新聞中心
在Linux環(huán)境下,CMake是一個常用的構(gòu)建工具,它可以幫助我們自動化構(gòu)建過程,提高開發(fā)效率,對于并行計算應用程序,我們需要特別關注一些配置技巧,以確保程序能夠正確地利用多核處理器進行并行計算,本文將介紹一些使用CMake構(gòu)建Linux并行計算應用程序的配置技巧。

1、啟用并行編譯
為了充分利用多核處理器進行編譯,我們需要在CMakeLists.txt文件中啟用并行編譯,可以通過設置CMAKE_MAKE_PROGRAM變量為"make j${NUMBER_OF_PROCESSORS}"來實現(xiàn)。
set(CMAKE_MAKE_PROGRAM "make j${NUMBER_OF_PROCESSORS}")
NUMBER_OF_PROCESSORS可以通過get_processor_count()函數(shù)獲取系統(tǒng)的處理器數(shù)量。
2、啟用并行運行測試
在執(zhí)行測試時,我們同樣希望能夠利用多核處理器進行并行運行,可以通過設置CMAKE_TEST_PARALLEL_WORKERS變量來實現(xiàn)。
set(CMAKE_TEST_PARALLEL_WORKERS ${NUMBER_OF_PROCESSORS})
3、啟用并行運行程序
在運行程序時,我們希望能夠利用多核處理器進行并行運行,可以通過設置CMAKE_BUILD_PARALLEL_LEVEL和CMAKE_RUN_PARALLEL_LEVEL變量來實現(xiàn)。
set(CMAKE_BUILD_PARALLEL_LEVEL ${NUMBER_OF_PROCESSORS})
set(CMAKE_RUN_PARALLEL_LEVEL ${NUMBER_OF_PROCESSORS})
4、使用OpenMP并行化代碼
為了實現(xiàn)真正的并行計算,我們需要在代碼中使用OpenMP庫來編寫并行化的代碼,需要在CMakeLists.txt文件中包含OpenMP庫:
find_package(OpenMP)
if (OPENMP_FOUND)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} ${OpenMP_EXE_LINKER_FLAGS}")
endif()
在需要并行化的代碼段前后添加#pragma omp parallel for指令:
#include#include #include int main() { std::vector data(100); #pragma omp parallel for for (int i = 0; i < data.size(); ++i) { data[i] = i * 2; } for (int i = 0; i < data.size(); ++i) { std::cout << data[i] << std::endl; } return 0; }
5、使用Intel TBB并行化代碼(可選)
除了OpenMP,我們還可以使用Intel TBB庫來實現(xiàn)并行計算,需要在CMakeLists.txt文件中包含TBB庫:
find_package(TBB)
if (TBB_FOUND)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TBB_CXX_FLAGS}")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${TBB_C_FLAGS}")
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} ${TBB_LIBRARIES}")
endif()
在需要并行化的代碼段前后添加tbb::parallel_for指令:
#include#include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include // For printing benchmark results to the console using CUPS API. Only needed if you want to print benchmark results to the console. You can remove this include if not needed.// If you want to print benchmark results to the console, you need to install the CUPS library and enable its support in your CMake configuration.// For example, add the following lines to your CMakeLists.txt file: find_package(CUDA REQUIRED) target_link libraries(yourTargetName PRIVATE CUDA::CUDA) target link libraries(yourTargetName PRIVATE CUPSVG) target link libraries(yourTargetName PRIVATE CUPS) target link libraries(yourTargetName PRIVATE CUPSAPI) target link libraries(yourTargetName PRIVATE CUPSNET) target link libraries(yourTargetName PRIVATE CUPSZIP) target link libraries(yourTargetName PRIVATE CUPSPDF) target link libraries(yourTargetName PRIVATE CUPSSMTP) target link libraries(yourTargetName PRIVATE CUPSPOP3) target link libraries(yourTargetName PRIVATE CUPSIMAP4) target link libraries(yourTargetName PRIVATE CUPSPRINT)// Then, in your benchmark code, you can use the following function to print benchmark results to the console using the CUPS API: void printBenchmarkResultsToConsole() { timeval start, end; gettimeofday(&start, NULL); // Your benchmark code here... gettimeofday(&end, NULL); double elapsedTime = end.tv_sec start.tv
網(wǎng)站標題:使用CMake構(gòu)建Linux并行計算應用程序的配置技巧
轉(zhuǎn)載來源:http://www.dlmjj.cn/article/djsecis.html


咨詢
建站咨詢
