/* * Copyright (c) 2017-2020 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 #include "arm_gemm.hpp" #include "bias_adder.hpp" #include "mergeresults.hpp" #include "transform.hpp" #ifdef CYCLE_PROFILING #include "profiler.hpp" #endif namespace arm_gemm { // Implementation of the GemmCommon abstract class. // // This is implementation is for GEMV with pretransposition. // // batches are not supported as a batched GEMV makes no sense (can be converted to a GEMM). template class GemvPretransposed : public GemmCommon { typedef typename strategy::operand_type Toi; typedef typename strategy::result_type Tri; const GemmArgs _args; const unsigned int _buffer_per_multi; unsigned int k_block=0; unsigned int n_block=0; const Toi *_B_pretransposed = nullptr; public: GemvPretransposed(GemvPretransposed &) = delete; GemvPretransposed & operator= (GemvPretransposed &) = delete; GemvPretransposed(const GemmArgs &args) : _args(args), _buffer_per_multi(args._Ksize * roundup(args._Nsize, strategy::out_width())) { /* For now don't do any blocking. TODO: figure out if we should. */ if (strategy::supports_accumulate() && args._cfg && args._cfg->inner_block_size) { k_block = args._cfg->inner_block_size; } else { k_block = args._Ksize; } if (args._cfg && args._cfg->outer_block_size) { n_block = args._cfg->outer_block_size; } else { n_block = args._Nsize; } } // Window is number of out_width blocks, times number of multis. ndrange_t get_window_size() const override { return { iceildiv(_args._Nsize, strategy::out_width()) * _args._nmulti }; } // Actually execute the GEMV. void execute(const ndcoord_t &work_range, const ndcoord_t &, int) override { #ifdef CYCLE_PROFILING profiler prof; #endif strategy strat(_args._ci); const auto start = work_range.get_position(0); const auto end = work_range.get_position_end(0); /* Break the window values down into multis of interest... */ const unsigned int window_per_multi = iceildiv(_args._Nsize, strategy::out_width()); const unsigned int multi_0 = start / window_per_multi; const unsigned int multi_end = end / window_per_multi; /* ... and figure out where we start and end in the first and last multi. */ const unsigned int n_0 = (start - (multi_0 * window_per_multi)) * strategy::out_width(); const unsigned int n_max = (end - (multi_end * window_per_multi)) * strategy::out_width(); static_assert(std::is_same::value, "GemvPretransposed: Result types must be the same."); for (unsigned int multi=multi_0; multi<=multi_end; multi++) { const unsigned int n_start = (multi==multi_0) ? n_0 : 0; const unsigned int n_end = (multi==multi_end) ? n_max : _args._Nsize; if (n_end <= n_start) continue; for (unsigned int k0=0; k0<_args._Ksize; k0+=k_block) { unsigned int kmax = std::min(k0 + k_block, _args._Ksize); for (unsigned int n=n_start; n_Aptr + (multi * this->_A_multi_stride) + k0, _B_pretransposed + (multi * _buffer_per_multi) + (n * roundup(_args._Ksize, strategy::k_unroll())) + (k0 * strategy::out_width()), this->_Cptr + (multi * this->_C_multi_stride) + n, (nmax - n), (kmax-k0), this->_bias ? this->_bias + (multi * this->_bias_multi_stride) + n : nullptr, _args._act, (k0 != 0)); } } } } /* Pretransposed interface implementation */ bool B_is_pretransposed() const override { return true; } bool B_pretranspose_required() const override { /* Transpose is required if _B_pretransposed is still nullptr */ return (_B_pretransposed == nullptr); } size_t get_B_pretransposed_array_size() const override { return _buffer_per_multi * _args._nmulti * sizeof(To); } void pretranspose_B_array(void *buffer, const To *B, const int ldb, const int B_multi_stride) override { Toi *B_buffer = reinterpret_cast(buffer); strategy strat(_args._ci); for (unsigned int multi=0; multi<_args._nmulti; multi++) { strat.transforms.PrepareB(B_buffer + (multi * _buffer_per_multi), B + (multi * B_multi_stride), ldb, 0, _args._Nsize, 0, _args._Ksize); } _B_pretransposed = B_buffer; } void set_pretransposed_B_data(void *buffer) override { _B_pretransposed = reinterpret_cast(buffer); } }; } // namespace arm_gemm