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/*
* Copyright (c) 2017-2018 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 <stdio.h>
#include "arm_gemm.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<typename strategy, typename To, typename Tr>
class GemvPretransposed : public GemmCommon<To, Tr> {
typedef typename strategy::operand_type Toi;
typedef typename strategy::result_type Tri;
const unsigned int _Nsize;
const unsigned int _Ksize;
const unsigned int _nmultis;
const bool _trB;
const Tr _beta;
const CPUInfo * const _ci;
const unsigned int _buffer_per_multi;
unsigned int m_block=0;
unsigned int n_block=0;
const Toi *_A_pretransposed = nullptr;
public:
GemvPretransposed(GemvPretransposed &) = delete;
GemvPretransposed & operator= (GemvPretransposed &) = delete;
GemvPretransposed(const CPUInfo *ci, const unsigned int N, const unsigned int K, const unsigned int nmultis, const bool trB, const Tr beta) :
_Nsize(N), _Ksize(K), _nmultis(nmultis), _trB(trB), _beta(beta), _ci(ci),
_buffer_per_multi(_Ksize * iceildiv(_Nsize, strategy::A_interleave) * strategy::A_interleave) {
/* For now don't do any blocking. TODO: figure out if we should. */
m_block = K;
n_block = N;
}
// Window is number of out_width blocks, times number of multis.
unsigned int get_window_size() const override {
return iceildiv(_Nsize, strategy::out_width) * _nmultis;
}
// Actually execute the GEMV.
void execute(unsigned int start, unsigned int end, int) override {
#ifdef CYCLE_PROFILING
profiler prof;
#endif
strategy strat(_ci);
/* Break the window values down into multis of interest... */
const unsigned int window_per_multi = iceildiv(_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<Tr, Tri>::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 : _Nsize;
if (n_end <= n_start)
continue;
for (unsigned int m0=0; m0<_Ksize; m0+=m_block) {
unsigned int mmax = std::min(m0 + m_block, _Ksize);
for (unsigned int n=n_start; n<n_end; n+=n_block) {
unsigned int nmax = std::min(n + n_block, n_end);
#ifdef CYCLE_PROFILING
auto p = prof.ScopedProfiler(PROFILE_KERNEL, (mmax-m0) * (nmax-n));
#endif
/* This assumes that the underlying call was a GEMM with M=1; for the N=1 case we would have to pick up this->_Bptr below instead */
strat.kernel(_A_pretransposed + (multi * _buffer_per_multi) + (n * _Ksize) + (m0 * strategy::A_interleave),
(_Ksize * strategy::A_interleave),
this->_Aptr + (multi * this->_A_multi_stride) + m0,
this->_Cptr + (multi * this->_C_multi_stride) + n,
_beta, (mmax-m0), (nmax-n));
}
}
}
}
/* Pretransposed interface implementation */
bool B_is_pretransposed() const override {
return true;
}
bool B_pretranspose_required() const override {
/* Transpose is required if _A_pretransposed is still nullptr */
return (_A_pretransposed == nullptr);
}
size_t get_B_pretransposed_array_size() const override {
return _buffer_per_multi * _nmultis * sizeof(To);
}
void pretranspose_B_array(void *buffer, const To *B, const int ldb, const int B_multi_stride) override {
Toi *A_buffer = reinterpret_cast<Toi *>(buffer);
for (unsigned int multi=0; multi<_nmultis; multi++) {
/* Reverse sense here as we are dealing with B rather than A. So if
* strategy::A_transpose is false and _trB is false, we still
* transpose. */
if (_trB ^ strategy::A_transpose) {
Transform<strategy::A_interleave, strategy::A_block, false>(A_buffer + (multi * _buffer_per_multi), B + (multi * B_multi_stride), ldb, 0, _Nsize, 0, _Ksize);
} else {
Transform<strategy::A_interleave, strategy::A_block, true>(A_buffer + (multi * _buffer_per_multi), B + (multi * B_multi_stride), ldb, 0, _Nsize, 0, _Ksize);
}
}
_A_pretransposed = A_buffer;
}
void set_pretransposed_B_data(void *buffer) override {
_A_pretransposed = reinterpret_cast<Toi *>(buffer);
}
};
} // namespace arm_gemm