华为Ascend C算子开发（中级）考试

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

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文章目录

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

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一、op_host文件夹下的sinh_custom_tiling.h文件

#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

#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

#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();}