT * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to * deal in the Software without restriction, including without limitation the * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or * sell copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in all * copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ #pragma once #include "arm_gemm.hpp" #include "utils.hpp" #include "mergeresults.hpp" #include "transform.hpp" #ifdef CYCLE_PROFILING #include "profiler.hpp" #endif #include #include // Some macros used to decide how much working space to allocate. // Round allocations up to the next cache line. #define ALLOC_ROUND 64 #define ROUND_UP(x) ((((x) + ALLOC_ROUND-1) / ALLOC_ROUND) * ALLOC_ROUND) // Implementation of the GemmCommon abstract class. // // This implementation interleaves the source matrices in blocks - good for // larger matrices. namespace arm_gemm { template class GemmInterleaved2d : public GemmCommon { typedef typename strategy::operand_type Toi; typedef typename strategy::result_type Tri; /* const properties set by constructor */ const CPUInfo * const _ci; const unsigned int _Msize; const unsigned int _Nsize; const unsigned int _Ksize; const unsigned int _nbatches; const unsigned int _nmulti; const bool _trA; const bool _trB; const Activation _act; const int _maxthreads; int _nthreads; /* Blocking info */ unsigned int _k_block=0; unsigned int _x_block=0; unsigned int _Mround_div=0; unsigned int _Mround=0; unsigned int _Nround_div=0; unsigned int _Nround=0; /* Working space, pretransposed buffer */ void *_working_space=nullptr; /* We will need to walk through the blocks of B in a few contexts, so * factor that out. */ class blockwalker { private: /* Size loops, etc. based on our parent's configuration */ const GemmInterleaved2d &_parent; /* K, X and multi parameters for current iteration. */ unsigned int _k0=0, _x0=0, _xmin=0, _xmax=0, _multi=0; unsigned int _index=0; bool _done=false; bool _newkblock=true; bool _newmulti=true; public: blockwalker(const GemmInterleaved2d &parent) : _parent(parent) , _xmax { parent._Nsize } { } blockwalker(const GemmInterleaved2d &parent, unsigned int x0, unsigned int xmax) : _parent(parent) , _x0 { x0 } , _xmin { x0 } , _xmax { xmax } { assert(_x0 <= _xmax); } unsigned int xmax() { return std::min(_x0 + _parent._x_block, _xmax); } unsigned int kmax() { return std::min(_k0 + _parent._k_block, _parent._Ksize); } /* Advance to the next block, return false at the end. */ bool advance(void) { if (_done) { return false; } _newkblock=false; _x0 += _parent._x_block; if (_x0 >= _xmax) { _x0=_xmin; _k0 += _parent._k_block; if (_k0 >= _parent._Ksize) { _k0=0; _multi++; if (_multi >= _parent._nmulti) { _done=true; return false; } _newmulti=true; } _newkblock=true; } _index++; return true; } unsigned int k0(void) { return _k0; } unsigned int x0(void) { return _x0; } unsigned int multi(void) { return _multi; } unsigned int index(void) { return _index; } bool done(void) { return _done; } bool newkblock(void) { return _newkblock; } }; // A working size: One of these needed, regardless of thread count. Divided according to window. size_t get_a_working_size() const { return ROUND_UP(sizeof(Toi) * _k_block * _Mround * _nbatches) * 2; } // B working size: 0, 1 or 3 of these needed depending on pretransposed and threading settings. size_t get_b_working_size() const { return ROUND_UP(sizeof(Toi) * _x_block * _k_block); } // C working size: One needed per thread. size_t get_c_working_size() const { return ROUND_UP(sizeof(Tri) * _x_block * strategy::out_height()); } void execute_transpose(unsigned int m_start, unsigned int m_end, unsigned int n_start, unsigned int n_end, int threadid, int mthreadid, int nthreadid) { UNUSED(mthreadid); strategy strat(_ci); /* Translate 'start' and 'end' into a position within the batches and rows. */ const unsigned int window_per_batch = _Mround / strategy::out_height(); unsigned int batch_0 = m_start / window_per_batch; unsigned int batch_end = m_end / window_per_batch; /* Compute the M values to operate on */ unsigned int m_0 = (m_start - (batch_0 * window_per_batch)) * strategy::out_height(); unsigned int m_max = (m_end - (batch_end * window_per_batch)) * strategy::out_height(); unsigned int n_0 = std::min(this->_Nsize, strategy::out_width() * n_start); unsigned int n_max = std::min(this->_Nsize, strategy::out_width() * n_end); blockwalker current(*this, n_0, n_max); /* get workspace as int8_t */ assert(_working_space); int8_t *working_space_bytes = reinterpret_cast(_working_space); auto c_panel_start = working_space_bytes; auto a_panel_start = c_panel_start + get_c_working_size() * _maxthreads; auto b_panel_start = a_panel_start + get_a_working_size() * _maxthreads; auto c_panel = reinterpret_cast(c_panel_start + get_c_working_size() * threadid); auto a_panel = reinterpret_cast(a_panel_start + get_a_working_size() * nthreadid); auto b_panel = reinterpret_cast(b_panel_start + get_b_working_size() * threadid); // newkblock() is always true on the first iteration, so this will be set properly on the first loop. int kern_k = 0; for (;!current.done();current.advance()) { const int bblocks = iceildiv(current.xmax() - current.x0(), strategy::out_width()); /* * The entirity of A^kblock is transpose upfront and computed against individual * blocks of B (xblock) * * Therefore, we only need to retranspose when k_block progresses */ if (current.newkblock()) { for (unsigned int batch = batch_0; batch <= batch_end; batch++) { unsigned int first_m = (batch == batch_0) ? m_0 : 0; unsigned int last_m = (batch == batch_end) ? m_max : _Msize; if (first_m >= last_m) continue; auto a_thread_panel_in = this->_Aptr + (batch * this->_A_batch_stride) + (current.multi() * this->_A_multi_stride); auto a_thread_panel_out = a_panel + ((batch * _Mround + first_m) * _k_block); strat.transforms.PrepareA( a_thread_panel_out, a_thread_panel_in, this->_lda, first_m, last_m, current.k0(), current.kmax(), _trA); } kern_k = iceildiv(current.kmax() - current.k0(), strategy::k_unroll()); kern_k *= strat.k_unroll(); } auto *b_panel_in = this->_Bptr + (current.multi() * this->_B_multi_stride); strat.transforms.PrepareB( b_panel, //dst b_panel_in, //src this->_ldb, current.x0(), //idx from current.xmax(), //idx to current.k0(), current.kmax(), _trB); //Iterate over the batches for (unsigned int batch = batch_0; batch <= batch_end; batch++) { unsigned int first_m = (batch == batch_0) ? m_0 : 0; unsigned int last_m = (batch == batch_end) ? m_max : _Msize; if (first_m >= last_m) continue; const Toi *a_ptr = a_panel + (batch * _Mround + first_m) * _k_block; //Iterate over the inerleaved rows of the packed A matrix for (unsigned int y=first_m; y_Cptr + this->_C_batch_stride * batch + this->_C_multi_stride * current.multi(); auto bias = (first_pass && this->_bias) ? this->_bias + (current.multi() * this->_bias_multi_stride) : nullptr; auto act = last_pass ? _act : Activation(); strat.transforms.Merge( c_panel_out, c_panel, this->_ldc, y, ymax, current.x0(), current.xmax(), bias, act, !first_pass); //Append } } } } public: GemmInterleaved2d(GemmInterleaved2d &) = delete; GemmInterleaved2d & operator= (GemmInterleaved2d &) = delete; /* Constructor */ /* Constructor */ GemmInterleaved2d(const GemmArgs &args) : _ci(args._ci) , _Msize(args._Msize) , _Nsize(args._Nsize) , _Ksize(args._Ksize) , _nbatches(args._nbatches) , _nmulti(args._nmulti) , _trA(args._trA) , _trB(args._trB) , _act(args._act) , _maxthreads(args._maxthreads) , _nthreads(args._maxthreads) // Work out the rounded size of M - needed for some buffers. , _Mround_div ( iceildiv(_Msize, strategy::out_height()) ) , _Mround ( _Mround_div * strategy::out_height() ) , _Nround_div ( iceildiv(_Nsize, strategy::out_width()) ) , _Nround ( _Nround_div * strategy::out_width() ) { const unsigned int L1_size = _ci->get_L1_cache_size(); const unsigned int L2_size = _ci->get_L2_cache_size(); assert(_maxthreads > 0); // Work out blocking parameters, or override from provided GemmConfig if (args._cfg && args._cfg->inner_block_size) { _k_block = args._cfg->inner_block_size; } else { // k_block: Find out how much of the larger array can be loaded into half the cache. // This should account for associative caches. _k_block = (L1_size / 2) / (sizeof(Toi) * (std::max(strategy::out_width(), strategy::out_height()))); // Needs to be (at least a single) multiple of the K unroll level. _k_block /= strategy::k_unroll(); _k_block = std::max(_k_block, 1U) * strategy::k_unroll(); // Now tune to presented problem size; this is how many blocks we need. unsigned int num_k_blocks = iceildiv(_Ksize, _k_block); // So divide the space equally into that many blocks. _k_block = iceildiv(_Ksize, num_k_blocks); // And round UP to the K unroll level required. _k_block = iceildiv(_k_block, strategy::k_unroll()); _k_block *= strategy::k_unroll(); } if (args._cfg && args._cfg->outer_block_size) { _x_block = args._cfg->outer_block_size; } else { // x_block: Work out how many rows (of length k_block) will fit in the L2 // Don't allocate more than 90% of the L2 to allow for overheads, and subtract off the L1 contents. _x_block = (((L2_size * 9) / 10) - (_k_block * sizeof(Toi) * (strategy::out_width() + strategy::out_height()))) / (sizeof(Toi) * _k_block); // Needs to be (at least a single) multiple of the kernel output width. _x_block /= strategy::out_width(); _x_block = std::max(_x_block, 1U) * strategy::out_width(); // And tune to the presented problem size. unsigned int num_x_blocks = iceildiv(_Nsize, _x_block); _x_block = iceildiv(_Nsize, num_x_blocks); _x_block = iceildiv(_x_block, strategy::out_width()); _x_block *= strategy::out_width(); } // Work out the rounded size of M - needed for some buffers. } // Interface implementation - Compulsory functions ndrange_t get_window_size() const override { unsigned m = (_Mround / strategy::out_height()) * _nbatches; unsigned n = _Nround_div; return { m, n, 1u, 1u, 1u, 1u }; } // set_nthreads: pass on to buffer manager to avoid it waiting for non-existant threads. void set_nthreads(int nthreads) override { _nthreads = std::min(nthreads, _maxthreads); } void execute(const ndcoord_t& work_range, const ndcoord_t& thread_locator, int threadid) override { /* * This particular GEMM implementation can only be broken up over the M & N * dimensions, we inform the frame work of this limitation via the get_window_size function */ assert(ndrange_popcount(work_range) <= 2); const auto m_start = work_range.get_position(0); const auto n_start = work_range.get_position(1); const auto m_size = work_range.get_size(0); const auto n_size = work_range.get_size(1); const auto m_end = m_start + m_size; const auto n_end = n_start + n_size; const auto m_threadid = thread_locator.get_position(0); const auto n_threadid = thread_locator.get_position(1); execute_transpose(m_start, m_end, n_start, n_end, threadid, m_threadid, n_threadid); } std::size_t get_working_size()const override { /* * Because we do not know how schedular will break up * the task, we need to ensure that alloc enough * space to be able to handle the case where every thread * is parallelised across B AND also every thrread is parallelised across A * * If we parallelise across A, then we only need one buffer of A and 64 buffers of B * If we parallelise across B, then we only need 64 buffer of B and */ return get_c_working_size() * _maxthreads + get_a_working_size() * _maxthreads + get_b_working_size() * _maxthreads + 64; //to account for cacheline alignment } void set_working_space(void *working_space) override { // Make sure everything ends up cache line aligned int8_t *working_space_bytes = reinterpret_cast(working_space); intptr_t working_space_int = reinterpret_cast(working_space); size_t diff=0; if (working_space_int & 0x3F) { diff = 0x40 - (working_space_int & 0x3F); } working_space_bytes += diff; _working_space = reinterpret_cast(working_space_bytes); } ~GemmInterleaved2d() override { } }; } // namespace arm_gemm