src/core/NEON/kernels/arm_gemm/gemm_interleaved_2d.hpp

/*
 * 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 <algorithm>
#include <cassert>

// 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<typename strategy, typename To, typename Tr>
class GemmInterleaved2d : public GemmCommon<To, Tr> {
    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<strategy, To, Tr> &_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<strategy, To, Tr> &parent)
        : _parent(parent)
        , _xmax { parent._Nsize }
        { }

        blockwalker(const GemmInterleaved2d<strategy, To, Tr> &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<int8_t *>(_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<Tri *>(c_panel_start + get_c_working_size() * threadid);
        auto a_panel = reinterpret_cast<Toi *>(a_panel_start + get_a_working_size() * nthreadid);
        auto b_panel = reinterpret_cast<Toi *>(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<last_m; y+=strategy::out_height()) {
                    unsigned int ymax = std::min(_Msize, y + strategy::out_height());

                    strat.kernel(a_ptr, b_panel, c_panel, 1, bblocks, kern_k);
                    a_ptr += (strategy::out_height() * kern_k);

                    const bool first_pass = current.k0()==0;
                    const bool last_pass  = current.kmax()==_Ksize;

                    auto c_panel_out = this->_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<int8_t *>(working_space);
        intptr_t working_space_int  = reinterpret_cast<intptr_t>(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<void *>(working_space_bytes);
    }

    ~GemmInterleaved2d() override { }
};

} // namespace arm_gemm