diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/add_custom.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/add_custom.cpp deleted file mode 100644 index 78a6ca0016e450c96ba40336720a19aca42e2e5a..0000000000000000000000000000000000000000 --- a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/add_custom.cpp +++ /dev/null @@ -1,213 +0,0 @@ -/** - * @file add_custom.cpp - * - * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. - */ -#include "add_custom_tiling.h" -#include "kernel_operator.h" - -constexpr int32_t BUFFER_NUM = 2; // tensor num for each queue - -constexpr uint32_t ADD_BFLOAT16 = 0; -constexpr uint32_t ADD_FLOAT16 = 1; -constexpr uint32_t ADD_FLOAT32 = 2; -constexpr uint32_t ADD_INT8 = 3; -constexpr uint32_t ADD_INT16 = 4; -constexpr uint32_t ADD_INT32 = 5; - -template class KernelAdd { -public: - __aicore__ inline KernelAdd() {} - __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) - { - this->xLength = tiling.xLength; - this->yLength = tiling.yLength; - if (tiling.isEvenCore) { - this->blockLength = tiling.blockLength; - this->tileNum = tiling.tileNum; - this->tileLength = tiling.tileLength / BUFFER_NUM; - this->lastTileLength = tiling.lastTileLength; - - xGm.SetGlobalBuffer((__gm__ dataType *)x + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); - yGm.SetGlobalBuffer((__gm__ dataType *)y + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); - zGm.SetGlobalBuffer((__gm__ dataType *)z + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); - } else { - this->formerNum = tiling.formerNum; - this->formerLength = tiling.formerLength; - this->formerTileNum = tiling.formerTileNum; - this->formerTileLength = tiling.formerTileLength; - this->formerLastTileLength = tiling.formerLastTileLength; - - this->tailNum = tiling.tailNum; - this->tailLength = tiling.tailLength; - this->tailTileNum = tiling.tailTileNum; - this->tailTileLength = tiling.tailTileLength; - this->tailLastTileLength = tiling.tailLastTileLength; - if (AscendC::GetBlockIdx() < this->formerNum) { - this->tileNum = this->formerTileNum; - this->tileLength = this->formerTileLength / BUFFER_NUM; - this->lastTileLength = this->formerLastTileLength; - - xGm.SetGlobalBuffer((__gm__ dataType *)x + this->formerLength * AscendC::GetBlockIdx(), this->formerLength); - yGm.SetGlobalBuffer((__gm__ dataType *)y + this->formerLength * AscendC::GetBlockIdx(), this->formerLength); - zGm.SetGlobalBuffer((__gm__ dataType *)z + this->formerLength * AscendC::GetBlockIdx(), this->formerLength); - } else { - this->tileNum = this->tailTileNum * BUFFER_NUM; - this->tileLength = this->tailTileLength / BUFFER_NUM; - this->lastTileLength = tailLastTileLength; - - xGm.SetGlobalBuffer((__gm__ dataType *)x + this->formerLength * this->formerNum + - this->tailLength * (AscendC::GetBlockIdx() - this->formerNum), this->tailLength); - yGm.SetGlobalBuffer((__gm__ dataType *)y + this->formerLength * this->formerNum + - this->tailLength * (AscendC::GetBlockIdx() - this->formerNum), this->tailLength); - zGm.SetGlobalBuffer((__gm__ dataType *)z + this->formerLength * this->formerNum + - this->tailLength * (AscendC::GetBlockIdx() - this->formerNum), this->tailLength); - } - } - pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(dataType)); - pipe.InitBuffer(inQueueY, BUFFER_NUM, this->tileLength * sizeof(dataType)); - pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(dataType)); - - if constexpr (AscendC::IsSameType::value) { - pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(float)); - pipe.InitBuffer(tmpBuf1, this->tileLength * sizeof(float)); - } else if constexpr (AscendC::IsSameType::value) { - pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(half)); - pipe.InitBuffer(tmpBuf1, this->tileLength * sizeof(half)); - } - } - __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 xLocal = inQueueX.AllocTensor(); - AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); - if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { - AscendC::DataCopy(xLocal, xGm[(progress - 2) * this->tileLength + this->lastTileLength], - this->tileLength); - AscendC::DataCopy(yLocal, yGm[(progress - 2) * this->tileLength + this->lastTileLength], - this->tileLength); - } else { - 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 xLocal = inQueueX.DeQue(); - AscendC::LocalTensor yLocal = inQueueY.DeQue(); - AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); - - if constexpr (AscendC::IsSameType::value) { - AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); - AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); - - AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); - AscendC::Cast(tmpTensor1, yLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); - - AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); - AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_RINT, this->tileLength); - } else if constexpr (AscendC::IsSameType::value) { - AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); - AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); - - AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); - AscendC::Cast(tmpTensor1, yLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); - - AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); - AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_NONE, this->tileLength); - } else { - AscendC::Add(zLocal, xLocal, yLocal, this->tileLength); - } - - outQueueZ.EnQue(zLocal); - inQueueX.FreeTensor(xLocal); - inQueueY.FreeTensor(yLocal); - - } - __aicore__ inline void CopyOut(int32_t progress) - { - AscendC::LocalTensor zLocal = outQueueZ.DeQue(); - if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { - AscendC::DataCopy(zGm[(progress - 2) * this->tileLength + this->lastTileLength], zLocal, - this->tileLength); - } else { - AscendC::DataCopy(zGm[progress * this->tileLength], zLocal, this->tileLength); - } - outQueueZ.FreeTensor(zLocal); - } - -private: - AscendC::TPipe pipe; - AscendC::TQue inQueueX, inQueueY; - AscendC::TQue outQueueZ; - AscendC::TBuf tmpBuf0, tmpBuf1; - - AscendC::GlobalTensor xGm, yGm, zGm; - - uint32_t xLength; - uint32_t yLength; - - uint32_t blockLength; - uint32_t tileNum; - uint32_t tileLength; - uint32_t lastTileLength; - - uint32_t formerNum; - uint32_t formerLength; - uint32_t formerTileNum; - uint32_t formerTileLength; - uint32_t formerLastTileLength; - - uint32_t tailNum; - uint32_t tailLength; - uint32_t tailTileNum; - uint32_t tailTileLength; - uint32_t tailLastTileLength; -}; - -extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) -{ - if (tiling.dataType == ADD_BFLOAT16) { - KernelAdd op; - op.Init(x, y, z, tiling); - op.Process(); - } else if (tiling.dataType == ADD_FLOAT16) { - KernelAdd op; - op.Init(x, y, z, tiling); - op.Process(); - } else if (tiling.dataType == ADD_FLOAT32) { - KernelAdd op; - op.Init(x, y, z, tiling); - op.Process(); - } else if (tiling.dataType == ADD_INT8) { - KernelAdd op; - op.Init(x, y, z, tiling); - op.Process(); - } else if (tiling.dataType == ADD_INT16) { - KernelAdd op; - op.Init(x, y, z, tiling); - op.Process(); - } else if (tiling.dataType == ADD_INT32) { - KernelAdd op; - op.Init(x, y, z, tiling); - op.Process(); - } else { - return; - } -} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/README.md b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/README.md index c9e7f6771470e657adccb3191719a0bedacc0fc3..bda5a062601ebb31f1e05f760a139e4786f83927 100644 --- a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/README.md +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/README.md @@ -1,10 +1,100 @@ ## 概述 -本样例介绍Add算子的核函数直调方法。 +本样例介绍三个不同的Add自定义算子，场景分别如下： + +- [基础Add算子](./VectorAddSingleCore)：支持的数据类型有：half，算子支持单核运行。 +- [使用临时内存Add算子](./VectorAddSingleCoreWithTmpbuf)：支持的数据类型有：bfloat16_t，算子支持单核运行，算子内部使用TmpBuf。 +- [多核Add算子](./VectorAddMultiCoreWithTiling)：支持的数据类型有：bfloat16_t/int8_t/float/half/int16_t/int32_t，算子支持多核运行、支持核间数据均分或不均分场景并且支持尾块处理。 +- [输入Broadcast的Add算子](./VectorAddMultiCoreWithTilingBroadcast)：两个输入shape不相等，算子对其中一个输入进行Broadcast后再进行计算。支持的数据类型有：bfloat16_t/int8_t/float/half/int16_t/int32_t，算子支持多核运行、支持核间数据均分或不均分场景并且支持尾块处理。 ## 目录结构介绍 ``` -├── KernelLaunch // 使用核函数直调的方式调用Add自定义算子 -│ ├── AddKernelInvocationTilingNeo // Kernel Launch方式调用核函数样例，带有Tiling +├── 21_vectoradd_kernellaunch // 使用核函数直调的方式调用Add自定义算子 +│ ├── VectorAddSingleCore // Kernel Launch方式调用核函数样例 +│ ├── VectorAddSingleCoreWithTmpbuf // Kernel Launch方式调用核函数样例，带有TmpBuffer +│ ├── VectorAddMultiCoreWithTiling // Kernel Launch方式调用核函数样例，带有多核&tiling切分 +│ └── VectorAddMultiCoreWithTilingBroadcast // Kernel Launch方式调用核函数样例，多核&tiling场景下增加输入Broadcast +``` + +## 算子描述 +Add算子实现了两个数据相加，返回相加结果的功能。对应的数学表达式为： +``` +z = x + y ``` +## 算子规格描述 +- VectorAddSingleCore + + + + + + + + + + + +
算子类型(OpType)Add
算子输入nameshapedata typeformat
x1 * 2048halfND
y1 * 2048halfND
算子输出z1 * 2048halfND
核函数名add_custom
+ +- VectorAddSingleCoreWithTmpbuf + + + + + + + + + + + +
算子类型(OpType)Add
算子输入nameshapedata typeformat
x1 * 2048bfloat16_tND
y1 * 2048bfloat16_tND
算子输出z1 * 2048bfloat16_tND
核函数名add_custom
+ +- VectorAddMultiCoreWithTiling + + + + + + + + + + + +
算子类型(OpType)Add
算子输入nameshapedata typeformat
x-bfloat16_t/int8_t/float/half/int16_t/int32_tND
y-bfloat16_t/int8_t/float/half/int16_t/int32_tND
算子输出z-bfloat16_t/int8_t/float/half/int16_t/int32_tND
核函数名add_custom
+ +- VectorAddMultiCoreWithTilingBroadcast + + + + + + + + + + + +
算子类型(OpType)Add
算子输入nameshapedata typeformat
x(m, n) / (1, n) / (m, 1)bfloat16_t/int8_t/float/half/int16_t/int32_tND
y(m, n) / (1, n) / (m, 1)bfloat16_t/int8_t/float/half/int16_t/int32_tND
算子输出z(m * n))bfloat16_t/int8_t/float/half/int16_t/int32_tND
核函数名add_custom
+ + +该算子支持对任一输入的某个轴进行广播，对应关系如下 + +- 针对axis = 0（第一个轴）进行广播 + - x(m, n), y(1, n) + - x(1, n), y(m, n) + + 注意，该场景下m需满足32字节对齐。 + +- 针对axis = 1（第二个轴）进行广播 + - x(m, n), y(m, 1) + - x(m, 1), y(m, n) + + + +## 支持的产品型号 +本样例支持如下产品型号： +- Atlas A2训练系列产品/Atlas 800I A2推理产品 + ## 编译运行样例算子 针对自定义算子工程，编译运行包含如下步骤： - 编译自定义算子工程； @@ -14,5 +104,7 @@ ### 1. 获取源码包 编译运行此样例前，请参考[准备：获取样例代码](../README.md#codeready)获取源码包。 ### 2. 编译运行样例工程 -- [AddKernelInvocationTilingNeo样例运行](./AddKernelInvocationTilingNeo/README.md) - +- [VectorAddSingleCore样例运行](./VectorAddSingleCore/README.md) +- [VectorAddSingleCoreWithTmpbuf样例运行](./VectorAddSingleCoreWithTmpbuf/README.md) +- [VectorAddMultiCoreWithTiling样例运行](./VectorAddMultiCoreWithTiling/README.md) +- [VectorAddMultiCoreWithTilingBroadcast样例运行](./VectorAddMultiCoreWithTilingBroadcast/README.md) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/CMakeLists.txt b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..dc32860d9a11b83813c1aa11687c3006b869623c --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/CMakeLists.txt @@ -0,0 +1,46 @@ +cmake_minimum_required(VERSION 3.16) +project(Ascend_c) + +set(RUN_MODE "npu" CACHE STRING "cpu/sim/npu") +set(SOC_VERSION "Ascend310P3" CACHE STRING "system on chip type") +set(ASCEND_CANN_PACKAGE_PATH "/usr/local/Ascend/ascend-toolkit/latest" + CACHE STRING "ASCEND CANN package installation directory" +) +if(NOT CMAKE_BUILD_TYPE) + set(CMAKE_BUILD_TYPE "Debug" CACHE STRING "Build type Release/Debug (default Debug)" FORCE) +endif() +if(CMAKE_INSTALL_PREFIX STREQUAL /usr/local) + set(CMAKE_INSTALL_PREFIX "${CMAKE_CURRENT_LIST_DIR}/out" CACHE STRING "path for install()" FORCE) +endif() + +# ${KERNEL_FILES} are used to compile library, push files written by ascendc in ${KERNEL_FILES}. +# ref to cmake/npu.cmake ascendc_library, cmake/cpu.cmake add_library +file(GLOB KERNEL_FILES ${CMAKE_CURRENT_SOURCE_DIR}/add_custom.cpp) + +if("${RUN_MODE}" STREQUAL "cpu") + include(cmake/cpu_lib.cmake) +elseif("${RUN_MODE}" STREQUAL "sim" OR "${RUN_MODE}" STREQUAL "npu") + include(cmake/npu_lib.cmake) +else() + message("invalid RUN_MODE: ${RUN_MODE}") +endif() +add_executable(ascendc_kernels_bbit + ${CMAKE_CURRENT_SOURCE_DIR}/main.cpp + ${CMAKE_CURRENT_SOURCE_DIR}/add_custom_tiling.cpp) + +target_compile_options(ascendc_kernels_bbit PRIVATE + $:-g>> + -O2 -std=c++17 -D_GLIBCXX_USE_CXX11_ABI=0 -Wall -Werror +) + +target_link_libraries(ascendc_kernels_bbit PRIVATE + $,$>:host_intf_pub>> + $:ascendcl>> + ascendc_kernels_${RUN_MODE} +) + +install(TARGETS ascendc_kernels_bbit + LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR} + ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR} + RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR} +) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/README.md b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d27f695877401085b9665a49ec0cd93a7f9c3479 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/README.md @@ -0,0 +1,82 @@ +## 目录结构介绍 +``` +├── VectorAddMultiCoreWithTiling +│ ├── cmake // 编译工程文件 +│ ├── scripts +│ │ ├── gen_data.py // 输入数据和真值数据生成脚本 +│ │ └── verify_result.py // 验证输出数据和真值数据是否一致的验证脚本 +│ ├── add_custom_tiling.h // 算子tiling结构体 +│ ├── add_custom_tiling.cpp // 算子tiling实现 +│ ├── add_custom.cpp // 算子kernel实现 +│ ├── CMakeLists.txt // 编译工程文件 +│ ├── data_utils.h // 数据读入写出函数 +│ ├── main.cpp // 主函数，调用算子的应用程序，含CPU域及NPU域调用 +│ └── run.sh // 编译运行算子的脚本 +``` +## 代码实现介绍 +- kernel实现 + Add算子的数学表达式为： + ``` + z = x + y + ``` + 计算逻辑是：Ascend C提供的矢量计算接口的操作元素都为LocalTensor，输入数据需要先计算出不同核上计算的数据相对首地址的偏移并搬运进片上存储。如果涉及到Add算子不支持的数据类型，则需要申请额外的tmpBufeer，并在计算前使用Cast算子进行类型转换，然后使用计算接口完成两个输入参数相加，得到最终结果，再搬出到外部存储上。 + + Add算子的实现流程分为3个基本任务：CopyIn，Compute，CopyOut。CopyIn任务负责将Global Memory上的输入Tensor xGm和yGm搬运到Local Memory，分别存储在xLocal、yLocal，Compute任务负责对xLocal、yLocal执行加法操作，计算结果存储在zLocal中，CopyOut任务负责将输出数据从zLocal搬运至Global Memory上的输出Tensor zGm中。 + + 具体请参考[add_custom.cpp](./add_custom.cpp)。 +- tiling实现 + - TilingData参数设计，TilingData参数本质上是和并行数据切分相关的参数。 + + 本样例尝试将输入数据均分在给定数目的核上计算，如不能均分，则计算整核和尾核的个数，整核和尾核分别处理不同数据量的数据。定义UB_BLOCK_NUM最为最大可用的UB数据块，对应UB的大小为UB_BLOCK_NUM * 32 Bytes。 并以UB_BLOCK_NUM为粒度进行tiling切分。算子中使用了17个tiling参数： + - totalLength、dataType为输入数据的总长度和数据类型； + - blockLength、tileNum、 tileLength、lastTileLength为核均分场景下每个核上的计算量、tiling切分个数以及整块和尾块长度； + - former(tail)Num、former(tail)Length、former(tail)TileNum、former(tail)TileLength、former(tail)LastTileLength为核不均分的场景下整核和尾核相关的切分数据，与核均分场景下对应； + - isEvenCore用来判断当前是否为核均分场景。 + + 具体请参考[add_custom_tiling.cpp](./add_custom_tiling.cpp)。 +- 调用实现 + 1. CPU侧运行验证主要通过ICPU_RUN_KF CPU调测宏等CPU调测库提供的接口来完成； + 2. NPU侧运行验证主要通过使用ACLRT_LAUNCH_KERNEL内核调用宏来完成。 + + 应用程序通过ASCENDC_CPU_DEBUG 宏区分代码逻辑运行于CPU侧还是NPU侧。 + +## 运行样例算子 + - 打开样例目录 + 以命令行方式下载样例代码，master分支为例。 + ```bash + cd ${git_clone_path}/samples/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/ + ``` + - 配置环境变量 + + 请根据当前环境上CANN开发套件包的[安装方式](https://hiascend.com/document/redirect/CannCommunityInstSoftware)，选择对应配置环境变量的命令。 + - 默认路径，root用户安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=/usr/local/Ascend/ascend-toolkit/latest + ``` + - 默认路径，非root用户安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=$HOME/Ascend/ascend-toolkit/latest + ``` + - 指定路径install_path，安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=${install_path}/ascend-toolkit/latest + ``` + + 配置仿真模式日志文件目录，默认为sim_log。 + ```bash + export CAMODEL_LOG_PATH=./sim_log + ``` + + - 样例执行 + + ```bash + bash run.sh -r [RUN_MODE] -v [SOC_VERSION] + ``` + - RUN_MODE：编译方式，可选择CPU调试，NPU仿真，NPU上板。支持参数为[cpu / sim / npu]，默认值为npu。 + - SOC_VERSION：昇腾AI处理器型号，如果无法确定具体的[SOC_VERSION]，则在安装昇腾AI处理器的服务器执行npu-smi info命令进行查询，在查询到的“Name”前增加Ascend信息，例如“Name”对应取值为xxxyy，实际配置的[SOC_VERSION]值为Ascendxxxyy。支持以下产品型号： + - Atlas A2训练系列产品/Atlas 800I A2推理产品 + + 示例如下，Ascendxxxyy请替换为实际的AI处理器型号。 + ```bash + bash run.sh -r cpu -v Ascendxxxyy + ``` \ No newline at end of file diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom.cpp new file mode 100644 index 0000000000000000000000000000000000000000..8e9dc83f0737f3251aa1d5a9e53849acef4d7f34 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom.cpp @@ -0,0 +1,399 @@ +/** + * @file add_custom.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include "add_custom_tiling.h" +#include "kernel_operator.h" + +constexpr int32_t BUFFER_NUM = 2; // tensor num for each queue + +constexpr uint32_t ADD_BFLOAT16 = 0; +constexpr uint32_t ADD_FLOAT16 = 1; +constexpr uint32_t ADD_FLOAT32 = 2; +constexpr uint32_t ADD_INT8 = 3; +constexpr uint32_t ADD_INT16 = 4; +constexpr uint32_t ADD_INT32 = 5; + +constexpr uint32_t LAST_TWO_TILE = 2; + +template class KernelAdd; +template <> class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + if (tiling.isEvenCore) { + this->blockLength = tiling.blockLength; + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)x + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)y + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)x + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)y + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)x + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)y + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(bfloat16_t)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->tileLength * sizeof(bfloat16_t)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(bfloat16_t)); + + pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(float)); + pipe.InitBuffer(tmpBuf1, 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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopy(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + this->tileLength); + AscendC::DataCopy(yLocal, yGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + this->tileLength); + } else { + 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 xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); + AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); + + AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + AscendC::Cast(tmpTensor1, yLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + + AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); + AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_RINT, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopy(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, + this->tileLength); + } else { + AscendC::DataCopy(zGm[progress * this->tileLength], zLocal, this->tileLength); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + AscendC::TBuf tmpBuf0; + AscendC::TBuf tmpBuf1; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t blockLength; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +template <> class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + if (tiling.isEvenCore) { + this->blockLength = tiling.blockLength; + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)x + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)y + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)x + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)y + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)x + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)y + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(int8_t)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->tileLength * sizeof(int8_t)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(int8_t)); + + pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(half)); + pipe.InitBuffer(tmpBuf1, this->tileLength * sizeof(half)); + } + __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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopy(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + this->tileLength); + AscendC::DataCopy(yLocal, yGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + this->tileLength); + } else { + 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 xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); + AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); + + AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + AscendC::Cast(tmpTensor1, yLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + + AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); + AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_NONE, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopy(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, + this->tileLength); + } else { + AscendC::DataCopy(zGm[progress * this->tileLength], zLocal, this->tileLength); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + AscendC::TBuf tmpBuf0; + AscendC::TBuf tmpBuf1; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t blockLength; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +template class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + if (tiling.isEvenCore) { + this->blockLength = tiling.blockLength; + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)x + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + yGm.SetGlobalBuffer((__gm__ dataType *)y + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + zGm.SetGlobalBuffer((__gm__ dataType *)z + this->blockLength * AscendC::GetBlockIdx(), this->blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)x + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ dataType *)y + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)x + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ dataType *)y + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(dataType)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->tileLength * sizeof(dataType)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(dataType)); + } + __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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopy(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + this->tileLength); + AscendC::DataCopy(yLocal, yGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + this->tileLength); + } else { + 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 xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::Add(zLocal, xLocal, yLocal, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopy(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, + this->tileLength); + } else { + AscendC::DataCopy(zGm[progress * this->tileLength], zLocal, this->tileLength); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t blockLength; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) +{ + if (tiling.dataType == ADD_BFLOAT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_FLOAT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_FLOAT32) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT8) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT32) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else { + return; + } +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom_tiling.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom_tiling.cpp new file mode 100644 index 0000000000000000000000000000000000000000..cfb838a6736daf78a0695e4767e4de1ac79b2a13 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom_tiling.cpp @@ -0,0 +1,112 @@ +/** + * @file add_custom_tiling.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include +#include +#include "add_custom_tiling.h" + +// bfloat16, float16, float, int8, int16, int32 +constexpr uint32_t DATA_TYPE_SIZE[] = {2, 2, 4, 1, 2, 4}; +constexpr uint32_t BLOCK_SIZE = 32; +constexpr uint32_t BUFFER_NUM = 2; +constexpr uint32_t UB_BLOCK_NUM = 21; // UB最大可以使用的block数量 +constexpr uint32_t MAX_AVAILABLE_UB_BLOCK_NUM = UB_BLOCK_NUM / BUFFER_NUM * BUFFER_NUM; +constexpr uint32_t BLOCK_DIM = 9; + +// tiling参数计算函数 +void TilingParamsCalc(uint32_t length, uint32_t alignNum, + uint32_t& tileNum, uint32_t& tileLength, uint32_t& lastTileLength) +{ + assert(alignNum != 0U); + tileNum = length / (alignNum * MAX_AVAILABLE_UB_BLOCK_NUM); + if ((static_cast(length / alignNum) % MAX_AVAILABLE_UB_BLOCK_NUM == 0U) || tileNum == 0U) { + if (tileNum == 0U) { + tileNum = 1U; + } + if (length < MAX_AVAILABLE_UB_BLOCK_NUM * alignNum) { + tileLength = ((static_cast(length) / alignNum) + 1) / BUFFER_NUM * BUFFER_NUM * alignNum; + lastTileLength = tileLength; + } else { + tileLength = MAX_AVAILABLE_UB_BLOCK_NUM * alignNum; + lastTileLength = (uint32_t)(length - (tileNum - 1) * tileLength); + } + } else { + tileNum++; + tileLength = MAX_AVAILABLE_UB_BLOCK_NUM * alignNum; + lastTileLength = (uint32_t)(length - (tileNum - 1) * tileLength); + } +} + +void GenerateTilingData(uint8_t* tilingBuf) +{ + uint32_t totalLength; + uint32_t dataTypeSize; + uint32_t blockLength; + uint32_t totalLengthAligned; + + AddCustomTilingData *tiling = reinterpret_cast(tilingBuf); + totalLength = tiling->totalLength; + dataTypeSize = DATA_TYPE_SIZE[tiling->dataType]; + + uint32_t alignNum = BLOCK_SIZE / dataTypeSize; + assert(alignNum != 0U); + /** 计算使用的核数 **/ + /* 如果传入数据的长度非32B对齐, 计算对齐后的长度*/ + totalLengthAligned = (totalLength % alignNum == 0U)? + static_cast(totalLength) : + ((static_cast(totalLength) + alignNum - 1) / alignNum) * alignNum; + + /* 核间可均分场景 */ + if ((totalLengthAligned / alignNum) % BLOCK_DIM == 0U) { + uint32_t tileNum = 0; + uint32_t tileLength = 0; + uint32_t lastTileLength = 0; + blockLength = totalLengthAligned / BLOCK_DIM; + TilingParamsCalc(blockLength, alignNum, tileNum, tileLength, lastTileLength); + + tiling->blockLength = blockLength; + tiling->tileNum = tileNum; + tiling->tileLength = tileLength; + tiling->lastTileLength = lastTileLength; + tiling->isEvenCore = 1U; + } else { // 核间不可均分 + uint32_t formerNum = (totalLengthAligned / alignNum) % BLOCK_DIM; + uint32_t tailNum = BLOCK_DIM - formerNum; + // 计算整块和尾块的数据量 + uint32_t formerLength = + static_cast(((totalLengthAligned + BLOCK_DIM - 1) / BLOCK_DIM + alignNum - 1) / alignNum) * alignNum; + uint32_t tailLength = (totalLengthAligned / BLOCK_DIM / alignNum) * alignNum; + + uint32_t formerTileNum; + uint32_t formerTileLength; + uint32_t formerLastTileLength; + + uint32_t tailTileNum; + uint32_t tailTileLength; + uint32_t tailLastTileLength; + + TilingParamsCalc(formerLength, alignNum, + formerTileNum, formerTileLength, formerLastTileLength); + TilingParamsCalc(tailLength, alignNum, + tailTileNum, tailTileLength, tailLastTileLength); + + tiling->formerNum = formerNum; + tiling->formerLength = formerLength; + tiling->formerTileNum = formerTileNum; + tiling->formerTileLength = formerTileLength; + tiling->formerLastTileLength = formerLastTileLength; + + tiling->tailNum = tailNum; + tiling->tailLength = tailLength; + tiling->tailTileNum = tailTileNum; + tiling->tailTileLength = tailTileLength; + tiling->tailLastTileLength = tailLastTileLength; + tiling->isEvenCore = 0U; + } +} \ No newline at end of file diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/add_custom_tiling.h b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom_tiling.h similarity index 92% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/add_custom_tiling.h rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom_tiling.h index 4f9e259edef49abb1502c5e1cb1bef2979f50393..6293b7713c707c5c65570e0e2cb13300050a49dd 100644 --- a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/add_custom_tiling.h +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/add_custom_tiling.h @@ -12,8 +12,7 @@ #include struct AddCustomTilingData { - uint32_t xLength; - uint32_t yLength; + uint32_t totalLength; uint32_t dataType; uint32_t blockLength; @@ -25,16 +24,14 @@ struct AddCustomTilingData { uint32_t formerLength; uint32_t formerTileNum; uint32_t formerTileLength; + uint32_t formerLastTileLength; uint32_t tailNum; uint32_t tailLength; uint32_t tailTileNum; uint32_t tailTileLength; - - uint32_t formerLastTileLength; uint32_t tailLastTileLength; uint32_t isEvenCore; - uint32_t needBroadcast; }; #endif \ No newline at end of file diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/cmake/cpu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/cmake/cpu_lib.cmake similarity index 100% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/cmake/cpu_lib.cmake rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/cmake/cpu_lib.cmake diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/cmake/npu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/cmake/npu_lib.cmake similarity index 100% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/cmake/npu_lib.cmake rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/cmake/npu_lib.cmake diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/data_utils.h b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/data_utils.h similarity index 100% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/data_utils.h rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/data_utils.h diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/main.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/main.cpp similarity index 34% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/main.cpp rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/main.cpp index f855ea411e746a36ee7bac6e811db982a50ca076..3e35408b79332cc38821eb83e66ee7a3e8dd41fe 100644 --- a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/main.cpp +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/main.cpp @@ -17,47 +17,20 @@ #include "tikicpulib.h" extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling); #endif +extern void GenerateTilingData(uint8_t* tilingBuf); -// bfloat16, float16, float, int8, int16, int32 -constexpr uint32_t DataTypeSize[] = {2, 2, 4, 1, 2, 4}; -constexpr uint32_t BlockSize = 32; -constexpr uint32_t BufferNum = 2; -constexpr uint32_t UbBlockNum = 20; // UB最大可以使用的block数量 -constexpr uint32_t BlockDim = 9; -void UnevenCoreTilingCalc(uint32_t length, uint32_t alignNum, - uint32_t& tileNum, uint32_t& tileLength, uint32_t& lastTileLength) -{ - tileNum = length / alignNum / UbBlockNum; - if ((length / alignNum) % UbBlockNum == 0 || tileNum == 0) { - if (tileNum == 0) { - tileNum = 1; - } - if (length < UbBlockNum * alignNum) { - tileLength = ((length / alignNum) + 1) / BufferNum * BufferNum * alignNum; - lastTileLength = tileLength; - } else { - tileLength = UbBlockNum * alignNum; - lastTileLength = tileLength; - } - } else { - tileNum = tileNum + 1; - tileLength = UbBlockNum * alignNum; - lastTileLength = (length - (tileNum - 1) * tileLength); - } -} int32_t main(int32_t argc, char *argv[]) { - size_t tilingSize = 19 * sizeof(uint32_t); - uint32_t xLength, yLength, totalLength, tileNum, dataTypeSize, blockLength, totalLengthAligned; + constexpr uint32_t BLOCK_DIM = 9; + constexpr uint32_t DATA_TYPE_SIZE[] = {2, 2, 4, 1, 2, 4}; + uint8_t *tiling = nullptr; + size_t tilingSize = 17 * sizeof(uint32_t); + #ifdef ASCENDC_CPU_DEBUG - uint8_t *tiling = (uint8_t *)AscendC::GmAlloc(tilingSize); + tiling = (uint8_t *)AscendC::GmAlloc(tilingSize); ReadFile("./input/input_tiling.bin", tilingSize, tiling, tilingSize); - - xLength = reinterpret_cast(tiling)->xLength; - yLength = reinterpret_cast(tiling)->yLength; - dataTypeSize = DataTypeSize[reinterpret_cast(tiling)->dataType]; #else CHECK_ACL(aclInit(nullptr)); int32_t deviceId = 0; @@ -65,107 +38,16 @@ int32_t main(int32_t argc, char *argv[]) aclrtStream stream = nullptr; CHECK_ACL(aclrtCreateStream(&stream)); - AddCustomTilingData *tiling; uint8_t *xHost, *yHost, *zHost; uint8_t *xDevice, *yDevice, *zDevice; CHECK_ACL(aclrtMallocHost((void **)(&tiling), tilingSize)); ReadFile("./input/input_tiling.bin", tilingSize, tiling, tilingSize); - - xLength = tiling->xLength; - yLength = tiling->yLength; - dataTypeSize = DataTypeSize[tiling->dataType]; -#endif - totalLength = (xLength > yLength)? xLength : yLength; - - size_t inputByteSize = totalLength * dataTypeSize; - size_t outputByteSize = totalLength * dataTypeSize; - uint32_t alignNum = BlockSize / dataTypeSize; - - /** 计算使用的核数 **/ - /* 如果传入数据的长度非32B对齐, 计算对齐后的长度*/ - totalLengthAligned = (totalLength % alignNum == 0)? - totalLength : ((totalLength + alignNum - 1) / alignNum) * alignNum; - - /* 核间可均分场景 */ - if ((totalLengthAligned / alignNum) % BlockDim == 0) { - uint32_t tileLength = 0; - uint32_t lastTileLength = 0; - blockLength = totalLengthAligned / BlockDim; - tileNum = blockLength / alignNum / UbBlockNum; - - if ((blockLength / alignNum) % UbBlockNum == 0 || tileNum == 0) { //满足32字节对齐，可以核内均分 - if (tileNum == 0) { - tileNum = 1; - } - if (blockLength < UbBlockNum * alignNum) { - tileLength = ((blockLength / alignNum) + 1) / BufferNum * BufferNum * alignNum; - lastTileLength = tileLength; - } else { - tileLength = UbBlockNum * alignNum; - lastTileLength = tileLength; - } - } else { - tileNum = tileNum + 1; - tileLength = UbBlockNum * alignNum; - lastTileLength = blockLength - (tileNum - 1) * tileLength; - } - -#ifdef ASCENDC_CPU_DEBUG - reinterpret_cast(tiling)->blockLength = blockLength; - reinterpret_cast(tiling)->tileNum = tileNum; - reinterpret_cast(tiling)->tileLength = tileLength; - reinterpret_cast(tiling)->lastTileLength = lastTileLength; - reinterpret_cast(tiling)->isEvenCore = 1; -#else - tiling->blockLength = blockLength; - tiling->tileNum = tileNum; - tiling->tileLength = tileLength; - tiling->lastTileLength = lastTileLength; - tiling->isEvenCore = 1; -#endif - } else { // 核间不可均分 - uint32_t formerNum = (totalLengthAligned / alignNum) % BlockDim; - uint32_t tailNum = BlockDim - formerNum; - // 计算整块和尾块的数据量 - uint32_t formerLength = - (((totalLengthAligned + BlockDim - 1) / BlockDim + alignNum - 1) / alignNum) * alignNum; - uint32_t tailLength = (totalLengthAligned / BlockDim / alignNum) * alignNum; - - uint32_t formerTileNum, formerTileLength, formerLastTileLength; - uint32_t tailTileNum, tailTileLength, tailLastTileLength; - - UnevenCoreTilingCalc(formerLength, alignNum, formerTileNum, formerTileLength, formerLastTileLength); - UnevenCoreTilingCalc(tailLength, alignNum, tailTileNum, tailTileLength, tailLastTileLength); - -#ifdef ASCENDC_CPU_DEBUG - reinterpret_cast(tiling)->formerNum = formerNum; - reinterpret_cast(tiling)->formerLength = formerLength; - reinterpret_cast(tiling)->formerTileNum = formerTileNum; - reinterpret_cast(tiling)->formerTileLength = formerTileLength; - reinterpret_cast(tiling)->formerLastTileLength = formerLastTileLength; - - reinterpret_cast(tiling)->tailNum = tailNum; - reinterpret_cast(tiling)->tailLength = tailLength; - reinterpret_cast(tiling)->tailTileNum = tailTileNum; - reinterpret_cast(tiling)->tailTileLength = tailTileLength; - reinterpret_cast(tiling)->tailLastTileLength = tailLastTileLength; - reinterpret_cast(tiling)->isEvenCore = 0; -#else - tiling->formerNum = formerNum; - tiling->formerLength = formerLength; - tiling->formerTileNum = formerTileNum; - tiling->formerTileLength = formerTileLength; - tiling->formerLastTileLength = formerLastTileLength; - - tiling->tailNum = tailNum; - tiling->tailLength = tailLength; - tiling->tailTileNum = tailTileNum; - tiling->tailTileLength = tailTileLength; - tiling->tailLastTileLength = tailLastTileLength; - tiling->isEvenCore = 0; #endif - } + GenerateTilingData(tiling); + uint32_t dataTypeSize = DATA_TYPE_SIZE[reinterpret_cast(tiling)->dataType]; + size_t inputByteSize = reinterpret_cast(tiling)->totalLength * dataTypeSize; + size_t outputByteSize = reinterpret_cast(tiling)->totalLength * dataTypeSize; #ifdef ASCENDC_CPU_DEBUG uint8_t *x = (uint8_t *)AscendC::GmAlloc(inputByteSize); @@ -177,7 +59,7 @@ int32_t main(int32_t argc, char *argv[]) AscendC::SetKernelMode(KernelMode::AIV_MODE); - ICPU_RUN_KF(add_custom, BlockDim, x, y, z, + ICPU_RUN_KF(add_custom, BLOCK_DIM, x, y, z, *reinterpret_cast(tiling)); WriteFile("./output/output_z.bin", z, outputByteSize); @@ -200,7 +82,8 @@ int32_t main(int32_t argc, char *argv[]) CHECK_ACL(aclrtMemcpy(xDevice, inputByteSize, xHost, inputByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); CHECK_ACL(aclrtMemcpy(yDevice, inputByteSize, yHost, inputByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); - ACLRT_LAUNCH_KERNEL(add_custom)(BlockDim, stream, xDevice, yDevice, zDevice, tiling); + ACLRT_LAUNCH_KERNEL(add_custom)(BLOCK_DIM, stream, xDevice, yDevice, zDevice, + reinterpret_cast(tiling)); CHECK_ACL(aclrtSynchronizeStream(stream)); CHECK_ACL(aclrtMemcpy(zHost, outputByteSize, zDevice, outputByteSize, ACL_MEMCPY_DEVICE_TO_HOST)); diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/run.sh b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/run.sh similarity index 100% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/run.sh rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/run.sh diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/scripts/gen_data.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/scripts/gen_data.py similarity index 72% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/scripts/gen_data.py rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/scripts/gen_data.py index 6b5a307419cdc9a6915a21297886b18a6697aafe..70f6bae3098905b8465f73c4a2e000e0a7a6d9a7 100644 --- a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/scripts/gen_data.py +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/scripts/gen_data.py @@ -14,22 +14,19 @@ bfloat16 = tf.bfloat16.as_numpy_dtype dtype_emu = {bfloat16: 0, np.float16: 1, np.float32: 2, np.int8: 3, np.int16: 4, np.int32: 5} def gen_golden_data_simple(): - input_shape_x = [32, 6737] - input_shape_y = [32, 6737] + input_shape = [32, 6737] dtype = np.int8 - input_x = np.random.uniform(-50, 50, input_shape_x).astype(dtype) - input_y = np.random.uniform(-50, 50, input_shape_y).astype(dtype) + input_x = np.random.uniform(-50, 50, input_shape).astype(dtype) + input_y = np.random.uniform(-50, 50, input_shape).astype(dtype) golden = (input_x + input_y).astype(dtype) - tiling = np.array([input_shape_x[0] * input_shape_x[1], input_shape_y[0] * input_shape_y[1], - dtype_emu[dtype]], dtype=np.uint32) + tiling = np.array([input_shape[0] * input_shape[1], dtype_emu[dtype]], dtype=np.uint32) tiling.tofile("./input/input_tiling.bin") input_x.tofile("./input/input_x.bin") input_y.tofile("./input/input_y.bin") golden.tofile("./output/golden.bin") - if __name__ == "__main__": gen_golden_data_simple() diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/scripts/verify_result.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/scripts/verify_result.py similarity index 87% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/scripts/verify_result.py rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/scripts/verify_result.py index aac4ba3107791b6c7fbef4b911f51af5149a7000..277d94780190059a76b88caa2347da11d4b14c67 100644 --- a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/scripts/verify_result.py +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTiling/scripts/verify_result.py @@ -17,11 +17,14 @@ bfloat16 = tf.bfloat16.as_numpy_dtype relative_tol = 1e-3 absolute_tol = 1e-5 error_tol = 1e-3 - +data_type = np.int8 def verify_result(output, golden): - output = np.fromfile(output, dtype=np.int8).reshape(-1) - golden = np.fromfile(golden, dtype=np.int8).reshape(-1) + output = np.fromfile(output, dtype=data_type).reshape(-1) + golden = np.fromfile(golden, dtype=data_type).reshape(-1) + if data_type == bfloat16: + output = output.astype(np.float32) + golden = golden.astype(np.float32) different_element_results = np.isclose(output, golden, rtol=relative_tol, diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/CMakeLists.txt b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..dc32860d9a11b83813c1aa11687c3006b869623c --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/CMakeLists.txt @@ -0,0 +1,46 @@ +cmake_minimum_required(VERSION 3.16) +project(Ascend_c) + +set(RUN_MODE "npu" CACHE STRING "cpu/sim/npu") +set(SOC_VERSION "Ascend310P3" CACHE STRING "system on chip type") +set(ASCEND_CANN_PACKAGE_PATH "/usr/local/Ascend/ascend-toolkit/latest" + CACHE STRING "ASCEND CANN package installation directory" +) +if(NOT CMAKE_BUILD_TYPE) + set(CMAKE_BUILD_TYPE "Debug" CACHE STRING "Build type Release/Debug (default Debug)" FORCE) +endif() +if(CMAKE_INSTALL_PREFIX STREQUAL /usr/local) + set(CMAKE_INSTALL_PREFIX "${CMAKE_CURRENT_LIST_DIR}/out" CACHE STRING "path for install()" FORCE) +endif() + +# ${KERNEL_FILES} are used to compile library, push files written by ascendc in ${KERNEL_FILES}. +# ref to cmake/npu.cmake ascendc_library, cmake/cpu.cmake add_library +file(GLOB KERNEL_FILES ${CMAKE_CURRENT_SOURCE_DIR}/add_custom.cpp) + +if("${RUN_MODE}" STREQUAL "cpu") + include(cmake/cpu_lib.cmake) +elseif("${RUN_MODE}" STREQUAL "sim" OR "${RUN_MODE}" STREQUAL "npu") + include(cmake/npu_lib.cmake) +else() + message("invalid RUN_MODE: ${RUN_MODE}") +endif() +add_executable(ascendc_kernels_bbit + ${CMAKE_CURRENT_SOURCE_DIR}/main.cpp + ${CMAKE_CURRENT_SOURCE_DIR}/add_custom_tiling.cpp) + +target_compile_options(ascendc_kernels_bbit PRIVATE + $:-g>> + -O2 -std=c++17 -D_GLIBCXX_USE_CXX11_ABI=0 -Wall -Werror +) + +target_link_libraries(ascendc_kernels_bbit PRIVATE + $,$>:host_intf_pub>> + $:ascendcl>> + ascendc_kernels_${RUN_MODE} +) + +install(TARGETS ascendc_kernels_bbit + LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR} + ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR} + RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR} +) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/README.md b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/README.md new file mode 100644 index 0000000000000000000000000000000000000000..75bf30d10dc6744e885451c3e0e4f5d55534e9b9 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/README.md @@ -0,0 +1,83 @@ +## 目录结构介绍 +``` +├── VectorAddMultiCoreWithTilingBroadcast +│ ├── cmake // 编译工程文件 +│ ├── scripts +│ │ ├── gen_data.py // 输入数据和真值数据生成脚本 +│ │ └── verify_result.py // 验证输出数据和真值数据是否一致的验证脚本 +│ ├── add_custom_tiling.h // 算子tiling结构体 +│ ├── add_custom_tiling.cpp // 算子tiling实现 +│ ├── add_custom.cpp // 算子kernel实现 +│ ├── CMakeLists.txt // 编译工程文件 +│ ├── data_utils.h // 数据读入写出函数 +│ ├── main.cpp // 主函数，调用算子的应用程序，含CPU域及NPU域调用 +│ └── run.sh // 编译运行算子的脚本 +``` +## 代码实现介绍 +- kernel实现 + Add算子的数学表达式为： + ``` + z = x + y + ``` + 计算逻辑是：Ascend C提供的矢量计算接口的操作元素都为LocalTensor，输入数据需要先搬运进片上存储，然后使用计算接口完成两个输入参数相加，得到最终结果，再搬出到外部存储上。 + + Add算子的实现流程分为3个基本任务：CopyIn，Compute，CopyOut。 + - CopyIn任务负责将Global Memory上的输入Tensor xGm和yGm搬运到Local Memory，分别存储在xLocal、yLocal； + - Compute任务负责对xLocal、yLocal进行Broadcast并存入临时内存，之后执行加法操作，计算结果存储在zLocal中； + - CopyOut任务负责将输出数据从zLocal搬运至Global Memory上的输出Tensor zGm中。具体请参考[add_custom.cpp](./add_custom.cpp)。 +- tiling实现 + - TilingData参数设计，TilingData参数本质上是和并行数据切分相关的参数。 + + 本样例尝试将输入数据均分在给定数目的核上计算，如不能均分，则计算整核和尾核的个数，整核和尾核分别处理不同数据量的数据。定义UB_BLOCK_NUM最为最大可用的UB数据块，对应UB的大小为UB_BLOCK_NUM * 32 Bytes。 并以UB_BLOCK_NUM为粒度进行tiling切分。 + + 本示例算子使用了20个tiling参数： xLen、yLen、dataType为x, y输入数据的总长度和数据类型；coef为需要Broadcast的输入扩维的倍数；axis为输入数据Broadcast的轴；blockLength、tileNum、 tileLength、lastTileLength为核均分场景下每个核上的计算量、tiling切分个数以及整块和尾块长度；former(tail)Num、former(tail)Length、former(tail)TileNum、former(tail)TileLength、former(tail)LastTileLength为核不均分的场景下整核和尾核相关的切分数据，与核均分场景下对应；isEvenCore用来判断当前是否为核均分场景。 + + 具体请参考[add_custom_tiling.cpp](./add_custom_tiling.cpp)。 + + +- 调用实现 + 1. CPU侧运行验证主要通过ICPU_RUN_KF CPU调测宏等CPU调测库提供的接口来完成； + 2. NPU侧运行验证主要通过使用ACLRT_LAUNCH_KERNEL内核调用宏来完成。 + + 应用程序通过ASCENDC_CPU_DEBUG 宏区分代码逻辑运行于CPU侧还是NPU侧。 + +## 运行样例算子 + - 打开样例目录 + 以命令行方式下载样例代码，master分支为例。 + ```bash + cd ${git_clone_path}/samples/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/ + ``` + - 配置环境变量 + + 请根据当前环境上CANN开发套件包的[安装方式](https://hiascend.com/document/redirect/CannCommunityInstSoftware)，选择对应配置环境变量的命令。 + - 默认路径，root用户安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=/usr/local/Ascend/ascend-toolkit/latest + ``` + - 默认路径，非root用户安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=$HOME/Ascend/ascend-toolkit/latest + ``` + - 指定路径install_path，安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=${install_path}/ascend-toolkit/latest + ``` + + 配置仿真模式日志文件目录，默认为sim_log。 + ```bash + export CAMODEL_LOG_PATH=./sim_log + ``` + + - 样例执行 + + ```bash + bash run.sh -r [RUN_MODE] -v [SOC_VERSION] + ``` + - RUN_MODE：编译方式，可选择CPU调试，NPU仿真，NPU上板。支持参数为[cpu / sim / npu]，默认值为npu。 + - SOC_VERSION：昇腾AI处理器型号，如果无法确定具体的[SOC_VERSION]，则在安装昇腾AI处理器的服务器执行npu-smi info命令进行查询，在查询到的“Name”前增加Ascend信息，例如“Name”对应取值为xxxyy，实际配置的[SOC_VERSION]值为Ascendxxxyy。支持以下产品型号： + - Atlas A2训练系列产品/Atlas 800I A2推理产品 + + 示例如下，Ascendxxxyy请替换为实际的AI处理器型号。 + ```bash + bash run.sh -r cpu -v Ascendxxxyy + ``` \ No newline at end of file diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom.cpp new file mode 100644 index 0000000000000000000000000000000000000000..a33c6a9308a0e4d084bb58feccd4cca5383d0d32 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom.cpp @@ -0,0 +1,909 @@ +/** + * @file add_custom.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include "add_custom_tiling.h" +#include "kernel_operator.h" + +constexpr int32_t BUFFER_NUM = 2; // tensor num for each queue + +constexpr uint32_t ADD_BFLOAT16 = 0; +constexpr uint32_t ADD_FLOAT16 = 1; +constexpr uint32_t ADD_FLOAT32 = 2; +constexpr uint32_t ADD_INT8 = 3; +constexpr uint32_t ADD_INT16 = 4; +constexpr uint32_t ADD_INT32 = 5; + +constexpr uint32_t BROADCAST_DIM = 2; +constexpr uint32_t BROADCAST_AXIS_ZERO = 0; +constexpr uint32_t BROADCAST_AXIS_ONE = 1; +constexpr uint32_t LAST_TWO_TILE = 2; +template class KernelAdd; + +// 针对axis = 0的场景 +template <> class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + GM_ADDR longerInputPtr; + GM_ADDR shorterInputPtr; + if (tiling.xLen > tiling.yLen) { + longerInputPtr = x; + shorterInputPtr = y; + } else { + longerInputPtr = y; + shorterInputPtr = x; + } + this->coef = tiling.coef; + if (tiling.isEvenCore) { + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)longerInputPtr + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)longerInputPtr + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)longerInputPtr + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(bfloat16_t)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->coef * sizeof(bfloat16_t)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(bfloat16_t)); + + pipe.InitBuffer(tmpBuf2, this->tileLength * sizeof(bfloat16_t)); + pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(float)); + pipe.InitBuffer(tmpBuf1, 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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopyExtParams copyXParams = {1, (uint32_t)(this->tileLength * sizeof(bfloat16_t)), 0, 0, 0}; + AscendC::DataCopyExtParams copyYParams = {1, (uint32_t)(this->coef * sizeof(bfloat16_t)), 0, 0, 0}; + AscendC::DataCopyPadExtParams padParams = {false, 0, 0, 0}; + + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + copyXParams, padParams); + } else { + AscendC::DataCopyPad(xLocal, xGm[progress * this->tileLength], copyXParams, padParams); + } + AscendC::DataCopyPad(yLocal, yGm, copyYParams, padParams); + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute(int32_t progress) + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor broadcastTmpTensor = tmpBuf2.Get(); + uint32_t dstShape[] = {this->tileLength / this->coef, this->coef}; + uint32_t srcShape[] = {1, this->coef}; + AscendC::Broadcast(broadcastTmpTensor, yLocal, dstShape, srcShape); + + AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); + AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); + + AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + AscendC::Cast(tmpTensor1, broadcastTmpTensor, AscendC::RoundMode::CAST_NONE, this->tileLength); + + AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); + AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_RINT, this->tileLength); + + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopyExtParams copyParams = {1, (uint32_t)(this->tileLength * sizeof(bfloat16_t)), 0, 0, 0}; + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, copyParams); + } else { + AscendC::DataCopyPad(zGm[progress * this->tileLength], zLocal, copyParams); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::TBuf tmpBuf0; + AscendC::TBuf tmpBuf1; + AscendC::TBuf tmpBuf2; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t coef; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +template <> class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + GM_ADDR longerInputPtr; + GM_ADDR shorterInputPtr; + if (tiling.xLen > tiling.yLen) { + longerInputPtr = x; + shorterInputPtr = y; + } else { + longerInputPtr = y; + shorterInputPtr = x; + } + this->coef = tiling.coef; + if (tiling.isEvenCore) { + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)longerInputPtr + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)longerInputPtr + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)longerInputPtr + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(int8_t)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->coef * sizeof(int8_t)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(int8_t)); + + pipe.InitBuffer(tmpBuf2, this->tileLength * sizeof(int8_t)); + + pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(half)); + pipe.InitBuffer(tmpBuf1, this->tileLength * sizeof(half)); + } + __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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopyExtParams copyXParams = {1, (uint32_t)(this->tileLength * sizeof(int8_t)), 0, 0, 0}; + AscendC::DataCopyExtParams copyYParams = {1, (uint32_t)(this->coef * sizeof(int8_t)), 0, 0, 0}; + AscendC::DataCopyPadExtParams padParams = {false, 0, 0, 0}; + + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + copyXParams, padParams); + } else { + AscendC::DataCopyPad(xLocal, xGm[progress * this->tileLength], copyXParams, padParams); + } + AscendC::DataCopyPad(yLocal, yGm, copyYParams, padParams); + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute(int32_t progress) + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor broadcastTmpTensor = tmpBuf2.Get(); + uint32_t dstShape[] = {this->tileLength / this->coef, this->coef}; + uint32_t srcShape[] = {1, this->coef}; + AscendC::Broadcast(broadcastTmpTensor, yLocal, dstShape, srcShape); + + AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); + AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); + + AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + AscendC::Cast(tmpTensor1, broadcastTmpTensor, AscendC::RoundMode::CAST_NONE, this->tileLength); + + AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); + AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_NONE, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopyExtParams copyParams = {1, (uint32_t)(this->tileLength * sizeof(int8_t)), 0, 0, 0}; + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, copyParams); + } else { + AscendC::DataCopyPad(zGm[progress * this->tileLength], zLocal, copyParams); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::TBuf tmpBuf0; + AscendC::TBuf tmpBuf1; + AscendC::TBuf tmpBuf2; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t coef; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +template class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + GM_ADDR longerInputPtr; + GM_ADDR shorterInputPtr; + if (tiling.xLen > tiling.yLen) { + longerInputPtr = x; + shorterInputPtr = y; + } else { + longerInputPtr = y; + shorterInputPtr = x; + } + this->coef = tiling.coef; + if (tiling.isEvenCore) { + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)longerInputPtr + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + yGm.SetGlobalBuffer((__gm__ dataType *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)longerInputPtr + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ dataType *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)longerInputPtr + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ dataType *)shorterInputPtr, this->coef); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(dataType)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->coef * sizeof(dataType)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(dataType)); + + pipe.InitBuffer(tmpBuf2, this->tileLength * sizeof(dataType)); + } + __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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopyExtParams copyXParams = {1, (uint32_t)(this->tileLength * sizeof(dataType)), 0, 0, 0}; + AscendC::DataCopyExtParams copyYParams = {1, (uint32_t)(this->coef * sizeof(dataType)), 0, 0, 0}; + AscendC::DataCopyPadExtParams padParams = {false, 0, 0, 0}; + + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + copyXParams, padParams); + } else { + AscendC::DataCopyPad(xLocal, xGm[progress * this->tileLength], copyXParams, padParams); + } + AscendC::DataCopyPad(yLocal, yGm, copyYParams, padParams); + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute(int32_t progress) + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor broadcastTmpTensor = tmpBuf2.Get(); + uint32_t dstShape[] = {this->tileLength / this->coef, this->coef}; + uint32_t srcShape[] = {1, this->coef}; + AscendC::Broadcast(broadcastTmpTensor, yLocal, dstShape, srcShape); + + AscendC::Add(zLocal, xLocal, broadcastTmpTensor, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopyExtParams copyParams = {1, (uint32_t)(this->tileLength * sizeof(dataType)), 0, 0, 0}; + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, copyParams); + } else { + AscendC::DataCopyPad(zGm[progress * this->tileLength], zLocal, copyParams); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::TBuf tmpBuf2; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t coef; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +// 针对axis = 1的场景 +template <> class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + GM_ADDR longerInputPtr; + GM_ADDR shorterInputPtr; + if (tiling.xLen > tiling.yLen) { + longerInputPtr = x; + shorterInputPtr = y; + } else { + longerInputPtr = y; + shorterInputPtr = x; + } + this->coef = tiling.coef; + if (tiling.isEvenCore) { + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)longerInputPtr + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)shorterInputPtr + tiling.blockLength * AscendC::GetBlockIdx() / this->coef, tiling.blockLength / this->coef); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)longerInputPtr + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)shorterInputPtr + tiling.formerLength * AscendC::GetBlockIdx() / this->coef, tiling.formerLength / this->coef); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)longerInputPtr + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)shorterInputPtr + tiling.formerLength * tiling.formerNum / this->coef + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum) / this->coef, tiling.tailLength / this->coef); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(bfloat16_t)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->coef * sizeof(bfloat16_t)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(bfloat16_t)); + + pipe.InitBuffer(tmpBuf2, this->tileLength * sizeof(bfloat16_t)); + pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(float)); + pipe.InitBuffer(tmpBuf1, 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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopyExtParams copyXParams = {1, (uint32_t)(this->tileLength * sizeof(bfloat16_t)), 0, 0, 0}; + AscendC::DataCopyExtParams copyYParams = {1, (uint32_t)(this->tileLength * sizeof(bfloat16_t) / this->coef), 0, 0, 0}; + AscendC::DataCopyPadExtParams padParams = {false, 0, 0, 0}; + + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + copyXParams, padParams); + AscendC::DataCopyPad(yLocal, yGm[((progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength) / this->coef], + copyYParams, padParams); + } else { + AscendC::DataCopyPad(xLocal, xGm[progress * this->tileLength], copyXParams, padParams); + AscendC::DataCopyPad(yLocal, yGm[progress * this->tileLength / this->coef], copyYParams, padParams); + } + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute(int32_t progress) + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor broadcastTmpTensor = tmpBuf2.Get(); + uint32_t dstShape[] = {this->tileLength / this->coef, this->coef}; + uint32_t srcShape[] = {this->tileLength / this->coef, 1}; + AscendC::Broadcast(broadcastTmpTensor, yLocal, dstShape, srcShape); + + AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); + AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); + + AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + AscendC::Cast(tmpTensor1, broadcastTmpTensor, AscendC::RoundMode::CAST_NONE, this->tileLength); + + AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); + AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_RINT, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopyExtParams copyParams = {1, (uint32_t)(this->tileLength * sizeof(bfloat16_t)), 0, 0, 0}; + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, copyParams); + } else { + AscendC::DataCopyPad(zGm[progress * this->tileLength], zLocal, copyParams); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::TBuf tmpBuf0; + AscendC::TBuf tmpBuf1; + AscendC::TBuf tmpBuf2; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t coef; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +template <> class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + GM_ADDR longerInputPtr; + GM_ADDR shorterInputPtr; + if (tiling.xLen > tiling.yLen) { + longerInputPtr = x; + shorterInputPtr = y; + } else { + longerInputPtr = y; + shorterInputPtr = x; + } + this->coef = tiling.coef; + if (tiling.isEvenCore) { + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)longerInputPtr + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)shorterInputPtr + tiling.blockLength * AscendC::GetBlockIdx() / this->coef, tiling.blockLength / this->coef); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)longerInputPtr + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)shorterInputPtr + tiling.formerLength * AscendC::GetBlockIdx() / this->coef, tiling.formerLength / this->coef); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ int8_t *)longerInputPtr + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ int8_t *)shorterInputPtr + tiling.formerLength * tiling.formerNum / this->coef + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum) / this->coef, tiling.tailLength / this->coef); + zGm.SetGlobalBuffer((__gm__ int8_t *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(int8_t)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->coef * sizeof(int8_t)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(int8_t)); + + pipe.InitBuffer(tmpBuf2, this->tileLength * sizeof(int8_t)); + + pipe.InitBuffer(tmpBuf0, this->tileLength * sizeof(half)); + pipe.InitBuffer(tmpBuf1, this->tileLength * sizeof(half)); + } + __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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopyExtParams copyXParams = {1, (uint32_t)(this->tileLength * sizeof(int8_t)), 0, 0, 0}; + AscendC::DataCopyExtParams copyYParams = {1, (uint32_t)(this->tileLength * sizeof(int8_t) / this->coef), 0, 0, 0}; + AscendC::DataCopyPadExtParams padParams = {false, 0, 0, 0}; + + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + copyXParams, padParams); + AscendC::DataCopyPad(yLocal, yGm[((progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength) / this->coef], + copyYParams, padParams); + } else { + AscendC::DataCopyPad(xLocal, xGm[progress * this->tileLength], copyXParams, padParams); + AscendC::DataCopyPad(yLocal, yGm[progress * this->tileLength / this->coef], copyYParams, padParams); + } + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute(int32_t progress) + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor broadcastTmpTensor = tmpBuf2.Get(); + uint32_t dstShape[] = {this->tileLength / this->coef, this->coef}; + uint32_t srcShape[] = {this->tileLength / this->coef, 1}; + AscendC::Broadcast(broadcastTmpTensor, yLocal, dstShape, srcShape); + + AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); + AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); + + AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, this->tileLength); + AscendC::Cast(tmpTensor1, broadcastTmpTensor, AscendC::RoundMode::CAST_NONE, this->tileLength); + + AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, this->tileLength); + AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_NONE, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopyExtParams copyParams = {1, (uint32_t)(this->tileLength * sizeof(int8_t)), 0, 0, 0}; + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, copyParams); + } else { + AscendC::DataCopyPad(zGm[progress * this->tileLength], zLocal, copyParams); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::TBuf tmpBuf0; + AscendC::TBuf tmpBuf1; + AscendC::TBuf tmpBuf2; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t coef; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +template class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) + { + GM_ADDR longerInputPtr; + GM_ADDR shorterInputPtr; + if (tiling.xLen > tiling.yLen) { + longerInputPtr = x; + shorterInputPtr = y; + } else { + longerInputPtr = y; + shorterInputPtr = x; + } + this->coef = tiling.coef; + if (tiling.isEvenCore) { + this->tileNum = tiling.tileNum; + this->tileLength = tiling.tileLength / BUFFER_NUM; + this->lastTileLength = tiling.lastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)longerInputPtr + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + yGm.SetGlobalBuffer((__gm__ dataType *)shorterInputPtr + tiling.blockLength * AscendC::GetBlockIdx() / this->coef, tiling.blockLength / this->coef); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.blockLength * AscendC::GetBlockIdx(), tiling.blockLength); + } else { + if (AscendC::GetBlockIdx() < tiling.formerNum) { + this->tileNum = tiling.formerTileNum; + this->tileLength = tiling.formerTileLength / BUFFER_NUM; + this->lastTileLength = tiling.formerLastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)longerInputPtr + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + yGm.SetGlobalBuffer((__gm__ dataType *)shorterInputPtr + tiling.formerLength * AscendC::GetBlockIdx() / this->coef, tiling.formerLength / this->coef); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.formerLength * AscendC::GetBlockIdx(), tiling.formerLength); + } else { + this->tileNum = tiling.tailTileNum; + this->tileLength = tiling.tailTileLength / BUFFER_NUM; + this->lastTileLength = tiling.tailLastTileLength; + + xGm.SetGlobalBuffer((__gm__ dataType *)longerInputPtr + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + yGm.SetGlobalBuffer((__gm__ dataType *)shorterInputPtr + tiling.formerLength * tiling.formerNum / this->coef + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum) / this->coef, tiling.tailLength / this->coef); + zGm.SetGlobalBuffer((__gm__ dataType *)z + tiling.formerLength * tiling.formerNum + + tiling.tailLength * (AscendC::GetBlockIdx() - tiling.formerNum), tiling.tailLength); + } + } + pipe.InitBuffer(inQueueX, BUFFER_NUM, this->tileLength * sizeof(dataType)); + pipe.InitBuffer(inQueueY, BUFFER_NUM, this->coef * sizeof(dataType)); + pipe.InitBuffer(outQueueZ, BUFFER_NUM, this->tileLength * sizeof(dataType)); + + pipe.InitBuffer(tmpBuf2, this->tileLength * sizeof(dataType)); + } + __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 xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopyExtParams copyXParams = {1, (uint32_t)(this->tileLength * sizeof(dataType)), 0, 0, 0}; + AscendC::DataCopyExtParams copyYParams = {1, (uint32_t)(this->tileLength * sizeof(dataType) / this->coef), 0, 0, 0}; + AscendC::DataCopyPadExtParams padParams = {false, 0, 0, 0}; + + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(xLocal, xGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], + copyXParams, padParams); + AscendC::DataCopyPad(yLocal, yGm[((progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength) / this->coef], + copyYParams, padParams); + } else { + AscendC::DataCopyPad(xLocal, xGm[progress * this->tileLength], copyXParams, padParams); + AscendC::DataCopyPad(yLocal, yGm[progress * this->tileLength / this->coef], copyYParams, padParams); + } + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute(int32_t progress) + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor broadcastTmpTensor = tmpBuf2.Get(); + uint32_t dstShape[] = {this->tileLength / this->coef, this->coef}; + uint32_t srcShape[] = {this->tileLength / this->coef, 1}; + AscendC::Broadcast(broadcastTmpTensor, yLocal, dstShape, srcShape); + + AscendC::Add(zLocal, xLocal, broadcastTmpTensor, this->tileLength); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut(int32_t progress) + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopyExtParams copyParams = {1, (uint32_t)(this->tileLength * sizeof(dataType)), 0, 0, 0}; + if ((progress == (this->tileNum * BUFFER_NUM - 2)) || (progress == (this->tileNum * BUFFER_NUM - 1))) { + AscendC::DataCopyPad(zGm[(progress - LAST_TWO_TILE) * this->tileLength + this->lastTileLength], zLocal, copyParams); + } else { + AscendC::DataCopyPad(zGm[progress * this->tileLength], zLocal, copyParams); + } + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::TBuf tmpBuf2; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; + + uint32_t coef; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; +}; + +extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling) +{ + if (tiling.axis == 0) { + if (tiling.dataType == ADD_BFLOAT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_FLOAT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_FLOAT32) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT8) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT32) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else { + return; + } + } else if (tiling.axis == 1) { + if (tiling.dataType == ADD_BFLOAT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_FLOAT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_FLOAT32) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT8) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT16) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else if (tiling.dataType == ADD_INT32) { + KernelAdd op; + op.Init(x, y, z, tiling); + op.Process(); + } else { + return; + } + } else { + return; + } +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom_tiling.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom_tiling.cpp new file mode 100644 index 0000000000000000000000000000000000000000..85e624b071ca20184412c6e7cbc4bf223e29e319 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom_tiling.cpp @@ -0,0 +1,111 @@ +/** + * @file add_custom_tiling.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ + +#include +#include "add_custom_tiling.h" + +// bfloat16, float16, float, int8, int16, int32 +constexpr uint32_t DATA_TYPE_SIZE[] = {2, 2, 4, 1, 2, 4}; +constexpr uint32_t BLOCK_SIZE = 32; +constexpr uint32_t BUFFER_NUM = 2; +constexpr uint32_t UB_BLOCK_NUM = 50; // UB最大可以使用的block数量 +constexpr uint32_t MAX_AVAILABLE_UB_BLOCK_NUM = UB_BLOCK_NUM / BUFFER_NUM * BUFFER_NUM; +constexpr uint32_t BLOCK_DIM = 8; +void TilingParamsCalc(uint32_t length, uint32_t ubBlockNum, + uint32_t& tileNum, uint32_t& tileLength, uint32_t& lastTileLength) +{ + assert(ubBlockNum != 0U); + tileNum = length / ubBlockNum; + if (length % ubBlockNum == 0U || tileNum == 0U) { + if (tileNum == 0U) { + tileNum = 1U; + } + if (length < ubBlockNum) { + tileLength = length; + lastTileLength = tileLength; + } else { + tileLength = ubBlockNum; + lastTileLength = tileLength; + } + } else { + tileNum++; + tileLength = ubBlockNum; + lastTileLength = (uint32_t)(length - (tileNum - 1) * tileLength); + } +} + +void GenerateTilingData(uint8_t* tilingBuf) +{ + uint32_t xLen; + uint32_t yLen; + uint32_t totalLength; + uint32_t dataTypeSize; + + AddCustomTilingData *tiling = reinterpret_cast(tilingBuf); + xLen = tiling->xLen; + yLen = tiling->yLen; + assert((xLen != 0U) && (yLen != 0U)); + dataTypeSize = DATA_TYPE_SIZE[tiling->dataType]; + totalLength = (xLen > yLen)? xLen : yLen; + + uint32_t alignNum = BLOCK_SIZE / dataTypeSize; + uint32_t shorterAxisLen = (xLen < yLen)? xLen : yLen; + uint32_t coef = totalLength / shorterAxisLen; + uint32_t ubBlockAligned = + (MAX_AVAILABLE_UB_BLOCK_NUM * alignNum / (coef * BUFFER_NUM) * (coef * BUFFER_NUM) == 0U)? + MAX_AVAILABLE_UB_BLOCK_NUM : MAX_AVAILABLE_UB_BLOCK_NUM * alignNum / (coef * BUFFER_NUM) * (coef * BUFFER_NUM); + + if (shorterAxisLen % (BLOCK_DIM * BUFFER_NUM) == 0U) { + uint32_t blockLength = shorterAxisLen / BLOCK_DIM * coef; + uint32_t tileNum = 0; + uint32_t tileLength = 0; + uint32_t lastTileLength = 0; + + TilingParamsCalc(blockLength, ubBlockAligned, tileNum, tileLength, lastTileLength); + + tiling->blockLength = blockLength; + tiling->tileNum = tileNum; + tiling->tileLength = tileLength; + tiling->lastTileLength = lastTileLength; + tiling->isEvenCore = 1U; + } else { + uint32_t formerNum = (shorterAxisLen / BUFFER_NUM) % BLOCK_DIM; + uint32_t tailNum = BLOCK_DIM - formerNum; + + uint32_t formerLength = (((shorterAxisLen / BUFFER_NUM) / BLOCK_DIM) + 1) * BUFFER_NUM * coef; + uint32_t tailLength = ((shorterAxisLen / BUFFER_NUM) / BLOCK_DIM) * BUFFER_NUM * coef; + + uint32_t formerTileNum; + uint32_t formerTileLength; + uint32_t formerLastTileLength; + + uint32_t tailTileNum; + uint32_t tailTileLength; + uint32_t tailLastTileLength; + + TilingParamsCalc(formerLength, ubBlockAligned, + formerTileNum, formerTileLength, formerLastTileLength); + TilingParamsCalc(tailLength, ubBlockAligned, + tailTileNum, tailTileLength, tailLastTileLength); + + tiling->formerNum = formerNum; + tiling->formerLength = formerLength; + tiling->formerTileNum = formerTileNum; + tiling->formerTileLength = formerTileLength; + tiling->formerLastTileLength = formerLastTileLength; + + tiling->tailNum = tailNum; + tiling->tailLength = tailLength; + tiling->tailTileNum = tailTileNum; + tiling->tailTileLength = tailTileLength; + tiling->tailLastTileLength = tailLastTileLength; + tiling->isEvenCore = 0U; + } +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom_tiling.h b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom_tiling.h new file mode 100644 index 0000000000000000000000000000000000000000..8c31f6f4a4b95904c18070db5dee70d29dd64ee9 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/add_custom_tiling.h @@ -0,0 +1,39 @@ +/** + * @file add_custom_tiling.h + * + * Copyright (C) 2025. Huawei Technologies Co. Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#ifndef ADD_CUSTOM_TILING_H +#define ADD_CUSTOM_TILING_H +#include + +struct AddCustomTilingData { + uint32_t xLen; + uint32_t yLen; + uint32_t coef; + uint32_t axis; + uint32_t dataType; + + uint32_t isEvenCore; + uint32_t blockLength; + uint32_t tileNum; + uint32_t tileLength; + uint32_t lastTileLength; + + uint32_t formerNum; + uint32_t formerLength; + uint32_t formerTileNum; + uint32_t formerTileLength; + uint32_t formerLastTileLength; + + uint32_t tailNum; + uint32_t tailLength; + uint32_t tailTileNum; + uint32_t tailTileLength; + uint32_t tailLastTileLength; +}; +#endif \ No newline at end of file diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/cmake/cpu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/cmake/cpu_lib.cmake new file mode 100644 index 0000000000000000000000000000000000000000..5362c8b5a53b1f730ac6fe542ee226a42dff40ff --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/cmake/cpu_lib.cmake @@ -0,0 +1,9 @@ +if(NOT DEFINED ENV{CMAKE_PREFIX_PATH}) + set(CMAKE_PREFIX_PATH ${ASCEND_CANN_PACKAGE_PATH}/tools/tikicpulib/lib/cmake) +endif() +find_package(tikicpulib REQUIRED) + +add_library(ascendc_kernels_${RUN_MODE} SHARED ${KERNEL_FILES}) +target_link_libraries(ascendc_kernels_${RUN_MODE} PUBLIC tikicpulib::${SOC_VERSION}) +target_compile_options(ascendc_kernels_${RUN_MODE} PRIVATE -g -O0 -std=c++17) +install(TARGETS ascendc_kernels_${RUN_MODE} DESTINATION ${CMAKE_INSTALL_LIBDIR}) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/cmake/npu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/cmake/npu_lib.cmake new file mode 100644 index 0000000000000000000000000000000000000000..f92b095d1f4f258af274b98dfcba2dccf6165b30 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/cmake/npu_lib.cmake @@ -0,0 +1,11 @@ +if(EXISTS ${ASCEND_CANN_PACKAGE_PATH}/compiler/tikcpp/ascendc_kernel_cmake) + set(ASCENDC_CMAKE_DIR ${ASCEND_CANN_PACKAGE_PATH}/compiler/tikcpp/ascendc_kernel_cmake) +elseif(EXISTS ${ASCEND_CANN_PACKAGE_PATH}/tools/tikcpp/ascendc_kernel_cmake) + set(ASCENDC_CMAKE_DIR ${ASCEND_CANN_PACKAGE_PATH}/tools/tikcpp/ascendc_kernel_cmake) +else() + message(FATAL_ERROR "ascendc_kernel_cmake does not exist ,please check whether the cann package is installed") +endif() +include(${ASCENDC_CMAKE_DIR}/ascendc.cmake) + +# ascendc_library use to add kernel file to generate ascendc library +ascendc_library(ascendc_kernels_${RUN_MODE} SHARED ${KERNEL_FILES}) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/data_utils.h b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/data_utils.h new file mode 100644 index 0000000000000000000000000000000000000000..9d34457807dda2d0c79ce19eadc7fcbd4667ece2 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/data_utils.h @@ -0,0 +1,203 @@ +/** + * @file data_utils.h + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#ifndef DATA_UTILS_H +#define DATA_UTILS_H +#include +#include +#include + +#include +#include +#include +#include +#include +#include +#include + +#include "acl/acl.h" + +typedef enum { + DT_UNDEFINED = -1, + FLOAT = 0, + HALF = 1, + INT8_T = 2, + INT32_T = 3, + UINT8_T = 4, + INT16_T = 6, + UINT16_T = 7, + UINT32_T = 8, + INT64_T = 9, + UINT64_T = 10, + DOUBLE = 11, + BOOL = 12, + STRING = 13, + COMPLEX64 = 16, + COMPLEX128 = 17, + BF16 = 27 +} printDataType; + +#define INFO_LOG(fmt, args...) fprintf(stdout, "[INFO] " fmt "\n", ##args) +#define WARN_LOG(fmt, args...) fprintf(stdout, "[WARN] " fmt "\n", ##args) +#define ERROR_LOG(fmt, args...) fprintf(stdout, "[ERROR] " fmt "\n", ##args) +#define CHECK_ACL(x) \ + do { \ + aclError __ret = x; \ + if (__ret != ACL_ERROR_NONE) { \ + std::cerr << __FILE__ << ":" << __LINE__ << " aclError:" << __ret << std::endl; \ + } \ + } while (0); + +/** + * @brief Read data from file + * @param [in] filePath: file path + * @param [out] fileSize: file size + * @return read result + */ +bool ReadFile(const std::string &filePath, size_t &fileSize, void *buffer, size_t bufferSize) +{ + struct stat sBuf; + int fileStatus = stat(filePath.data(), &sBuf); + if (fileStatus == -1) { + ERROR_LOG("failed to get file"); + return false; + } + if (S_ISREG(sBuf.st_mode) == 0) { + ERROR_LOG("%s is not a file, please enter a file", filePath.c_str()); + return false; + } + + std::ifstream file; + file.open(filePath, std::ios::binary); + if (!file.is_open()) { + ERROR_LOG("Open file failed. path = %s", filePath.c_str()); + return false; + } + + std::filebuf *buf = file.rdbuf(); + size_t size = buf->pubseekoff(0, std::ios::end, std::ios::in); + if (size == 0) { + ERROR_LOG("file size is 0"); + file.close(); + return false; + } + if (size > bufferSize) { + ERROR_LOG("file size is larger than buffer size"); + file.close(); + return false; + } + buf->pubseekpos(0, std::ios::in); + buf->sgetn(static_cast(buffer), size); + fileSize = size; + file.close(); + return true; +} + +/** + * @brief Write data to file + * @param [in] filePath: file path + * @param [in] buffer: data to write to file + * @param [in] size: size to write + * @return write result + */ +bool WriteFile(const std::string &filePath, const void *buffer, size_t size) +{ + if (buffer == nullptr) { + ERROR_LOG("Write file failed. buffer is nullptr"); + return false; + } + + int fd = open(filePath.c_str(), O_RDWR | O_CREAT | O_TRUNC, S_IRUSR | S_IWRITE); + if (fd < 0) { + ERROR_LOG("Open file failed. path = %s", filePath.c_str()); + return false; + } + + size_t writeSize = write(fd, buffer, size); + (void)close(fd); + if (writeSize != size) { + ERROR_LOG("Write file Failed."); + return false; + } + + return true; +} + +template void DoPrintData(const T *data, size_t count, size_t elementsPerRow) +{ + assert(elementsPerRow != 0); + for (size_t i = 0; i < count; ++i) { + std::cout << std::setw(10) << data[i]; + if (i % elementsPerRow == elementsPerRow - 1) { + std::cout << std::endl; + } + } +} + +void DoPrintHalfData(const aclFloat16 *data, size_t count, size_t elementsPerRow) +{ + assert(elementsPerRow != 0); + for (size_t i = 0; i < count; ++i) { + std::cout << std::setw(10) << std::setprecision(6) << aclFloat16ToFloat(data[i]); + if (i % elementsPerRow == elementsPerRow - 1) { + std::cout << std::endl; + } + } +} + +void PrintData(const void *data, size_t count, printDataType dataType, size_t elementsPerRow = 16) +{ + if (data == nullptr) { + ERROR_LOG("Print data failed. data is nullptr"); + return; + } + + switch (dataType) { + case BOOL: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT8_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT8_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT16_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT16_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT32_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT32_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT64_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT64_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case HALF: + DoPrintHalfData(reinterpret_cast(data), count, elementsPerRow); + break; + case FLOAT: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case DOUBLE: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + default: + ERROR_LOG("Unsupported type: %d", dataType); + } + std::cout << std::endl; +} +#endif // DATA_UTILS_H diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/main.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/main.cpp new file mode 100644 index 0000000000000000000000000000000000000000..b5c077951a778a38029743958fa617406706c785 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/main.cpp @@ -0,0 +1,109 @@ +/** + * @file main.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include "add_custom_tiling.h" +#include "data_utils.h" +#ifndef ASCENDC_CPU_DEBUG +#include "acl/acl.h" +#include "aclrtlaunch_add_custom.h" +#include "tiling/platform/platform_ascendc.h" +#else +#include "tikicpulib.h" +extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z, AddCustomTilingData tiling); +#endif +extern void GenerateTilingData(uint8_t* tilingBuf); + + +int32_t main(int32_t argc, char *argv[]) +{ + constexpr uint32_t BLOCK_DIM = 8; + constexpr uint32_t DATA_TYPE_SIZE[] = {2, 2, 4, 1, 2, 4}; + uint8_t *tiling = nullptr; + size_t tilingSize = 20 * sizeof(uint32_t); + +#ifdef ASCENDC_CPU_DEBUG + tiling = (uint8_t *)AscendC::GmAlloc(tilingSize); + ReadFile("./input/input_tiling.bin", tilingSize, tiling, tilingSize); +#else + CHECK_ACL(aclInit(nullptr)); + int32_t deviceId = 0; + CHECK_ACL(aclrtSetDevice(deviceId)); + aclrtStream stream = nullptr; + CHECK_ACL(aclrtCreateStream(&stream)); + + uint8_t *xHost, *yHost, *zHost; + uint8_t *xDevice, *yDevice, *zDevice; + + CHECK_ACL(aclrtMallocHost((void **)(&tiling), tilingSize)); + ReadFile("./input/input_tiling.bin", tilingSize, tiling, tilingSize); +#endif + GenerateTilingData(tiling); + uint32_t dataTypeSize = DATA_TYPE_SIZE[reinterpret_cast(tiling)->dataType]; + uint32_t xLen = reinterpret_cast(tiling)->xLen; + uint32_t yLen = reinterpret_cast(tiling)->yLen; + uint32_t totalLength = (xLen > yLen)? xLen : yLen; + + size_t inputXByteSize = xLen * dataTypeSize; + size_t inputYByteSize = yLen * dataTypeSize; + size_t outputByteSize = totalLength * dataTypeSize; + +#ifdef ASCENDC_CPU_DEBUG + uint8_t *x = (uint8_t *)AscendC::GmAlloc(inputXByteSize); + uint8_t *y = (uint8_t *)AscendC::GmAlloc(inputYByteSize); + uint8_t *z = (uint8_t *)AscendC::GmAlloc(outputByteSize); + + ReadFile("./input/input_x.bin", inputXByteSize, x, inputXByteSize); + ReadFile("./input/input_y.bin", inputYByteSize, y, inputYByteSize); + + AscendC::SetKernelMode(KernelMode::AIV_MODE); + + ICPU_RUN_KF(add_custom, BLOCK_DIM, x, y, z, + *reinterpret_cast(tiling)); + + WriteFile("./output/output_z.bin", z, outputByteSize); + + AscendC::GmFree((void *)x); + AscendC::GmFree((void *)y); + AscendC::GmFree((void *)z); + AscendC::GmFree((void *)tiling); +#else + CHECK_ACL(aclrtMallocHost((void **)(&xHost), inputXByteSize)); + CHECK_ACL(aclrtMallocHost((void **)(&yHost), inputYByteSize)); + CHECK_ACL(aclrtMallocHost((void **)(&zHost), outputByteSize)); + CHECK_ACL(aclrtMalloc((void **)&xDevice, inputXByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + CHECK_ACL(aclrtMalloc((void **)&yDevice, inputYByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + CHECK_ACL(aclrtMalloc((void **)&zDevice, outputByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + + ReadFile("./input/input_x.bin", inputXByteSize, xHost, inputXByteSize); + ReadFile("./input/input_y.bin", inputYByteSize, yHost, inputYByteSize); + + CHECK_ACL(aclrtMemcpy(xDevice, inputXByteSize, xHost, inputXByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); + CHECK_ACL(aclrtMemcpy(yDevice, inputYByteSize, yHost, inputYByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); + + ACLRT_LAUNCH_KERNEL(add_custom)(BLOCK_DIM, stream, xDevice, yDevice, zDevice, + reinterpret_cast(tiling)); + CHECK_ACL(aclrtSynchronizeStream(stream)); + + CHECK_ACL(aclrtMemcpy(zHost, outputByteSize, zDevice, outputByteSize, ACL_MEMCPY_DEVICE_TO_HOST)); + WriteFile("./output/output_z.bin", zHost, outputByteSize); + + CHECK_ACL(aclrtFree(xDevice)); + CHECK_ACL(aclrtFree(yDevice)); + CHECK_ACL(aclrtFree(zDevice)); + CHECK_ACL(aclrtFreeHost(xHost)); + CHECK_ACL(aclrtFreeHost(yHost)); + CHECK_ACL(aclrtFreeHost(zHost)); + CHECK_ACL(aclrtFreeHost(tiling)); + + CHECK_ACL(aclrtDestroyStream(stream)); + CHECK_ACL(aclrtResetDevice(deviceId)); + CHECK_ACL(aclFinalize()); +#endif + return 0; +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/run.sh b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/run.sh new file mode 100644 index 0000000000000000000000000000000000000000..8fcd5973012ebe2bf99402148a89ee2ff8ec9655 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/run.sh @@ -0,0 +1,124 @@ +#!/bin/bash +CURRENT_DIR=$( + cd $(dirname ${BASH_SOURCE:-$0}) + pwd +) +cd $CURRENT_DIR + +BUILD_TYPE="Debug" +INSTALL_PREFIX="${CURRENT_DIR}/out" + +SHORT=r:,v:,i:,b:,p:, +LONG=run-mode:,soc-version:,install-path:,build-type:,install-prefix:, +OPTS=$(getopt -a --options $SHORT --longoptions $LONG -- "$@") +eval set -- "$OPTS" +SOC_VERSION="Ascend310P3" + +while :; do + case "$1" in + -r | --run-mode) + RUN_MODE="$2" + shift 2 + ;; + -v | --soc-version) + SOC_VERSION="$2" + shift 2 + ;; + -i | --install-path) + ASCEND_INSTALL_PATH="$2" + shift 2 + ;; + -b | --build-type) + BUILD_TYPE="$2" + shift 2 + ;; + -p | --install-prefix) + INSTALL_PREFIX="$2" + shift 2 + ;; + --) + shift + break + ;; + *) + echo "[ERROR] Unexpected option: $1" + break + ;; + esac +done + +RUN_MODE_LIST="cpu sim npu" +if [[ " $RUN_MODE_LIST " != *" $RUN_MODE "* ]]; then + echo "ERROR: RUN_MODE error, This sample only support specify cpu, sim or npu!" + exit -1 +fi + +VERSION_LIST="Ascend910A Ascend910B Ascend310B1 Ascend310B2 Ascend310B3 Ascend310B4 Ascend310P1 Ascend310P3 Ascend910B1 Ascend910B2 Ascend910B3 Ascend910B4" +if [[ " $VERSION_LIST " != *" $SOC_VERSION "* ]]; then + echo "ERROR: SOC_VERSION should be in [$VERSION_LIST]" + exit -1 +fi + +if [ -n "$ASCEND_INSTALL_PATH" ]; then + _ASCEND_INSTALL_PATH=$ASCEND_INSTALL_PATH +elif [ -n "$ASCEND_HOME_PATH" ]; then + _ASCEND_INSTALL_PATH=$ASCEND_HOME_PATH +else + if [ -d "$HOME/Ascend/ascend-toolkit/latest" ]; then + _ASCEND_INSTALL_PATH=$HOME/Ascend/ascend-toolkit/latest + else + _ASCEND_INSTALL_PATH=/usr/local/Ascend/ascend-toolkit/latest + fi +fi + +export ASCEND_TOOLKIT_HOME=${_ASCEND_INSTALL_PATH} +export ASCEND_HOME_PATH=${_ASCEND_INSTALL_PATH} +echo "Current compile soc version is ${SOC_VERSION}" +source ${_ASCEND_INSTALL_PATH}/bin/setenv.bash +if [ "${RUN_MODE}" = "sim" ]; then + # in case of running op in simulator, use stub .so instead + export LD_LIBRARY_PATH=${_ASCEND_INSTALL_PATH}/tools/simulator/${SOC_VERSION}/lib:$LD_LIBRARY_PATH + if [ ! $CAMODEL_LOG_PATH ]; then + export CAMODEL_LOG_PATH=$(pwd)/sim_log + fi + if [ -d "$CAMODEL_LOG_PATH" ]; then + rm -rf $CAMODEL_LOG_PATH + fi + mkdir -p $CAMODEL_LOG_PATH +elif [ "${RUN_MODE}" = "cpu" ]; then + export LD_LIBRARY_PATH=${_ASCEND_INSTALL_PATH}/tools/tikicpulib/lib:${_ASCEND_INSTALL_PATH}/tools/tikicpulib/lib/${SOC_VERSION}:${_ASCEND_INSTALL_PATH}/tools/simulator/${SOC_VERSION}/lib:$LD_LIBRARY_PATH +fi + +set -e +rm -rf build out +mkdir -p build +cmake -B build \ + -DRUN_MODE=${RUN_MODE} \ + -DSOC_VERSION=${SOC_VERSION} \ + -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \ + -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} \ + -DASCEND_CANN_PACKAGE_PATH=${_ASCEND_INSTALL_PATH} +cmake --build build -j +cmake --install build + +rm -f ascendc_kernels_bbit +cp ./out/bin/ascendc_kernels_bbit ./ +rm -rf input output +mkdir -p input output +python3 scripts/gen_data.py +( + export LD_LIBRARY_PATH=$(pwd)/out/lib:$(pwd)/out/lib64:${_ASCEND_INSTALL_PATH}/lib64:$LD_LIBRARY_PATH + if [[ "$RUN_WITH_TOOLCHAIN" -eq 1 ]]; then + if [ "${RUN_MODE}" = "npu" ]; then + msprof op --application=./ascendc_kernels_bbit + elif [ "${RUN_MODE}" = "sim" ]; then + msprof op simulator --application=./ascendc_kernels_bbit + elif [ "${RUN_MODE}" = "cpu" ]; then + ./ascendc_kernels_bbit + fi + else + ./ascendc_kernels_bbit + fi +) +md5sum output/*.bin +python3 scripts/verify_result.py output/output_z.bin output/golden.bin diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/scripts/gen_data.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/scripts/gen_data.py new file mode 100644 index 0000000000000000000000000000000000000000..ce8a8f4ae6efd89f422f7de6b198243d6211c9cc --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/scripts/gen_data.py @@ -0,0 +1,56 @@ +#!/usr/bin/python3 +# coding=utf-8 +# +# Copyright (C) 2023-2025. Huawei Technologies Co., Ltd. All rights reserved. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. +# =============================================================================== + +import numpy as np +import tensorflow as tf +bfloat16 = tf.bfloat16.as_numpy_dtype +dtype_emu = {bfloat16: 0, np.float16: 1, np.float32: 2, np.int8: 3, np.int16: 4, np.int32: 5} + +def gen_golden_data_simple(): + input_shape_x = [32, 128] + input_shape_y = [1, 128] + + #input_shape_x = [14, 1] + #input_shape_y = [14, 280] + + dtype = np.int8 + + input_x = np.random.uniform(-50, 50, input_shape_x).astype(dtype) + input_y = np.random.uniform(-50, 50, input_shape_y).astype(dtype) + golden = (input_x + input_y).astype(dtype) + + if np.size(input_x) > np.size(input_y): + if input_shape_y[0] == 1: + axis = 0 + coef = np.size(input_y) + elif input_shape_y[1] == 1: + axis = 1 + coef = np.size(input_x) / np.size(input_y) + else: + if input_shape_x[0] == 1: + axis = 0 + coef = np.size(input_x) + elif input_shape_x[1] == 1: + axis = 1 + coef = np.size(input_y) / np.size(input_x) + tiling = np.array([input_shape_x[0] * input_shape_x[1], + input_shape_y[0] * input_shape_y[1], + coef, + axis, + dtype_emu[dtype]], + dtype=np.uint32) + + tiling.tofile("./input/input_tiling.bin") + input_x.tofile("./input/input_x.bin") + input_y.tofile("./input/input_y.bin") + golden.tofile("./output/golden.bin") + +if __name__ == "__main__": + gen_golden_data_simple() diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/scripts/verify_result.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/scripts/verify_result.py new file mode 100644 index 0000000000000000000000000000000000000000..277d94780190059a76b88caa2347da11d4b14c67 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddMultiCoreWithTilingBroadcast/scripts/verify_result.py @@ -0,0 +1,58 @@ +#!/usr/bin/python3 +# coding=utf-8 +# +# Copyright (C) 2023-2025. Huawei Technologies Co., Ltd. All rights reserved. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. +# =============================================================================== + +import sys +import numpy as np +import tensorflow as tf +bfloat16 = tf.bfloat16.as_numpy_dtype + +# for float16 +relative_tol = 1e-3 +absolute_tol = 1e-5 +error_tol = 1e-3 +data_type = np.int8 + +def verify_result(output, golden): + output = np.fromfile(output, dtype=data_type).reshape(-1) + golden = np.fromfile(golden, dtype=data_type).reshape(-1) + if data_type == bfloat16: + output = output.astype(np.float32) + golden = golden.astype(np.float32) + different_element_results = np.isclose(output, + golden, + rtol=relative_tol, + atol=absolute_tol, + equal_nan=True) + different_element_indexes = np.where(different_element_results == False)[0] + for index in range(len(different_element_indexes)): + real_index = different_element_indexes[index] + golden_data = golden[real_index] + output_data = output[real_index] + print( + "data index: %06d, expected: %-.9f, actual: %-.9f, rdiff: %-.6f" % + (real_index, golden_data, output_data, + abs(output_data - golden_data) / golden_data)) + if index == 100: + break + error_ratio = float(different_element_indexes.size) / golden.size + print("error ratio: %.4f, tolrence: %.4f" % (error_ratio, error_tol)) + return error_ratio <= error_tol + + +if __name__ == '__main__': + try: + res = verify_result(sys.argv[1], sys.argv[2]) + if not res: + raise ValueError("[ERROR] result error") + else: + print("test pass") + except Exception as e: + print(e) + sys.exit(1) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/CMakeLists.txt b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/CMakeLists.txt similarity index 100% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/CMakeLists.txt rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/CMakeLists.txt diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/README.md b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/README.md similarity index 81% rename from operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/README.md rename to operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/README.md index 56d20ae886c58c54ea5484e60407a0b3e61d07dc..b2fe9aaefbb52df359b19f9149c5703a5a3a39c9 100644 --- a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/AddKernelInvocationTilingNeo/README.md +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/README.md @@ -1,11 +1,10 @@ ## 目录结构介绍 ``` -├── AddKernelInvocationTilingNeo +├── VectorAddSingleCore │ ├── cmake // 编译工程文件 │ ├── scripts │ │ ├── gen_data.py // 输入数据和真值数据生成脚本 │ │ └── verify_result.py // 验证输出数据和真值数据是否一致的验证脚本 -│ ├── add_custom_tiling.h // 算子tiling实现 │ ├── add_custom.cpp // 算子kernel实现 │ ├── CMakeLists.txt // 编译工程文件 │ ├── data_utils.h // 数据读入写出函数 @@ -21,8 +20,6 @@ 计算逻辑是：Ascend C提供的矢量计算接口的操作元素都为LocalTensor，输入数据需要先搬运进片上存储，然后使用计算接口完成两个输入参数相加，得到最终结果，再搬出到外部存储上。 Add算子的实现流程分为3个基本任务：CopyIn，Compute，CopyOut。CopyIn任务负责将Global Memory上的输入Tensor xGm和yGm搬运到Local Memory，分别存储在xLocal、yLocal，Compute任务负责对xLocal、yLocal执行加法操作，计算结果存储在zLocal中，CopyOut任务负责将输出数据从zLocal搬运至Global Memory上的输出Tensor zGm中。具体请参考[add_custom.cpp](./add_custom.cpp)。 -- tiling实现 - TilingData参数设计，TilingData参数本质上是和并行数据切分相关的参数，本示例算子使用了2个tiling参数：totalLength、tileNum。totalLength是指需要计算的数据量大小，tileNum是指每个核上总计算数据分块个数。比如，totalLength这个参数传递到kernel侧后，可以通过除以参与计算的核数，得到每个核上的计算量，这样就完成了多核数据的切分。tiling实现代码中通过上下文获取输入输出的shape信息，并对应设置TilingData。 - 调用实现 1. CPU侧运行验证主要通过ICPU_RUN_KF CPU调测宏等CPU调测库提供的接口来完成； @@ -34,7 +31,7 @@ - 打开样例目录 以命令行方式下载样例代码，master分支为例。 ```bash - cd ${git_clone_path}/samples/operator/AddCustomSample/KernelLaunch/AddKernelInvocationTilingNeo + cd ${git_clone_path}/samples/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/ ``` - 配置环境变量 diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/add_custom.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/add_custom.cpp new file mode 100644 index 0000000000000000000000000000000000000000..968a4dc16bf8ff25c13b83df31c3fb5cb15f683f --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/add_custom.cpp @@ -0,0 +1,81 @@ +/** + * @file add_custom.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include "kernel_operator.h" +constexpr uint32_t TOTAL_LENGTH = 2048; + +class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z) + { + xGm.SetGlobalBuffer((__gm__ half *)x, TOTAL_LENGTH); + yGm.SetGlobalBuffer((__gm__ half *)y, TOTAL_LENGTH); + zGm.SetGlobalBuffer((__gm__ half *)z, TOTAL_LENGTH); + + pipe.InitBuffer(inQueueX, 1, TOTAL_LENGTH * sizeof(half)); + pipe.InitBuffer(inQueueY, 1, TOTAL_LENGTH * sizeof(half)); + pipe.InitBuffer(outQueueZ, 1, TOTAL_LENGTH * sizeof(half)); + } + __aicore__ inline void Process() + { + CopyIn(); + Compute(); + CopyOut(); + } + +private: + __aicore__ inline void CopyIn() + { + AscendC::LocalTensor xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopy(xLocal, xGm, TOTAL_LENGTH); + AscendC::DataCopy(yLocal, yGm, TOTAL_LENGTH); + + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute() + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::Add(zLocal, xLocal, yLocal, TOTAL_LENGTH); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut() + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopy(zGm, zLocal, TOTAL_LENGTH); + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; +}; + +extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z) +{ + KernelAdd op; + op.Init(x, y, z); + op.Process(); +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/cmake/cpu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/cmake/cpu_lib.cmake new file mode 100644 index 0000000000000000000000000000000000000000..5362c8b5a53b1f730ac6fe542ee226a42dff40ff --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/cmake/cpu_lib.cmake @@ -0,0 +1,9 @@ +if(NOT DEFINED ENV{CMAKE_PREFIX_PATH}) + set(CMAKE_PREFIX_PATH ${ASCEND_CANN_PACKAGE_PATH}/tools/tikicpulib/lib/cmake) +endif() +find_package(tikicpulib REQUIRED) + +add_library(ascendc_kernels_${RUN_MODE} SHARED ${KERNEL_FILES}) +target_link_libraries(ascendc_kernels_${RUN_MODE} PUBLIC tikicpulib::${SOC_VERSION}) +target_compile_options(ascendc_kernels_${RUN_MODE} PRIVATE -g -O0 -std=c++17) +install(TARGETS ascendc_kernels_${RUN_MODE} DESTINATION ${CMAKE_INSTALL_LIBDIR}) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/cmake/npu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/cmake/npu_lib.cmake new file mode 100644 index 0000000000000000000000000000000000000000..f92b095d1f4f258af274b98dfcba2dccf6165b30 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/cmake/npu_lib.cmake @@ -0,0 +1,11 @@ +if(EXISTS ${ASCEND_CANN_PACKAGE_PATH}/compiler/tikcpp/ascendc_kernel_cmake) + set(ASCENDC_CMAKE_DIR ${ASCEND_CANN_PACKAGE_PATH}/compiler/tikcpp/ascendc_kernel_cmake) +elseif(EXISTS ${ASCEND_CANN_PACKAGE_PATH}/tools/tikcpp/ascendc_kernel_cmake) + set(ASCENDC_CMAKE_DIR ${ASCEND_CANN_PACKAGE_PATH}/tools/tikcpp/ascendc_kernel_cmake) +else() + message(FATAL_ERROR "ascendc_kernel_cmake does not exist ,please check whether the cann package is installed") +endif() +include(${ASCENDC_CMAKE_DIR}/ascendc.cmake) + +# ascendc_library use to add kernel file to generate ascendc library +ascendc_library(ascendc_kernels_${RUN_MODE} SHARED ${KERNEL_FILES}) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/data_utils.h b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/data_utils.h new file mode 100644 index 0000000000000000000000000000000000000000..9d34457807dda2d0c79ce19eadc7fcbd4667ece2 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/data_utils.h @@ -0,0 +1,203 @@ +/** + * @file data_utils.h + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#ifndef DATA_UTILS_H +#define DATA_UTILS_H +#include +#include +#include + +#include +#include +#include +#include +#include +#include +#include + +#include "acl/acl.h" + +typedef enum { + DT_UNDEFINED = -1, + FLOAT = 0, + HALF = 1, + INT8_T = 2, + INT32_T = 3, + UINT8_T = 4, + INT16_T = 6, + UINT16_T = 7, + UINT32_T = 8, + INT64_T = 9, + UINT64_T = 10, + DOUBLE = 11, + BOOL = 12, + STRING = 13, + COMPLEX64 = 16, + COMPLEX128 = 17, + BF16 = 27 +} printDataType; + +#define INFO_LOG(fmt, args...) fprintf(stdout, "[INFO] " fmt "\n", ##args) +#define WARN_LOG(fmt, args...) fprintf(stdout, "[WARN] " fmt "\n", ##args) +#define ERROR_LOG(fmt, args...) fprintf(stdout, "[ERROR] " fmt "\n", ##args) +#define CHECK_ACL(x) \ + do { \ + aclError __ret = x; \ + if (__ret != ACL_ERROR_NONE) { \ + std::cerr << __FILE__ << ":" << __LINE__ << " aclError:" << __ret << std::endl; \ + } \ + } while (0); + +/** + * @brief Read data from file + * @param [in] filePath: file path + * @param [out] fileSize: file size + * @return read result + */ +bool ReadFile(const std::string &filePath, size_t &fileSize, void *buffer, size_t bufferSize) +{ + struct stat sBuf; + int fileStatus = stat(filePath.data(), &sBuf); + if (fileStatus == -1) { + ERROR_LOG("failed to get file"); + return false; + } + if (S_ISREG(sBuf.st_mode) == 0) { + ERROR_LOG("%s is not a file, please enter a file", filePath.c_str()); + return false; + } + + std::ifstream file; + file.open(filePath, std::ios::binary); + if (!file.is_open()) { + ERROR_LOG("Open file failed. path = %s", filePath.c_str()); + return false; + } + + std::filebuf *buf = file.rdbuf(); + size_t size = buf->pubseekoff(0, std::ios::end, std::ios::in); + if (size == 0) { + ERROR_LOG("file size is 0"); + file.close(); + return false; + } + if (size > bufferSize) { + ERROR_LOG("file size is larger than buffer size"); + file.close(); + return false; + } + buf->pubseekpos(0, std::ios::in); + buf->sgetn(static_cast(buffer), size); + fileSize = size; + file.close(); + return true; +} + +/** + * @brief Write data to file + * @param [in] filePath: file path + * @param [in] buffer: data to write to file + * @param [in] size: size to write + * @return write result + */ +bool WriteFile(const std::string &filePath, const void *buffer, size_t size) +{ + if (buffer == nullptr) { + ERROR_LOG("Write file failed. buffer is nullptr"); + return false; + } + + int fd = open(filePath.c_str(), O_RDWR | O_CREAT | O_TRUNC, S_IRUSR | S_IWRITE); + if (fd < 0) { + ERROR_LOG("Open file failed. path = %s", filePath.c_str()); + return false; + } + + size_t writeSize = write(fd, buffer, size); + (void)close(fd); + if (writeSize != size) { + ERROR_LOG("Write file Failed."); + return false; + } + + return true; +} + +template void DoPrintData(const T *data, size_t count, size_t elementsPerRow) +{ + assert(elementsPerRow != 0); + for (size_t i = 0; i < count; ++i) { + std::cout << std::setw(10) << data[i]; + if (i % elementsPerRow == elementsPerRow - 1) { + std::cout << std::endl; + } + } +} + +void DoPrintHalfData(const aclFloat16 *data, size_t count, size_t elementsPerRow) +{ + assert(elementsPerRow != 0); + for (size_t i = 0; i < count; ++i) { + std::cout << std::setw(10) << std::setprecision(6) << aclFloat16ToFloat(data[i]); + if (i % elementsPerRow == elementsPerRow - 1) { + std::cout << std::endl; + } + } +} + +void PrintData(const void *data, size_t count, printDataType dataType, size_t elementsPerRow = 16) +{ + if (data == nullptr) { + ERROR_LOG("Print data failed. data is nullptr"); + return; + } + + switch (dataType) { + case BOOL: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT8_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT8_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT16_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT16_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT32_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT32_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT64_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT64_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case HALF: + DoPrintHalfData(reinterpret_cast(data), count, elementsPerRow); + break; + case FLOAT: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case DOUBLE: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + default: + ERROR_LOG("Unsupported type: %d", dataType); + } + std::cout << std::endl; +} +#endif // DATA_UTILS_H diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/main.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/main.cpp new file mode 100644 index 0000000000000000000000000000000000000000..d0c372ba02ad65ae47e8139f43fa2df2e45d10b5 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/main.cpp @@ -0,0 +1,83 @@ +/** + * @file main.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include "data_utils.h" +#ifndef ASCENDC_CPU_DEBUG +#include "acl/acl.h" +#include "aclrtlaunch_add_custom.h" +#else +#include "tikicpulib.h" +extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z); +#endif + + +int32_t main(int32_t argc, char *argv[]) +{ + uint32_t blockDim = 1; + size_t inputByteSize = static_cast(1) * 2048 * sizeof(uint16_t); + size_t outputByteSize = static_cast(1) * 2048 * sizeof(uint16_t); + +#ifdef ASCENDC_CPU_DEBUG + uint8_t *x = (uint8_t *)AscendC::GmAlloc(inputByteSize); + uint8_t *y = (uint8_t *)AscendC::GmAlloc(inputByteSize); + uint8_t *z = (uint8_t *)AscendC::GmAlloc(outputByteSize); + + ReadFile("./input/input_x.bin", inputByteSize, x, inputByteSize); + ReadFile("./input/input_y.bin", inputByteSize, y, inputByteSize); + + AscendC::SetKernelMode(KernelMode::AIV_MODE); + ICPU_RUN_KF(add_custom, blockDim, x, y, z); // use this macro for cpu debug + + WriteFile("./output/output_z.bin", z, outputByteSize); + + AscendC::GmFree((void *)x); + AscendC::GmFree((void *)y); + AscendC::GmFree((void *)z); +#else + CHECK_ACL(aclInit(nullptr)); + int32_t deviceId = 0; + CHECK_ACL(aclrtSetDevice(deviceId)); + aclrtStream stream = nullptr; + CHECK_ACL(aclrtCreateStream(&stream)); + + uint8_t *xHost, *yHost, *zHost; + uint8_t *xDevice, *yDevice, *zDevice; + + CHECK_ACL(aclrtMallocHost((void **)(&xHost), inputByteSize)); + CHECK_ACL(aclrtMallocHost((void **)(&yHost), inputByteSize)); + CHECK_ACL(aclrtMallocHost((void **)(&zHost), outputByteSize)); + CHECK_ACL(aclrtMalloc((void **)&xDevice, inputByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + CHECK_ACL(aclrtMalloc((void **)&yDevice, inputByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + CHECK_ACL(aclrtMalloc((void **)&zDevice, outputByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + + ReadFile("./input/input_x.bin", inputByteSize, xHost, inputByteSize); + ReadFile("./input/input_y.bin", inputByteSize, yHost, inputByteSize); + + CHECK_ACL(aclrtMemcpy(xDevice, inputByteSize, xHost, inputByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); + CHECK_ACL(aclrtMemcpy(yDevice, inputByteSize, yHost, inputByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); + + ACLRT_LAUNCH_KERNEL(add_custom)(blockDim, stream, xDevice, yDevice, zDevice); + CHECK_ACL(aclrtSynchronizeStream(stream)); + + CHECK_ACL(aclrtMemcpy(zHost, outputByteSize, zDevice, outputByteSize, ACL_MEMCPY_DEVICE_TO_HOST)); + WriteFile("./output/output_z.bin", zHost, outputByteSize); + + CHECK_ACL(aclrtFree(xDevice)); + CHECK_ACL(aclrtFree(yDevice)); + CHECK_ACL(aclrtFree(zDevice)); + CHECK_ACL(aclrtFreeHost(xHost)); + CHECK_ACL(aclrtFreeHost(yHost)); + CHECK_ACL(aclrtFreeHost(zHost)); + + CHECK_ACL(aclrtDestroyStream(stream)); + CHECK_ACL(aclrtResetDevice(deviceId)); + CHECK_ACL(aclFinalize()); +#endif + return 0; +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/run.sh b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/run.sh new file mode 100644 index 0000000000000000000000000000000000000000..8fcd5973012ebe2bf99402148a89ee2ff8ec9655 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/run.sh @@ -0,0 +1,124 @@ +#!/bin/bash +CURRENT_DIR=$( + cd $(dirname ${BASH_SOURCE:-$0}) + pwd +) +cd $CURRENT_DIR + +BUILD_TYPE="Debug" +INSTALL_PREFIX="${CURRENT_DIR}/out" + +SHORT=r:,v:,i:,b:,p:, +LONG=run-mode:,soc-version:,install-path:,build-type:,install-prefix:, +OPTS=$(getopt -a --options $SHORT --longoptions $LONG -- "$@") +eval set -- "$OPTS" +SOC_VERSION="Ascend310P3" + +while :; do + case "$1" in + -r | --run-mode) + RUN_MODE="$2" + shift 2 + ;; + -v | --soc-version) + SOC_VERSION="$2" + shift 2 + ;; + -i | --install-path) + ASCEND_INSTALL_PATH="$2" + shift 2 + ;; + -b | --build-type) + BUILD_TYPE="$2" + shift 2 + ;; + -p | --install-prefix) + INSTALL_PREFIX="$2" + shift 2 + ;; + --) + shift + break + ;; + *) + echo "[ERROR] Unexpected option: $1" + break + ;; + esac +done + +RUN_MODE_LIST="cpu sim npu" +if [[ " $RUN_MODE_LIST " != *" $RUN_MODE "* ]]; then + echo "ERROR: RUN_MODE error, This sample only support specify cpu, sim or npu!" + exit -1 +fi + +VERSION_LIST="Ascend910A Ascend910B Ascend310B1 Ascend310B2 Ascend310B3 Ascend310B4 Ascend310P1 Ascend310P3 Ascend910B1 Ascend910B2 Ascend910B3 Ascend910B4" +if [[ " $VERSION_LIST " != *" $SOC_VERSION "* ]]; then + echo "ERROR: SOC_VERSION should be in [$VERSION_LIST]" + exit -1 +fi + +if [ -n "$ASCEND_INSTALL_PATH" ]; then + _ASCEND_INSTALL_PATH=$ASCEND_INSTALL_PATH +elif [ -n "$ASCEND_HOME_PATH" ]; then + _ASCEND_INSTALL_PATH=$ASCEND_HOME_PATH +else + if [ -d "$HOME/Ascend/ascend-toolkit/latest" ]; then + _ASCEND_INSTALL_PATH=$HOME/Ascend/ascend-toolkit/latest + else + _ASCEND_INSTALL_PATH=/usr/local/Ascend/ascend-toolkit/latest + fi +fi + +export ASCEND_TOOLKIT_HOME=${_ASCEND_INSTALL_PATH} +export ASCEND_HOME_PATH=${_ASCEND_INSTALL_PATH} +echo "Current compile soc version is ${SOC_VERSION}" +source ${_ASCEND_INSTALL_PATH}/bin/setenv.bash +if [ "${RUN_MODE}" = "sim" ]; then + # in case of running op in simulator, use stub .so instead + export LD_LIBRARY_PATH=${_ASCEND_INSTALL_PATH}/tools/simulator/${SOC_VERSION}/lib:$LD_LIBRARY_PATH + if [ ! $CAMODEL_LOG_PATH ]; then + export CAMODEL_LOG_PATH=$(pwd)/sim_log + fi + if [ -d "$CAMODEL_LOG_PATH" ]; then + rm -rf $CAMODEL_LOG_PATH + fi + mkdir -p $CAMODEL_LOG_PATH +elif [ "${RUN_MODE}" = "cpu" ]; then + export LD_LIBRARY_PATH=${_ASCEND_INSTALL_PATH}/tools/tikicpulib/lib:${_ASCEND_INSTALL_PATH}/tools/tikicpulib/lib/${SOC_VERSION}:${_ASCEND_INSTALL_PATH}/tools/simulator/${SOC_VERSION}/lib:$LD_LIBRARY_PATH +fi + +set -e +rm -rf build out +mkdir -p build +cmake -B build \ + -DRUN_MODE=${RUN_MODE} \ + -DSOC_VERSION=${SOC_VERSION} \ + -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \ + -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} \ + -DASCEND_CANN_PACKAGE_PATH=${_ASCEND_INSTALL_PATH} +cmake --build build -j +cmake --install build + +rm -f ascendc_kernels_bbit +cp ./out/bin/ascendc_kernels_bbit ./ +rm -rf input output +mkdir -p input output +python3 scripts/gen_data.py +( + export LD_LIBRARY_PATH=$(pwd)/out/lib:$(pwd)/out/lib64:${_ASCEND_INSTALL_PATH}/lib64:$LD_LIBRARY_PATH + if [[ "$RUN_WITH_TOOLCHAIN" -eq 1 ]]; then + if [ "${RUN_MODE}" = "npu" ]; then + msprof op --application=./ascendc_kernels_bbit + elif [ "${RUN_MODE}" = "sim" ]; then + msprof op simulator --application=./ascendc_kernels_bbit + elif [ "${RUN_MODE}" = "cpu" ]; then + ./ascendc_kernels_bbit + fi + else + ./ascendc_kernels_bbit + fi +) +md5sum output/*.bin +python3 scripts/verify_result.py output/output_z.bin output/golden.bin diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/scripts/gen_data.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/scripts/gen_data.py new file mode 100644 index 0000000000000000000000000000000000000000..a0aceb3bcb253a4a613353bcbbc12b10299fa6b8 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/scripts/gen_data.py @@ -0,0 +1,30 @@ +#!/usr/bin/python3 +# coding=utf-8 +# +# Copyright (C) 2023-2025. Huawei Technologies Co., Ltd. All rights reserved. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. +# =============================================================================== + +import numpy as np +import tensorflow as tf +bfloat16 = tf.bfloat16.as_numpy_dtype + +def gen_golden_data_simple(): + input_shape_x = [1, 2048] + input_shape_y = [1, 2048] + dtype = np.float16 + + input_x = np.random.uniform(-50, 50, input_shape_x).astype(dtype) + input_y = np.random.uniform(-50, 50, input_shape_y).astype(dtype) + golden = (input_x + input_y).astype(dtype) + + input_x.tofile("./input/input_x.bin") + input_y.tofile("./input/input_y.bin") + golden.tofile("./output/golden.bin") + + +if __name__ == "__main__": + gen_golden_data_simple() diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/scripts/verify_result.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/scripts/verify_result.py new file mode 100644 index 0000000000000000000000000000000000000000..4e1c4ad459ab05ae28add5c75045c0c09d578e6f --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/scripts/verify_result.py @@ -0,0 +1,57 @@ +#!/usr/bin/python3 +# coding=utf-8 +# +# Copyright (C) 2023-2025. Huawei Technologies Co., Ltd. All rights reserved. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. +# =============================================================================== +import sys +import numpy as np +import tensorflow as tf +bfloat16 = tf.bfloat16.as_numpy_dtype + +# for float16 +relative_tol = 1e-3 +absolute_tol = 1e-5 +error_tol = 1e-3 +data_type = bfloat16 + +def verify_result(output, golden): + output = np.fromfile(output, dtype=data_type).reshape(-1) + golden = np.fromfile(golden, dtype=data_type).reshape(-1) + if data_type == bfloat16: + output = output.astype(np.float32) + golden = golden.astype(np.float32) + different_element_results = np.isclose(output, + golden, + rtol=relative_tol, + atol=absolute_tol, + equal_nan=True) + different_element_indexes = np.where(different_element_results == False)[0] + for index in range(len(different_element_indexes)): + real_index = different_element_indexes[index] + golden_data = golden[real_index] + output_data = output[real_index] + print( + "data index: %06d, expected: %-.9f, actual: %-.9f, rdiff: %-.6f" % + (real_index, golden_data, output_data, + abs(output_data - golden_data) / golden_data)) + if index == 100: + break + error_ratio = float(different_element_indexes.size) / golden.size + print("error ratio: %.4f, tolrence: %.4f" % (error_ratio, error_tol)) + return error_ratio <= error_tol + + +if __name__ == '__main__': + try: + res = verify_result(sys.argv[1], sys.argv[2]) + if not res: + raise ValueError("[ERROR] result error") + else: + print("test pass") + except Exception as e: + print(e) + sys.exit(1) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/CMakeLists.txt b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..1e4d6de99eb77103ff1448394a307ac436a44f4c --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/CMakeLists.txt @@ -0,0 +1,44 @@ +cmake_minimum_required(VERSION 3.16) +project(Ascend_c) + +set(RUN_MODE "npu" CACHE STRING "cpu/sim/npu") +set(SOC_VERSION "Ascend310P3" CACHE STRING "system on chip type") +set(ASCEND_CANN_PACKAGE_PATH "/usr/local/Ascend/ascend-toolkit/latest" + CACHE STRING "ASCEND CANN package installation directory" +) +if(NOT CMAKE_BUILD_TYPE) + set(CMAKE_BUILD_TYPE "Debug" CACHE STRING "Build type Release/Debug (default Debug)" FORCE) +endif() +if(CMAKE_INSTALL_PREFIX STREQUAL /usr/local) + set(CMAKE_INSTALL_PREFIX "${CMAKE_CURRENT_LIST_DIR}/out" CACHE STRING "path for install()" FORCE) +endif() + +# ${KERNEL_FILES} are used to compile library, push files written by ascendc in ${KERNEL_FILES}. +# ref to cmake/npu.cmake ascendc_library, cmake/cpu.cmake add_library +file(GLOB KERNEL_FILES ${CMAKE_CURRENT_SOURCE_DIR}/add_custom.cpp) + +if("${RUN_MODE}" STREQUAL "cpu") + include(cmake/cpu_lib.cmake) +elseif("${RUN_MODE}" STREQUAL "sim" OR "${RUN_MODE}" STREQUAL "npu") + include(cmake/npu_lib.cmake) +else() + message("invalid RUN_MODE: ${RUN_MODE}") +endif() +add_executable(ascendc_kernels_bbit ${CMAKE_CURRENT_SOURCE_DIR}/main.cpp) + +target_compile_options(ascendc_kernels_bbit PRIVATE + $:-g>> + -O2 -std=c++17 -D_GLIBCXX_USE_CXX11_ABI=0 -Wall -Werror +) + +target_link_libraries(ascendc_kernels_bbit PRIVATE + $,$>:host_intf_pub>> + $:ascendcl>> + ascendc_kernels_${RUN_MODE} +) + +install(TARGETS ascendc_kernels_bbit + LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR} + ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR} + RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR} +) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/README.md b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a8f76986da2e30a3d1bf7f67e75158107a1dce9c --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/README.md @@ -0,0 +1,72 @@ +## 目录结构介绍 +``` +├── VectorAddSingleCore +│ ├── cmake // 编译工程文件 +│ ├── scripts +│ │ ├── gen_data.py // 输入数据和真值数据生成脚本 +│ │ └── verify_result.py // 验证输出数据和真值数据是否一致的验证脚本 +│ ├── add_custom.cpp // 算子kernel实现 +│ ├── CMakeLists.txt // 编译工程文件 +│ ├── data_utils.h // 数据读入写出函数 +│ ├── main.cpp // 主函数，调用算子的应用程序，含CPU域及NPU域调用 +│ └── run.sh // 编译运行算子的脚本 +``` +## 代码实现介绍 +- kernel实现 + Add算子的数学表达式为： + ``` + z = x + y + ``` + 计算逻辑是：Ascend C提供的矢量计算接口的操作元素都为LocalTensor，输入数据需要先搬运进片上存储，然后使用Cast接口进行数据转换，并将结果存入临时内存中。之后再调用计算接口完成两个输入参数相加，得到最终结果，再搬出到外部存储上。 + + Add算子的实现流程分为3个基本任务：CopyIn，Compute，CopyOut。 + - CopyIn任务负责将Global Memory上的输入Tensor xGm和yGm搬运到Local Memory，分别存储在xLocal、yLocal； + - Compute任务负责对xLocal、yLocal进行类型转换，并执行加法操作，计算结果存储在zLocal中； + - CopyOut任务负责将输出数据从zLocal搬运至Global Memory上的输出Tensor zGm中。具体请参考[add_custom.cpp](./add_custom.cpp)。 + +- 调用实现 + 1. CPU侧运行验证主要通过ICPU_RUN_KF CPU调测宏等CPU调测库提供的接口来完成； + 2. NPU侧运行验证主要通过使用ACLRT_LAUNCH_KERNEL内核调用宏来完成。 + + 应用程序通过ASCENDC_CPU_DEBUG 宏区分代码逻辑运行于CPU侧还是NPU侧。 + +## 运行样例算子 + - 打开样例目录 + 以命令行方式下载样例代码，master分支为例。 + ```bash + cd ${git_clone_path}/samples/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCore/ + ``` + - 配置环境变量 + + 请根据当前环境上CANN开发套件包的[安装方式](https://hiascend.com/document/redirect/CannCommunityInstSoftware)，选择对应配置环境变量的命令。 + - 默认路径，root用户安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=/usr/local/Ascend/ascend-toolkit/latest + ``` + - 默认路径，非root用户安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=$HOME/Ascend/ascend-toolkit/latest + ``` + - 指定路径install_path，安装CANN软件包 + ```bash + export ASCEND_INSTALL_PATH=${install_path}/ascend-toolkit/latest + ``` + + 配置仿真模式日志文件目录，默认为sim_log。 + ```bash + export CAMODEL_LOG_PATH=./sim_log + ``` + + - 样例执行 + + ```bash + bash run.sh -r [RUN_MODE] -v [SOC_VERSION] + ``` + - RUN_MODE：编译方式，可选择CPU调试，NPU仿真，NPU上板。支持参数为[cpu / sim / npu]，默认值为npu。 + - SOC_VERSION：昇腾AI处理器型号，如果无法确定具体的[SOC_VERSION]，则在安装昇腾AI处理器的服务器执行npu-smi info命令进行查询，在查询到的“Name”前增加Ascend信息，例如“Name”对应取值为xxxyy，实际配置的[SOC_VERSION]值为Ascendxxxyy。支持以下产品型号： + - Atlas A2训练系列产品/Atlas 800I A2推理产品 + + 示例如下，Ascendxxxyy请替换为实际的AI处理器型号。 + ```bash + bash run.sh -r cpu -v Ascendxxxyy + ``` \ No newline at end of file diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/add_custom.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/add_custom.cpp new file mode 100644 index 0000000000000000000000000000000000000000..948da72bce57250832dc76ab03bd69f05f51902d --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/add_custom.cpp @@ -0,0 +1,95 @@ +/** + * @file add_custom.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include "kernel_operator.h" +constexpr uint32_t TOTAL_LENGTH = 2048; + + +class KernelAdd { +public: + __aicore__ inline KernelAdd() {} + __aicore__ inline void Init(GM_ADDR x, GM_ADDR y, GM_ADDR z) + { + xGm.SetGlobalBuffer((__gm__ bfloat16_t *)x, TOTAL_LENGTH); + yGm.SetGlobalBuffer((__gm__ bfloat16_t *)y, TOTAL_LENGTH); + zGm.SetGlobalBuffer((__gm__ bfloat16_t *)z, TOTAL_LENGTH); + + pipe.InitBuffer(inQueueX, 1, TOTAL_LENGTH * sizeof(bfloat16_t)); + pipe.InitBuffer(inQueueY, 1, TOTAL_LENGTH * sizeof(bfloat16_t)); + pipe.InitBuffer(outQueueZ, 1, TOTAL_LENGTH * sizeof(bfloat16_t)); + + pipe.InitBuffer(tmpBuf0, TOTAL_LENGTH * sizeof(float)); + pipe.InitBuffer(tmpBuf1, TOTAL_LENGTH * sizeof(float)); + } + __aicore__ inline void Process() + { + CopyIn(); + Compute(); + CopyOut(); + } + +private: + __aicore__ inline void CopyIn() + { + AscendC::LocalTensor xLocal = inQueueX.AllocTensor(); + AscendC::LocalTensor yLocal = inQueueY.AllocTensor(); + + AscendC::DataCopy(xLocal, xGm, TOTAL_LENGTH); + AscendC::DataCopy(yLocal, yGm, TOTAL_LENGTH); + + inQueueX.EnQue(xLocal); + inQueueY.EnQue(yLocal); + } + __aicore__ inline void Compute() + { + AscendC::LocalTensor xLocal = inQueueX.DeQue(); + AscendC::LocalTensor yLocal = inQueueY.DeQue(); + AscendC::LocalTensor zLocal = outQueueZ.AllocTensor(); + + AscendC::LocalTensor tmpTensor0 = tmpBuf0.Get(); + AscendC::LocalTensor tmpTensor1 = tmpBuf1.Get(); + + AscendC::Cast(tmpTensor0, xLocal, AscendC::RoundMode::CAST_NONE, TOTAL_LENGTH); + AscendC::Cast(tmpTensor1, yLocal, AscendC::RoundMode::CAST_NONE, TOTAL_LENGTH); + + AscendC::Add(tmpTensor0, tmpTensor0, tmpTensor1, TOTAL_LENGTH); + AscendC::Cast(zLocal, tmpTensor0, AscendC::RoundMode::CAST_RINT, TOTAL_LENGTH); + + outQueueZ.EnQue(zLocal); + inQueueX.FreeTensor(xLocal); + inQueueY.FreeTensor(yLocal); + } + __aicore__ inline void CopyOut() + { + AscendC::LocalTensor zLocal = outQueueZ.DeQue(); + AscendC::DataCopy(zGm, zLocal, TOTAL_LENGTH); + outQueueZ.FreeTensor(zLocal); + } + +private: + AscendC::TPipe pipe; + + AscendC::TQue inQueueX; + AscendC::TQue inQueueY; + AscendC::TQue outQueueZ; + + AscendC::TBuf tmpBuf0; + AscendC::TBuf tmpBuf1; + + AscendC::GlobalTensor xGm; + AscendC::GlobalTensor yGm; + AscendC::GlobalTensor zGm; +}; + +extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z) +{ + KernelAdd op; + op.Init(x, y, z); + op.Process(); +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/cmake/cpu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/cmake/cpu_lib.cmake new file mode 100644 index 0000000000000000000000000000000000000000..5362c8b5a53b1f730ac6fe542ee226a42dff40ff --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/cmake/cpu_lib.cmake @@ -0,0 +1,9 @@ +if(NOT DEFINED ENV{CMAKE_PREFIX_PATH}) + set(CMAKE_PREFIX_PATH ${ASCEND_CANN_PACKAGE_PATH}/tools/tikicpulib/lib/cmake) +endif() +find_package(tikicpulib REQUIRED) + +add_library(ascendc_kernels_${RUN_MODE} SHARED ${KERNEL_FILES}) +target_link_libraries(ascendc_kernels_${RUN_MODE} PUBLIC tikicpulib::${SOC_VERSION}) +target_compile_options(ascendc_kernels_${RUN_MODE} PRIVATE -g -O0 -std=c++17) +install(TARGETS ascendc_kernels_${RUN_MODE} DESTINATION ${CMAKE_INSTALL_LIBDIR}) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/cmake/npu_lib.cmake b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/cmake/npu_lib.cmake new file mode 100644 index 0000000000000000000000000000000000000000..f92b095d1f4f258af274b98dfcba2dccf6165b30 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/cmake/npu_lib.cmake @@ -0,0 +1,11 @@ +if(EXISTS ${ASCEND_CANN_PACKAGE_PATH}/compiler/tikcpp/ascendc_kernel_cmake) + set(ASCENDC_CMAKE_DIR ${ASCEND_CANN_PACKAGE_PATH}/compiler/tikcpp/ascendc_kernel_cmake) +elseif(EXISTS ${ASCEND_CANN_PACKAGE_PATH}/tools/tikcpp/ascendc_kernel_cmake) + set(ASCENDC_CMAKE_DIR ${ASCEND_CANN_PACKAGE_PATH}/tools/tikcpp/ascendc_kernel_cmake) +else() + message(FATAL_ERROR "ascendc_kernel_cmake does not exist ,please check whether the cann package is installed") +endif() +include(${ASCENDC_CMAKE_DIR}/ascendc.cmake) + +# ascendc_library use to add kernel file to generate ascendc library +ascendc_library(ascendc_kernels_${RUN_MODE} SHARED ${KERNEL_FILES}) diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/data_utils.h b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/data_utils.h new file mode 100644 index 0000000000000000000000000000000000000000..9d34457807dda2d0c79ce19eadc7fcbd4667ece2 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/data_utils.h @@ -0,0 +1,203 @@ +/** + * @file data_utils.h + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#ifndef DATA_UTILS_H +#define DATA_UTILS_H +#include +#include +#include + +#include +#include +#include +#include +#include +#include +#include + +#include "acl/acl.h" + +typedef enum { + DT_UNDEFINED = -1, + FLOAT = 0, + HALF = 1, + INT8_T = 2, + INT32_T = 3, + UINT8_T = 4, + INT16_T = 6, + UINT16_T = 7, + UINT32_T = 8, + INT64_T = 9, + UINT64_T = 10, + DOUBLE = 11, + BOOL = 12, + STRING = 13, + COMPLEX64 = 16, + COMPLEX128 = 17, + BF16 = 27 +} printDataType; + +#define INFO_LOG(fmt, args...) fprintf(stdout, "[INFO] " fmt "\n", ##args) +#define WARN_LOG(fmt, args...) fprintf(stdout, "[WARN] " fmt "\n", ##args) +#define ERROR_LOG(fmt, args...) fprintf(stdout, "[ERROR] " fmt "\n", ##args) +#define CHECK_ACL(x) \ + do { \ + aclError __ret = x; \ + if (__ret != ACL_ERROR_NONE) { \ + std::cerr << __FILE__ << ":" << __LINE__ << " aclError:" << __ret << std::endl; \ + } \ + } while (0); + +/** + * @brief Read data from file + * @param [in] filePath: file path + * @param [out] fileSize: file size + * @return read result + */ +bool ReadFile(const std::string &filePath, size_t &fileSize, void *buffer, size_t bufferSize) +{ + struct stat sBuf; + int fileStatus = stat(filePath.data(), &sBuf); + if (fileStatus == -1) { + ERROR_LOG("failed to get file"); + return false; + } + if (S_ISREG(sBuf.st_mode) == 0) { + ERROR_LOG("%s is not a file, please enter a file", filePath.c_str()); + return false; + } + + std::ifstream file; + file.open(filePath, std::ios::binary); + if (!file.is_open()) { + ERROR_LOG("Open file failed. path = %s", filePath.c_str()); + return false; + } + + std::filebuf *buf = file.rdbuf(); + size_t size = buf->pubseekoff(0, std::ios::end, std::ios::in); + if (size == 0) { + ERROR_LOG("file size is 0"); + file.close(); + return false; + } + if (size > bufferSize) { + ERROR_LOG("file size is larger than buffer size"); + file.close(); + return false; + } + buf->pubseekpos(0, std::ios::in); + buf->sgetn(static_cast(buffer), size); + fileSize = size; + file.close(); + return true; +} + +/** + * @brief Write data to file + * @param [in] filePath: file path + * @param [in] buffer: data to write to file + * @param [in] size: size to write + * @return write result + */ +bool WriteFile(const std::string &filePath, const void *buffer, size_t size) +{ + if (buffer == nullptr) { + ERROR_LOG("Write file failed. buffer is nullptr"); + return false; + } + + int fd = open(filePath.c_str(), O_RDWR | O_CREAT | O_TRUNC, S_IRUSR | S_IWRITE); + if (fd < 0) { + ERROR_LOG("Open file failed. path = %s", filePath.c_str()); + return false; + } + + size_t writeSize = write(fd, buffer, size); + (void)close(fd); + if (writeSize != size) { + ERROR_LOG("Write file Failed."); + return false; + } + + return true; +} + +template void DoPrintData(const T *data, size_t count, size_t elementsPerRow) +{ + assert(elementsPerRow != 0); + for (size_t i = 0; i < count; ++i) { + std::cout << std::setw(10) << data[i]; + if (i % elementsPerRow == elementsPerRow - 1) { + std::cout << std::endl; + } + } +} + +void DoPrintHalfData(const aclFloat16 *data, size_t count, size_t elementsPerRow) +{ + assert(elementsPerRow != 0); + for (size_t i = 0; i < count; ++i) { + std::cout << std::setw(10) << std::setprecision(6) << aclFloat16ToFloat(data[i]); + if (i % elementsPerRow == elementsPerRow - 1) { + std::cout << std::endl; + } + } +} + +void PrintData(const void *data, size_t count, printDataType dataType, size_t elementsPerRow = 16) +{ + if (data == nullptr) { + ERROR_LOG("Print data failed. data is nullptr"); + return; + } + + switch (dataType) { + case BOOL: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT8_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT8_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT16_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT16_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT32_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT32_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case INT64_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case UINT64_T: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case HALF: + DoPrintHalfData(reinterpret_cast(data), count, elementsPerRow); + break; + case FLOAT: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + case DOUBLE: + DoPrintData(reinterpret_cast(data), count, elementsPerRow); + break; + default: + ERROR_LOG("Unsupported type: %d", dataType); + } + std::cout << std::endl; +} +#endif // DATA_UTILS_H diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/main.cpp b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/main.cpp new file mode 100644 index 0000000000000000000000000000000000000000..d0c372ba02ad65ae47e8139f43fa2df2e45d10b5 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/main.cpp @@ -0,0 +1,83 @@ +/** + * @file main.cpp + * + * Copyright (C) 2025. Huawei Technologies Co., Ltd. All rights reserved. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. + */ +#include "data_utils.h" +#ifndef ASCENDC_CPU_DEBUG +#include "acl/acl.h" +#include "aclrtlaunch_add_custom.h" +#else +#include "tikicpulib.h" +extern "C" __global__ __aicore__ void add_custom(GM_ADDR x, GM_ADDR y, GM_ADDR z); +#endif + + +int32_t main(int32_t argc, char *argv[]) +{ + uint32_t blockDim = 1; + size_t inputByteSize = static_cast(1) * 2048 * sizeof(uint16_t); + size_t outputByteSize = static_cast(1) * 2048 * sizeof(uint16_t); + +#ifdef ASCENDC_CPU_DEBUG + uint8_t *x = (uint8_t *)AscendC::GmAlloc(inputByteSize); + uint8_t *y = (uint8_t *)AscendC::GmAlloc(inputByteSize); + uint8_t *z = (uint8_t *)AscendC::GmAlloc(outputByteSize); + + ReadFile("./input/input_x.bin", inputByteSize, x, inputByteSize); + ReadFile("./input/input_y.bin", inputByteSize, y, inputByteSize); + + AscendC::SetKernelMode(KernelMode::AIV_MODE); + ICPU_RUN_KF(add_custom, blockDim, x, y, z); // use this macro for cpu debug + + WriteFile("./output/output_z.bin", z, outputByteSize); + + AscendC::GmFree((void *)x); + AscendC::GmFree((void *)y); + AscendC::GmFree((void *)z); +#else + CHECK_ACL(aclInit(nullptr)); + int32_t deviceId = 0; + CHECK_ACL(aclrtSetDevice(deviceId)); + aclrtStream stream = nullptr; + CHECK_ACL(aclrtCreateStream(&stream)); + + uint8_t *xHost, *yHost, *zHost; + uint8_t *xDevice, *yDevice, *zDevice; + + CHECK_ACL(aclrtMallocHost((void **)(&xHost), inputByteSize)); + CHECK_ACL(aclrtMallocHost((void **)(&yHost), inputByteSize)); + CHECK_ACL(aclrtMallocHost((void **)(&zHost), outputByteSize)); + CHECK_ACL(aclrtMalloc((void **)&xDevice, inputByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + CHECK_ACL(aclrtMalloc((void **)&yDevice, inputByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + CHECK_ACL(aclrtMalloc((void **)&zDevice, outputByteSize, ACL_MEM_MALLOC_HUGE_FIRST)); + + ReadFile("./input/input_x.bin", inputByteSize, xHost, inputByteSize); + ReadFile("./input/input_y.bin", inputByteSize, yHost, inputByteSize); + + CHECK_ACL(aclrtMemcpy(xDevice, inputByteSize, xHost, inputByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); + CHECK_ACL(aclrtMemcpy(yDevice, inputByteSize, yHost, inputByteSize, ACL_MEMCPY_HOST_TO_DEVICE)); + + ACLRT_LAUNCH_KERNEL(add_custom)(blockDim, stream, xDevice, yDevice, zDevice); + CHECK_ACL(aclrtSynchronizeStream(stream)); + + CHECK_ACL(aclrtMemcpy(zHost, outputByteSize, zDevice, outputByteSize, ACL_MEMCPY_DEVICE_TO_HOST)); + WriteFile("./output/output_z.bin", zHost, outputByteSize); + + CHECK_ACL(aclrtFree(xDevice)); + CHECK_ACL(aclrtFree(yDevice)); + CHECK_ACL(aclrtFree(zDevice)); + CHECK_ACL(aclrtFreeHost(xHost)); + CHECK_ACL(aclrtFreeHost(yHost)); + CHECK_ACL(aclrtFreeHost(zHost)); + + CHECK_ACL(aclrtDestroyStream(stream)); + CHECK_ACL(aclrtResetDevice(deviceId)); + CHECK_ACL(aclFinalize()); +#endif + return 0; +} diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/run.sh b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/run.sh new file mode 100644 index 0000000000000000000000000000000000000000..8fcd5973012ebe2bf99402148a89ee2ff8ec9655 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/run.sh @@ -0,0 +1,124 @@ +#!/bin/bash +CURRENT_DIR=$( + cd $(dirname ${BASH_SOURCE:-$0}) + pwd +) +cd $CURRENT_DIR + +BUILD_TYPE="Debug" +INSTALL_PREFIX="${CURRENT_DIR}/out" + +SHORT=r:,v:,i:,b:,p:, +LONG=run-mode:,soc-version:,install-path:,build-type:,install-prefix:, +OPTS=$(getopt -a --options $SHORT --longoptions $LONG -- "$@") +eval set -- "$OPTS" +SOC_VERSION="Ascend310P3" + +while :; do + case "$1" in + -r | --run-mode) + RUN_MODE="$2" + shift 2 + ;; + -v | --soc-version) + SOC_VERSION="$2" + shift 2 + ;; + -i | --install-path) + ASCEND_INSTALL_PATH="$2" + shift 2 + ;; + -b | --build-type) + BUILD_TYPE="$2" + shift 2 + ;; + -p | --install-prefix) + INSTALL_PREFIX="$2" + shift 2 + ;; + --) + shift + break + ;; + *) + echo "[ERROR] Unexpected option: $1" + break + ;; + esac +done + +RUN_MODE_LIST="cpu sim npu" +if [[ " $RUN_MODE_LIST " != *" $RUN_MODE "* ]]; then + echo "ERROR: RUN_MODE error, This sample only support specify cpu, sim or npu!" + exit -1 +fi + +VERSION_LIST="Ascend910A Ascend910B Ascend310B1 Ascend310B2 Ascend310B3 Ascend310B4 Ascend310P1 Ascend310P3 Ascend910B1 Ascend910B2 Ascend910B3 Ascend910B4" +if [[ " $VERSION_LIST " != *" $SOC_VERSION "* ]]; then + echo "ERROR: SOC_VERSION should be in [$VERSION_LIST]" + exit -1 +fi + +if [ -n "$ASCEND_INSTALL_PATH" ]; then + _ASCEND_INSTALL_PATH=$ASCEND_INSTALL_PATH +elif [ -n "$ASCEND_HOME_PATH" ]; then + _ASCEND_INSTALL_PATH=$ASCEND_HOME_PATH +else + if [ -d "$HOME/Ascend/ascend-toolkit/latest" ]; then + _ASCEND_INSTALL_PATH=$HOME/Ascend/ascend-toolkit/latest + else + _ASCEND_INSTALL_PATH=/usr/local/Ascend/ascend-toolkit/latest + fi +fi + +export ASCEND_TOOLKIT_HOME=${_ASCEND_INSTALL_PATH} +export ASCEND_HOME_PATH=${_ASCEND_INSTALL_PATH} +echo "Current compile soc version is ${SOC_VERSION}" +source ${_ASCEND_INSTALL_PATH}/bin/setenv.bash +if [ "${RUN_MODE}" = "sim" ]; then + # in case of running op in simulator, use stub .so instead + export LD_LIBRARY_PATH=${_ASCEND_INSTALL_PATH}/tools/simulator/${SOC_VERSION}/lib:$LD_LIBRARY_PATH + if [ ! $CAMODEL_LOG_PATH ]; then + export CAMODEL_LOG_PATH=$(pwd)/sim_log + fi + if [ -d "$CAMODEL_LOG_PATH" ]; then + rm -rf $CAMODEL_LOG_PATH + fi + mkdir -p $CAMODEL_LOG_PATH +elif [ "${RUN_MODE}" = "cpu" ]; then + export LD_LIBRARY_PATH=${_ASCEND_INSTALL_PATH}/tools/tikicpulib/lib:${_ASCEND_INSTALL_PATH}/tools/tikicpulib/lib/${SOC_VERSION}:${_ASCEND_INSTALL_PATH}/tools/simulator/${SOC_VERSION}/lib:$LD_LIBRARY_PATH +fi + +set -e +rm -rf build out +mkdir -p build +cmake -B build \ + -DRUN_MODE=${RUN_MODE} \ + -DSOC_VERSION=${SOC_VERSION} \ + -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \ + -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} \ + -DASCEND_CANN_PACKAGE_PATH=${_ASCEND_INSTALL_PATH} +cmake --build build -j +cmake --install build + +rm -f ascendc_kernels_bbit +cp ./out/bin/ascendc_kernels_bbit ./ +rm -rf input output +mkdir -p input output +python3 scripts/gen_data.py +( + export LD_LIBRARY_PATH=$(pwd)/out/lib:$(pwd)/out/lib64:${_ASCEND_INSTALL_PATH}/lib64:$LD_LIBRARY_PATH + if [[ "$RUN_WITH_TOOLCHAIN" -eq 1 ]]; then + if [ "${RUN_MODE}" = "npu" ]; then + msprof op --application=./ascendc_kernels_bbit + elif [ "${RUN_MODE}" = "sim" ]; then + msprof op simulator --application=./ascendc_kernels_bbit + elif [ "${RUN_MODE}" = "cpu" ]; then + ./ascendc_kernels_bbit + fi + else + ./ascendc_kernels_bbit + fi +) +md5sum output/*.bin +python3 scripts/verify_result.py output/output_z.bin output/golden.bin diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/scripts/gen_data.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/scripts/gen_data.py new file mode 100644 index 0000000000000000000000000000000000000000..872333fc0033d611ea7b1a9459da3f66ec10dd60 --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/scripts/gen_data.py @@ -0,0 +1,30 @@ +#!/usr/bin/python3 +# coding=utf-8 +# +# Copyright (C) 2023-2025. Huawei Technologies Co., Ltd. All rights reserved. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. +# =============================================================================== + +import numpy as np +import tensorflow as tf +bfloat16 = tf.bfloat16.as_numpy_dtype + +def gen_golden_data_simple(): + input_shape_x = [1, 2048] + input_shape_y = [1, 2048] + dtype = bfloat16 + + input_x = np.random.uniform(-50, 50, input_shape_x).astype(dtype) + input_y = np.random.uniform(-50, 50, input_shape_y).astype(dtype) + golden = (input_x + input_y).astype(dtype) + + input_x.tofile("./input/input_x.bin") + input_y.tofile("./input/input_y.bin") + golden.tofile("./output/golden.bin") + + +if __name__ == "__main__": + gen_golden_data_simple() diff --git a/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/scripts/verify_result.py b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/scripts/verify_result.py new file mode 100644 index 0000000000000000000000000000000000000000..4e1c4ad459ab05ae28add5c75045c0c09d578e6f --- /dev/null +++ b/operator/ascendc/0_introduction/21_vectoradd_kernellaunch/VectorAddSingleCoreWithTmpbuf/scripts/verify_result.py @@ -0,0 +1,57 @@ +#!/usr/bin/python3 +# coding=utf-8 +# +# Copyright (C) 2023-2025. Huawei Technologies Co., Ltd. All rights reserved. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. +# =============================================================================== +import sys +import numpy as np +import tensorflow as tf +bfloat16 = tf.bfloat16.as_numpy_dtype + +# for float16 +relative_tol = 1e-3 +absolute_tol = 1e-5 +error_tol = 1e-3 +data_type = bfloat16 + +def verify_result(output, golden): + output = np.fromfile(output, dtype=data_type).reshape(-1) + golden = np.fromfile(golden, dtype=data_type).reshape(-1) + if data_type == bfloat16: + output = output.astype(np.float32) + golden = golden.astype(np.float32) + different_element_results = np.isclose(output, + golden, + rtol=relative_tol, + atol=absolute_tol, + equal_nan=True) + different_element_indexes = np.where(different_element_results == False)[0] + for index in range(len(different_element_indexes)): + real_index = different_element_indexes[index] + golden_data = golden[real_index] + output_data = output[real_index] + print( + "data index: %06d, expected: %-.9f, actual: %-.9f, rdiff: %-.6f" % + (real_index, golden_data, output_data, + abs(output_data - golden_data) / golden_data)) + if index == 100: + break + error_ratio = float(different_element_indexes.size) / golden.size + print("error ratio: %.4f, tolrence: %.4f" % (error_ratio, error_tol)) + return error_ratio <= error_tol + + +if __name__ == '__main__': + try: + res = verify_result(sys.argv[1], sys.argv[2]) + if not res: + raise ValueError("[ERROR] result error") + else: + print("test pass") + except Exception as e: + print(e) + sys.exit(1) diff --git a/operator/ascendc/0_introduction/README.md b/operator/ascendc/0_introduction/README.md index 70a27a117ebcc2e35c51ccebb95f8a0b50ec87b1..0c9e46bf7073b9d42b51dd06320aa97811b7442d 100644 --- a/operator/ascendc/0_introduction/README.md +++ b/operator/ascendc/0_introduction/README.md @@ -34,6 +34,7 @@ | [18_unaligned_wholereduces_frameworklaunch](./18_unaligned_wholereduces_frameworklaunch) | 基于Ascend C的非对齐WholeReduceSum自定义算子及FrameworkLaunch调用样例 | Atlas A2训练系列产品/Atlas 800I A2推理产品 | [19_unaligned_wholereduces_kernellaunch](./19_unaligned_wholereduces_kernellaunch) | 基于Ascend C的非对齐WholeReduceSum自定义算子及KernelLaunch调用样例 | Atlas A2训练系列产品/Atlas 800I A2推理产品 | [20_mmad_kernellaunch](./20_mmad_kernellaunch) | 基于Ascend C基础API的Matmul自定义Cube算子及KernelLaunch调用样例 | Atlas 推理系列产品AI Core
Atlas A2训练系列产品/Atlas 800I A2推理产品 | +| [21_vectoradd_kernellaunch](./21_vectoradd_kernellaunch) | 基于Ascend C的Add多场景自定义Vector算子的KernelLaunch调用样例 | Atlas A2训练系列产品/Atlas 800I A2推理产品 ## 获取样例代码