/**
* 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 add.asc
* \brief
*/
#include <cstdint>
#include <iostream>
#include <vector>
#include <algorithm>
#include <iterator>
#include "acl/acl.h"
#include "kernel_operator.h"
constexpr uint32_t BUFFER_NUM = 2;
constexpr uint32_t TILE_NUM = 8;
struct AddCustomTilingData {
uint32_t totalLength;
uint32_t tileNum;
};
class KernelAdd {
public:
__aicore__ inline KernelAdd() {}
__aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, uint32_t totalLength, uint32_t tileNum)
{
const uint32_t blockNum = AscendC::GetBlockNum();
ascendc_assert(blockNum != 0 && "block dim can not be zero!");
this->blockLength = totalLength / blockNum;
this->tileNum = tileNum;
ascendc_assert(this->tileNum != 0 && "tile num can not be zero!");
this->tileLength = this->blockLength / this->tileNum / BUFFER_NUM;
ascendc_assert(this->tileLength != 0 && "tile length can not be zero!");
xGm.SetGlobalBuffer((__gm__ float *)x + this->blockLength * AscendC::GetBlockIdx(), this->blockLength);
yGm.SetGlobalBuffer((__gm__ float *)y + this->blockLength * AscendC::GetBlockIdx(), this->blockLength);
zGm.SetGlobalBuffer((__gm__ float *)z + this->blockLength * AscendC::GetBlockIdx(), this->blockLength);
pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(float));
pipe.InitBuffer(inQueueY, BUFFER_NUM, this->tileLength * sizeof(float));
pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(float));
}
__aicore__ inline void Process()
{
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)
{
AscendC::LocalTensor<float> xLocal = inQueueX.AllocTensor<float>();
AscendC::LocalTensor<float> yLocal = inQueueY.AllocTensor<float>();
AscendC::DataCopy(xLocal, xGm[progress * this->tileLength], this->tileLength);
AscendC::DataCopy(yLocal, yGm[progress * this->tileLength], this->tileLength);
inQueueX.EnQue(xLocal);
inQueueY.EnQue(yLocal);
}
__aicore__ inline void Compute(int32_t progress)
{
AscendC::LocalTensor<float> xLocal = inQueueX.DeQue<float>();
AscendC::LocalTensor<float> yLocal = inQueueY.DeQue<float>();
AscendC::LocalTensor<float> zLocal = outQueueZ.AllocTensor<float>();
AscendC::Add(zLocal, xLocal, yLocal, this->tileLength);
outQueueZ.EnQue<float>(zLocal);
inQueueX.FreeTensor(xLocal);
inQueueY.FreeTensor(yLocal);
// DumpTensor show input/output info
AscendC::DumpTensor(xLocal[64], 0, 16);
AscendC::DumpTensor(yLocal[64], 1, 16);
AscendC::DumpTensor(zLocal[64], 2, 16);
if (progress == 0) {
// PrintTimeStamp
AscendC::PrintTimeStamp(65577);
// printf int
AscendC::printf("fmt string int: %d\n", 0x123);
AscendC::PRINTF("fmt string int: %d\n", 0x123);
// printf float
float a = 3.14;
AscendC::printf("fmt string float: %f\n", a);
AscendC::PRINTF("fmt string float: %f\n", a);
}
}
__aicore__ inline void CopyOut(int32_t progress)
{
AscendC::LocalTensor<float> zLocal = outQueueZ.DeQue<float>();
AscendC::DataCopy(zGm[progress * this->tileLength], zLocal, this->tileLength);
outQueueZ.FreeTensor(zLocal);
}
private:
AscendC::TPipe pipe;
AscendC::TQue<AscendC::TPosition::VECIN, BUFFER_NUM> inQueueX, inQueueY;
AscendC::TQue<AscendC::TPosition::VECOUT, BUFFER_NUM> outQueueZ;
AscendC::GlobalTensor<float> xGm;
AscendC::GlobalTensor<float> yGm;
AscendC::GlobalTensor<float> zGm;
uint32_t blockLength = 0;
uint32_t tileNum = 0;
uint32_t tileLength = 0;
};
__global__ __vector__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling)
{
KernelAdd op;
op.Init(x, y, z, tiling.totalLength, tiling.tileNum);
op.Process();
}
std::vector<float> kernel_add(std::vector<float> &x, std::vector<float> &y)
{
constexpr uint32_t numBlocks = 8;
uint32_t totalLength = x.size();
size_t totalByteSize = totalLength * sizeof(float);
int32_t deviceId = 0;
aclrtStream stream = nullptr;
AddCustomTilingData tiling = {totalLength, TILE_NUM};
uint8_t *xHost = reinterpret_cast<uint8_t *>(x.data());
uint8_t *yHost = reinterpret_cast<uint8_t *>(y.data());
uint8_t *zHost = nullptr;
uint8_t *xDevice = nullptr;
uint8_t *yDevice = nullptr;
uint8_t *zDevice = nullptr;
aclInit("../acl.json");
aclrtSetDevice(deviceId);
aclrtCreateStream(&stream);
aclrtMallocHost((void **)(&zHost), totalByteSize);
aclrtMalloc((void **)&xDevice, totalByteSize, ACL_MEM_MALLOC_HUGE_FIRST);
aclrtMalloc((void **)&yDevice, totalByteSize, ACL_MEM_MALLOC_HUGE_FIRST);
aclrtMalloc((void **)&zDevice, totalByteSize, ACL_MEM_MALLOC_HUGE_FIRST);
aclrtMemcpy(xDevice, totalByteSize, xHost, totalByteSize, ACL_MEMCPY_HOST_TO_DEVICE);
aclrtMemcpy(yDevice, totalByteSize, yHost, totalByteSize, ACL_MEMCPY_HOST_TO_DEVICE);
add_custom<<<numBlocks, nullptr, stream>>>(xDevice, yDevice, zDevice, tiling);
aclrtSynchronizeStream(stream);
aclrtMemcpy(zHost, totalByteSize, zDevice, totalByteSize, ACL_MEMCPY_DEVICE_TO_HOST);
std::vector<float> z((float *)zHost, (float *)(zHost + totalLength));
aclrtFree(xDevice);
aclrtFree(yDevice);
aclrtFree(zDevice);
aclrtFreeHost(zHost);
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return z;
}
uint32_t VerifyResult(std::vector<float> &output, std::vector<float> &golden)
{
auto printTensor = [](std::vector<float> &tensor, const char *name) {
constexpr size_t maxPrintSize = 20;
std::cout << name << ": ";
std::copy(tensor.begin(), tensor.begin() + std::min(tensor.size(), maxPrintSize),
std::ostream_iterator<float>(std::cout, " "));
if (tensor.size() > maxPrintSize) {
std::cout << "...";
}
std::cout << std::endl;
};
printTensor(output, "Output");
printTensor(golden, "Golden");
if (std::equal(output.begin(), output.end(), golden.begin())) {
std::cout << "[Success] Case accuracy is verification passed." << std::endl;
return 0;
}
std::cout << "[Failed] Case accuracy is verification failed!" << std::endl;
return 1;
}
int32_t main(int32_t argc, char *argv[])
{
constexpr uint32_t totalLength = 8 * 2048;
constexpr float valueX = 1.2f;
constexpr float valueY = 2.3f;
std::vector<float> x(totalLength, valueX);
std::vector<float> y(totalLength, valueY);
std::vector<float> output = kernel_add(x, y);
std::vector<float> golden(totalLength, valueX + valueY);
return VerifyResult(output, golden);
}