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‎.gitmodules‎

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[submodule "cmake/examples"]
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path = cmake/examples
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url = https://github.com/ttroy50/cmake-examples.git
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[submodule "submodule/cmake-examples"]
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path = submodule/cmake-examples
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url = https://github.com/ttroy50/cmake-examples
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[submodule "submodule/GenericMakefile"]
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path = submodule/GenericMakefile
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url = https://github.com/mbcrawfo/GenericMakefile
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[submodule "submodule/CMakeTutorial"]
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path = submodule/CMakeTutorial
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url = https://github.com/BrightXiaoHan/CMakeTutorial

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‎make/cmake/CMakeTutorial/.gitignore‎

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# Prerequisites
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*.d
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# Compiled Object files
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*.slo
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*.lo
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*.o
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*.obj
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# Precompiled Headers
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*.gch
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*.pch
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# Compiled Dynamic libraries
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*.so
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*.dylib
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*.dll
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# Fortran module files
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*.mod
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*.smod
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# Compiled Static libraries
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*.lai
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*.la
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*.a
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*.lib
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# Executables
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*.exe
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*.out
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*.app
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# Generate Config files
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src/config
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include/config
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# ide
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.vscode
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# build
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build/

‎make/cmake/CMakeTutorial/.gitmodules‎

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[submodule "ImportExternalProject/spdlog"]
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path = ImportExternalProject/spdlog
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url = https://github.com/gabime/spdlog.git

‎make/cmake/CMakeTutorial/CUDA/CMakeLists.txt‎

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cmake_minimum_required(VERSION 3.8)
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project(CUDA_MAT_MUL LANGUAGES CXX CUDA)
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add_library(cudaMatMul cudaMatMul.cu cudaMatMul.h)
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target_compile_features(cudaMatMul PUBLIC cxx_std_11)
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add_executable(main main.cc)
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target_link_libraries(main cudaMatMul)
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set(CMAKE_MODULE_PATH "${CMAKE_SOURCE_DIR}/cmake;${CMAKE_MODULE_PATH}")
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find_package(cuBLAS)
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add_executable(cublasMatMul cublasMatMul.cu)
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target_compile_features(cublasMatMul PRIVATE cxx_std_11)
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target_link_libraries(cublasMatMul PRIVATE ${CUBLAS_LIBRARIES})

‎make/cmake/CMakeTutorial/CUDA/README.md‎

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# CMake 编写 CUDA 应用程序
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从cmake 3.9版本开始，cmake就原生支持了cuda c/c++。再这之前，是通过find_package(CUDA REQUIRED)来间接支持cuda c/c++的。这种写法不仅繁琐而且丑陋。所以这里主要介绍3.9版本之后引入的方法，cuda c/c++程序可以使用和普通的c/c++程序完全一样的操作，甚至两者可以混合使用，非常的方便，清晰明了。
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![](./imgs/cmake_cuda_support.png)
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本文便通过一个例子（矩阵乘法运算）来具体讲解。
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## 准备工作
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#### 安装cuda driver与cuda toolkit
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具体参考nvidia官方文档，这里不再赘述。
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安装完成后测试nvcc命令是否可以正常运行
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```bash
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nvcc --version
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```
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如果不能正常运行，将cudatoolkit下的bin目录加入到环境变量中（linux下通常为/usr/local/cuda/bin）
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## 开启CUDA支持的选项
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想要cmake支持.cu文件的编译，需要在CMakeLists.txt中开启CUDA的支持选项
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```cmake
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project(CUDA_MAT_MUL LANGUAGES CXX CUDA)
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```
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如果需要编译选项支持是否开启cuda支持(即cuda为可选项)，也可以使用如下方法
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```cmake
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project(CUDA_MAT_MUL)
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if(CUDA_ENABLE)
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enable_language(CUDA)
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endif()
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```
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你可以像往常一样添加一个库
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```
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add_library(cudaMatMul cudaMatMul.cu cudaMatMul.h)
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target_compile_features(cudaMatMul PUBLIC cxx_std_11)
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```
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可以链接到普通的c++程序中
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```
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add_executable(main main.cc)
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target_link_libraries(main cudaMatMul)
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```
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## 引入cuda依赖库
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如果我们想引入英伟达官方或者第三方的cuda库时，我们也可以编写一个供find_package调用的模块。这里以引入cublas库为例，新建一个FindcuBLAS.cmake（参考Github [CLblast](https://github.com/CNugteren/CLBlast/blob/master/cmake/Modules/FindcuBLAS.cmake)）
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```cmake
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# ==================================================================================================
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# This file is part of the cuBLASt project. The project is licensed under Apache Version 2.0. This
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# project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
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# width of 100 characters per line.
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#
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# Author(s):
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# Cedric Nugteren <www.cedricnugteren.nl>
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#
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# ==================================================================================================
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#
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# Defines the following variables:
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# CUBLAS_FOUND Boolean holding whether or not the cuBLAS library was found
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# CUBLAS_INCLUDE_DIRS The CUDA and cuBLAS include directory
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# CUDA_LIBRARIES The CUDA library
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# CUBLAS_LIBRARIES The cuBLAS library
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#
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# In case CUDA is not installed in the default directory, set the CUDA_ROOT variable to point to
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# the root of cuBLAS, such that 'cublas_v2.h' can be found in $CUDA_ROOT/include. This can either be
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# done using an environmental variable (e.g. export CUDA_ROOT=/path/to/cuBLAS) or using a CMake
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# variable (e.g. cmake -DCUDA_ROOT=/path/to/cuBLAS ..).
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#
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# ==================================================================================================
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# Sets the possible install locations
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set(CUBLAS_HINTS
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${CUDA_ROOT}
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$ENV{CUDA_ROOT}
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$ENV{CUDA_TOOLKIT_ROOT_DIR}
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)
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set(CUBLAS_PATHS
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/usr
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/usr/local
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/usr/local/cuda
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)
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# Finds the include directories
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find_path(CUBLAS_INCLUDE_DIRS
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NAMES cublas_v2.h cuda.h
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HINTS ${CUBLAS_HINTS}
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PATH_SUFFIXES include inc include/x86_64 include/x64
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PATHS ${CUBLAS_PATHS}
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DOC "cuBLAS include header cublas_v2.h"
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)
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mark_as_advanced(CUBLAS_INCLUDE_DIRS)
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# Finds the libraries
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find_library(CUDA_LIBRARIES
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NAMES cudart
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HINTS ${CUBLAS_HINTS}
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PATH_SUFFIXES lib lib64 lib/x86_64 lib/x64 lib/x86 lib/Win32 lib/import lib64/import
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PATHS ${CUBLAS_PATHS}
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DOC "CUDA library"
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)
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mark_as_advanced(CUDA_LIBRARIES)
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find_library(CUBLAS_LIBRARIES
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NAMES cublas
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HINTS ${CUBLAS_HINTS}
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PATH_SUFFIXES lib lib64 lib/x86_64 lib/x64 lib/x86 lib/Win32 lib/import lib64/import
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PATHS ${CUBLAS_PATHS}
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DOC "cuBLAS library"
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)
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mark_as_advanced(CUBLAS_LIBRARIES)
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# ==================================================================================================
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# Notification messages
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if(NOT CUBLAS_INCLUDE_DIRS)
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message(STATUS "Could NOT find 'cuBLAS.h', install CUDA/cuBLAS or set CUDA_ROOT")
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endif()
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if(NOT CUDA_LIBRARIES)
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message(STATUS "Could NOT find CUDA library, install it or set CUDA_ROOT")
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endif()
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if(NOT CUBLAS_LIBRARIES)
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message(STATUS "Could NOT find cuBLAS library, install it or set CUDA_ROOT")
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endif()
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# Determines whether or not cuBLAS was found
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include(FindPackageHandleStandardArgs)
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find_package_handle_standard_args(cuBLAS DEFAULT_MSG CUBLAS_INCLUDE_DIRS CUDA_LIBRARIES CUBLAS_LIBRARIES)
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# ==================================================================================================
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```
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当我们编写需要依赖cublas库的程序时便可以这样写
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```cmake
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find_package(cuBLAS)
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add_executable(cublasMatMul cublasMatMul.cu)
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target_compile_features(cublasMatMul PRIVATE cxx_std_11)
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target_link_libraries(cublasMatMul PRIVATE ${CUBLAS_LIBRARIES})
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```
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完全和编写普通c++程序一样的体验，非常棒。

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