华为Ascend C算子开发（中级）考试题
提示：这个是河北廊坊Ascend C算子开发考试题和答案，仅供参考，因为不确定其他城市的考试题是否也是一样
文章目录
- [华为Ascend C算子开发（中级）考试题](#华为Ascend C算子开发（中级）考试题)
- 一、op_host文件夹下的sinh_custom_tiling.h文件
- 二、op_host文件夹下的sinh_custom.cpp文件
- 三、op_kernel文件夹下的sinh_custom.cpp文件
一、op_host文件夹下的sinh_custom_tiling.h文件
javascript
#include "register/tilingdata_base.h"
namespace optiling {
BEGIN_TILING_DATA_DEF(SinhCustomTilingData)
//考生自行定义 tiling 结构体成员变量
TILING_DATA_FIELD_DEF(uint32_t, totalLength);
TILING_DATA_FIELD_DEF(uint32_t, tileNum);
END_TILING_DATA_DEF;
REGISTER_TILING_DATA_CLASS(SinhCustom, SinhCustomTilingData)
}二、op_host文件夹下的sinh_custom.cpp文件
javascript
#include "sinh_custom_tiling.h"
#include "register/op_def_registry.h"
namespace optiling {
static ge::graphStatus TilingFunc(gert::TilingContext* context)
{
SinhCustomTilingData tiling;
//考生自行填充
const uint32_t BLOCK_DIM = 8;
const uint32_t TILE_NUM = 8;
uint32_t totalLength = context->GetInputShape(0)->GetOriginShape().GetShapeSize();
context->SetBlockDim(BLOCK_DIM);
tiling.set_totalLength(totalLength);
tiling.set_tileNum(TILE_NUM);
tiling.SaveToBuffer(context->GetRawTilingData()->GetData(),
context->GetRawTilingData()->GetCapacity());
context->GetRawTilingData()->SetDataSize(tiling.GetDataSize());
size_t *currentWorkspace = context->GetWorkspaceSizes(1);
currentWorkspace[0] = 0;
return ge::GRAPH_SUCCESS;
}
}
namespace ge {
static ge::graphStatus InferShape(gert::InferShapeContext* context)
{
const gert::Shape* x1_shape = context->GetInputShape(0);
gert::Shape* y_shape = context->GetOutputShape(0);
*y_shape = *x1_shape;
return GRAPH_SUCCESS;
}
}
namespace ops {
class SinhCustom : public OpDef {
public:
explicit SinhCustom(const char* name) : OpDef(name)
{
this->Input("x")
.ParamType(REQUIRED)
.DataType({ge::DT_FLOAT16})
.Format({ge::FORMAT_ND})
.UnknownShapeFormat({ge::FORMAT_ND});
this->Output("y")
.ParamType(REQUIRED)
.DataType({ge::DT_FLOAT16})
.Format({ge::FORMAT_ND})
.UnknownShapeFormat({ge::FORMAT_ND});
this->SetInferShape(ge::InferShape);
this->AICore()
.SetTiling(optiling::TilingFunc);
this->AICore().AddConfig("ascend310b");
}
};
OP_ADD(SinhCustom);
}三、op_kernel文件夹下的sinh_custom.cpp文件
javascript
#include "kernel_operator.h"
using namespace AscendC;
constexpr int32_t BUFFER_NUM = 2;
class KernelSinh {
public:
__aicore__ inline KernelSinh() {}
__aicore__ inline void Init(GM_ADDR x, GM_ADDR y, uint32_t totalLength, uint32_t
tileNum)
{
//考生补充初始化代码
ASSERT(GetBlockNum() != 0 && "block dim can not be zero!");
this->blockLength = totalLength / GetBlockNum();
this->tileNum = tileNum;
ASSERT(tileNum != 0 && "tile num can not be zero!");
this->tileLength = this->blockLength / tileNum / BUFFER_NUM;
xGm.SetGlobalBuffer((__gm__ DTYPE_X *)x + this->blockLength * GetBlockIdx(),
this->blockLength);
yGm.SetGlobalBuffer((__gm__ DTYPE_Y *)y + this->blockLength * GetBlockIdx(),
this->blockLength);
pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(DTYPE_X));
pipe.InitBuffer(outQueueY, BUFFER_NUM, this->tileLength * sizeof(DTYPE_Y));
pipe.InitBuffer(tmpBuffer1, this->tileLength * sizeof(DTYPE_X));
pipe.InitBuffer(tmpBuffer2, this->tileLength * sizeof(DTYPE_X));
pipe.InitBuffer(tmpBuffer3, this->tileLength * sizeof(DTYPE_X));
pipe.InitBuffer(tmpBuffer4, this->tileLength * sizeof(DTYPE_X));
}
__aicore__ inline void Process()
{
//考生补充对"loopCount"的定义，注意对 Tiling 的处理
int32_t loopCount = this->tileNum * BUFFER_NUM;
for (int32_t i = 0; i < loopCount; i++) {
CopyIn(i);
Compute(i);
CopyOut(i);
}
}
private:
__aicore__ inline void CopyIn(int32_t progress)
{
//考生补充算子代码
LocalTensor<DTYPE_X> xLocal = inQueueX.AllocTensor<DTYPE_X>();
DataCopy(xLocal, xGm[progress * this->tileLength], this->tileLength);
inQueueX.EnQue(xLocal);
}
__aicore__ inline void Compute(int32_t progress)
{
//考生补充算子计算代码
LocalTensor<DTYPE_X> xLocal = inQueueX.DeQue<DTYPE_X>();
LocalTensor<DTYPE_Y> yLocal = outQueueY.AllocTensor<DTYPE_Y>();
LocalTensor<DTYPE_X> tmpTensor1 = tmpBuffer1.Get<DTYPE_X>();
LocalTensor<DTYPE_X> tmpTensor2 = tmpBuffer2.Get<DTYPE_X>();
LocalTensor<DTYPE_X> tmpTensor3 = tmpBuffer3.Get<DTYPE_X>();
LocalTensor<DTYPE_X> tmpTensor4 = tmpBuffer4.Get<DTYPE_X>();
DTYPE_X inputVal1 = -1;
DTYPE_X inputVal2 = 0.5;
//sinh(x) = (exp(x) - exp(-x)) / 2.0
Muls(tmpTensor1, xLocal, inputVal1, this->tileLength);
Exp(tmpTensor2, tmpTensor1, this->tileLength);
Exp(tmpTensor3, xLocal, this->tileLength);
Sub(tmpTensor4, tmpTensor3, tmpTensor2, this->tileLength);
Muls(yLocal, tmpTensor4, inputVal2, this->tileLength);
outQueueY.EnQue<DTYPE_Y>(yLocal);
inQueueX.FreeTensor(xLocal);
}
__aicore__ inline void CopyOut(int32_t progress)
{
//考生补充算子代码
LocalTensor<DTYPE_Y> yLocal = outQueueY.DeQue<DTYPE_Y>();
DataCopy(yGm[progress * this->tileLength], yLocal, this->tileLength);
outQueueY.FreeTensor(yLocal);
}
private:
TPipe pipe;
//create queue for input, in this case depth is equal to buffer num
TQue<QuePosition::VECIN, BUFFER_NUM> inQueueX;
//create queue for output, in this case depth is equal to buffer num
TQue<QuePosition::VECOUT, BUFFER_NUM> outQueueY;
GlobalTensor<half> xGm;
GlobalTensor<half> yGm;
//考生补充自定义成员变量
TBuf<QuePosition::VECCALC> tmpBuffer1, tmpBuffer2, tmpBuffer3, tmpBuffer4;
uint32_t blockLength;
uint32_t tileNum;
uint32_t tileLength;
};
extern "C" __global__ __aicore__ void sinh_custom(GM_ADDR x, GM_ADDR y, GM_ADDR
workspace, GM_ADDR tiling) {
GET_TILING_DATA(tiling_data, tiling);
KernelSinh op;
//补充 init 和 process 函数调用内容
op.Init(x, y, tiling_data.totalLength, tiling_data.tileNum);
op.Process();
}