* Copyright (c) 2025 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
* \file bitwise_and.h
* \brief
*/
#ifndef BITWISE_AND_H_
#define BITWISE_AND_H_
#include "kernel_operator.h"
#include "kernel_tiling/kernel_tiling.h"
#include "bitwise_and_tiling_data.h"
#include "bitwise_and_tiling_key.h"
#include "kernel_operator.h"
namespace NsBitwiseAnd {
using namespace AscendC;
constexpr int32_t BUFFER_NUM = 2;
template <typename TYPE_X1>
class KernelBitwiseAnd {
public:
__aicore__ inline KernelBitwiseAnd(){};
__aicore__ inline void Init(GM_ADDR x1, GM_ADDR x2, GM_ADDR y, uint64_t smallCoreDataNum, uint64_t bigCoreDataNum, uint64_t finalBigTileNum,
uint64_t finalSmallTileNum, uint64_t tileDataNum, uint64_t smallTailDataNum, uint64_t bigTailDataNum, uint64_t tailBlockNum,
uint64_t tmpTileDataNum, uint64_t tmpSmallTailDataNum, uint64_t tmpBigTailDataNum);
__aicore__ inline void Process();
private:
__aicore__ inline void CopyIn(int32_t progress);
__aicore__ inline void CopyOut(int32_t progress);
__aicore__ inline void Compute(int32_t progress);
private:
AscendC::TPipe pipe;
AscendC::TQue<AscendC::TPosition::VECIN, BUFFER_NUM> inQueueX1, inQueueX2;
AscendC::TQue<AscendC::TPosition::VECOUT, BUFFER_NUM> outQueueY;
AscendC::GlobalTensor<TYPE_X1> x1Gm, x2Gm, yGm;
uint64_t coreDataNum;
uint64_t tileNum;
uint64_t tileDataNum;
uint64_t tailDataNum;
uint64_t processDataNum;
uint64_t tmpTileDataNum, tmpTailDataNum, tmpProcessDataNum;
};
template <typename TYPE_X1>
__aicore__ inline void KernelBitwiseAnd<TYPE_X1>::Init(GM_ADDR x1, GM_ADDR x2, GM_ADDR y, uint64_t smallCoreDataNum, uint64_t bigCoreDataNum, uint64_t finalBigTileNum,
uint64_t finalSmallTileNum, uint64_t tileDataNum, uint64_t smallTailDataNum, uint64_t bigTailDataNum, uint64_t tailBlockNum, uint64_t tmpTileDataNum,
uint64_t tmpSmallTailDataNum, uint64_t tmpBigTailDataNum)
{
ASSERT(AscendC::GetBlockNum() != 0 && "block dim can not be zero!");
uint64_t coreId = AscendC::GetBlockIdx();
uint64_t globalBufferIndex = bigCoreDataNum * coreId;
this->tileDataNum = tileDataNum;
this->tmpTileDataNum = tmpTileDataNum;
if (coreId < tailBlockNum) {
this->coreDataNum = bigCoreDataNum;
this->tileNum = finalBigTileNum;
this->tailDataNum = bigTailDataNum;
this->tmpTailDataNum = tmpBigTailDataNum;
} else {
this->coreDataNum = smallCoreDataNum;
this->tileNum = finalSmallTileNum;
this->tailDataNum = smallTailDataNum;
this->tmpTailDataNum = tmpSmallTailDataNum;
globalBufferIndex -= (bigCoreDataNum - smallCoreDataNum) * (coreId - tailBlockNum);
}
x1Gm.SetGlobalBuffer((__gm__ TYPE_X1 *)x1 + globalBufferIndex, this->coreDataNum);
x2Gm.SetGlobalBuffer((__gm__ TYPE_X1 *)x2 + globalBufferIndex, this->coreDataNum);
yGm.SetGlobalBuffer((__gm__ TYPE_X1 *)y + globalBufferIndex, this->coreDataNum);
pipe.InitBuffer(inQueueX1, BUFFER_NUM, this->tileDataNum * sizeof(TYPE_X1));
pipe.InitBuffer(inQueueX2, BUFFER_NUM, this->tileDataNum * sizeof(TYPE_X1));
pipe.InitBuffer(outQueueY, BUFFER_NUM, this->tileDataNum * sizeof(TYPE_X1));
}
template <typename TYPE_X1>
__aicore__ inline void KernelBitwiseAnd<TYPE_X1>::CopyIn(int32_t progress)
{
AscendC::LocalTensor<TYPE_X1> x1Local = inQueueX1.AllocTensor<TYPE_X1>();
AscendC::LocalTensor<TYPE_X1> x2Local = inQueueX2.AllocTensor<TYPE_X1>();
AscendC::DataCopy(x1Local, x1Gm[progress * this->tileDataNum], this->processDataNum);
AscendC::DataCopy(x2Local, x2Gm[progress * this->tileDataNum], this->processDataNum);
inQueueX1.EnQue(x1Local);
inQueueX2.EnQue(x2Local);
}
template <typename TYPE_X1>
__aicore__ inline void KernelBitwiseAnd<TYPE_X1>::CopyOut(int32_t progress)
{
AscendC::LocalTensor<TYPE_X1> yLocal = outQueueY.DeQue<TYPE_X1>();
AscendC::DataCopy(yGm[progress * this->tileDataNum], yLocal, this->processDataNum);
outQueueY.FreeTensor(yLocal);
}
template <typename TYPE_X1>
__aicore__ inline void KernelBitwiseAnd<TYPE_X1>::Compute(int32_t progress)
{
AscendC::LocalTensor<TYPE_X1> x1Local = inQueueX1.DeQue<TYPE_X1>();
AscendC::LocalTensor<TYPE_X1> x2Local = inQueueX2.DeQue<TYPE_X1>();
if constexpr (!std::is_same_v<TYPE_X1, int32_t>) {
AscendC::LocalTensor<TYPE_X1> yLocal = outQueueY.AllocTensor<TYPE_X1>();
AscendC::And(yLocal, x1Local, x2Local, this->processDataNum);
outQueueY.EnQue<TYPE_X1>(yLocal);
} else {
AscendC::LocalTensor<int16_t> yLocal = outQueueY.AllocTensor<int16_t>();
AscendC::And(yLocal, x1Local.template ReinterpretCast<int16_t>(), x2Local.template ReinterpretCast<int16_t>(), this->tmpProcessDataNum);
outQueueY.EnQue<int16_t>(yLocal);
}
inQueueX1.FreeTensor(x1Local);
inQueueX2.FreeTensor(x2Local);
}
template <typename TYPE_X1>
__aicore__ inline void KernelBitwiseAnd<TYPE_X1>::Process()
{
int32_t loopCount = this->tileNum;
this->processDataNum = this->tileDataNum;
if constexpr (std::is_same_v<TYPE_X1, int32_t>) {
this->tmpProcessDataNum = this->tmpTileDataNum;
}
for (int32_t i = 0; i < loopCount - 1; i++) {
CopyIn(i);
Compute(i);
CopyOut(i);
}
this->processDataNum = this->tailDataNum;
if constexpr (std::is_same_v<TYPE_X1, int32_t>) {
this->tmpProcessDataNum = this->tmpTailDataNum;
}
CopyIn(loopCount - 1);
Compute(loopCount - 1);
CopyOut(loopCount - 1);
}
}
#endif