cmake -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda .. 找到CUDA,CMake正常运行: staudt ~/workspace/clutbb/cluster/build $ cmake -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda .. -- Found CUDA: /usr/local/cuda (found version "6.5") -- Found Intel TBB -- Boost version: 1.56.0 -- Found ...
不同之处在于我使用 Cmake 3.5 和 CUDA Toolkit 9.0: cmake_minimum_required(VERSION 3.5) project( myproject) find_package(CUDA 9.0 REQUIRED) if(CUDA_FOUND) list(APPEND CUDA_NVCC_FLAGS "-std=c++11") endif(CUDA_FOUND) cuda_add_library(mylib SHARED mycudalib.cu) cuda_add_executable(test_my...
Cmake错误:没有找到CUDA工具集EN对于刚接触人工智能领域不久的我而言，装 CUDA 等一些跑模型需要用到的...
CMake 旧版本中会使用find_package(CUDA)来查找 CUDA 工具包, 该命令会查找软件包路径并定义一些内置变量, 但在 CMake 3.10 版本后弃用. 在 CMake 3.17 版本后推荐使用find_package(CUDAToolkit), 能以更便利的方式添加库文件. 关于FindCUDAToolkit的详细信息可参考 CMake 官方文档 :FindCUDAToolkit - CMake 3...
安装cuda driver与cuda toolkit 具体参考nvidia官方文档,这里不再赘述。 安装完成后测试nvcc命令是否可以正常运行 nvcc --version 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) 开启CUDA支持的选项 想要cmake支持.cu文件的编译,需要在CMakeLists.txt中开启CUDA的支持...
7 packages not processed The command ‘/bin/bash -c . /opt/ros/$ROS_DISTRO/install/setup.sh && colcon build --merge-install --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release’ returned a non-zero code: 1 I noticed that the CUDA Toolkit 11.4 has an option to target ...
set(CUDA_TOOLKIT_ROOT_DIR /usr/local/cuda) # 定义cuda路径变量 # project name,指定项目的名称,一般和项目的文件夹名称对应 project(smart) add_definitions(-std=c++11) # 添加支持c++11特征 # find_package(CUDA) find_package(OpenCV REQUIRED) # 它找到OpenCV程序库之后,就会帮助我们预定义几个变量,OpenC...
Found OpenMP: TRUE (found version "2.0") -> darknet is fine for now, but uselib_track has been disabled! -> Please rebuild OpenCV from sources with CUDA support to enable it Found CUDNN: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.1/include (found version "?") ...
"C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.0/bin/nvcc.exe" is not able to compile a simple test program. I tested with visual studio 2019 + cuda 10.1, and solved the problem. @SpaceViewon ubuntu, I add set(CMAKE_CUDA_COMPILER "/usr/local/cuda-9.0/bin/nvcc") ...
$ CMAKE_ARGS="-DLLAMA_CUBLAS=on -DCUDA_PATH=/usr/local/cuda-12.2 -DCUDAToolkit_ROOT=/usr/local/cuda-12.2" FORCE_CMAKE=1 CUDA_PATH=/usr/local/cuda-12.2 CUDAToolkit_ROOT=/usr/local/cuda-12.2 pip install llama-cpp-python --no-cache-dir Collecting llama-cpp-python Downloading llama_cpp...