在使用CMake时,确保选择了与安装的CUDA工具集相匹配的CMake生成器。例如,如果安装的是Visual Studio 2019和CUDA 11.4,可以使用以下命令生成Visual Studio 2019的解决方案:cmake -G "Visual Studio 16 2019" -DCMAKE_CUDA_COMPILER="/path/to/cuda/bin/nvcc" /path/to/source 总结起来,要解决"未找到CUDA工具集...
set(CMAKE_CUDA_COMPILER "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.1/bin/nvcc") 或将以下变量添加到 Cmake: 这是我在 Linux 上成功编译的“CMakeLists.txt”文件。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_pack...
4 (found version "12.4") [cmake] -- The CUDA compiler identification is NVIDIA 12.4.99 [cmake] -- Detecting CUDA compiler ABI info [cmake] -- Detecting CUDA compiler ABI info - done [cmake] -- Check for working CUDA compiler: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v...
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...
export CMAKE_CUDA_COMPILER=$HOME/cuda_10.1/bin/nvcc 1. 2. 3. 4. 5. 【温馨提示:(也算是细节吧)将路径都用引号引起来】 保存退出后,输入命令 source ~/.bashrc 1. 最后再试试nvcc -V,当当当; 正好今天看到一句话之前想逃避的,总有一天会加倍向你席卷而来。
somisawacommentedJan 17, 2022 I solved the same error by setting CMAKE_CUDA_COMPILER. When running cmake, I rancmake . -B build -DCMAKE_CUDA_COMPILER=/usr/local/cuda-<your cuda version>/bin/nvccand then, this was solved in my case. ...
DDLE2ONNX -D__TBB_NO_IMPLICIT_LINKAGE=1 -D"CMAKE_INTDIR=\"Release\"" -Dfastdeploy_EXPORTS -D"__REL_FILE__=\"fast deploy/runtime/backends/common/cuda/adaptive_pool2d_kernel.cu\"" -D_WINDLL -D_MBCS -DWIN32 -D_WINDOWS -DNDEBUG - ...
NCNN 源码编译 cmake windows,gcc--versiong++--version如果安装了anaconda需要先屏蔽掉。1.安装CUDA9.0到NVIDIA官网下载CUDA9.0系统版本的对应的1个主安装包,4个补丁包。cd到安装包和补丁包所在的文件夹。sudoshcuda_9.0.176_384.81_linux.runsudoshcuda_9.0.176_384.8
Check for working CUDA compiler: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.7/bin/nvcc.exe - skipped Detecting CUDA compile features Detecting CUDA compile features - done CMAKE_CUDA_STANDARD=20 FoundOpenMP_C: -openmp (found version "2.0") ...
cmake 3.9.1 swig 3.0.12 一、安装CUDA 二、安装tensorflow-gpu pip install --ignore-installed --upgrade tensorflow-gpu 在CUDA_PATH后面添加bin和lib\x64路径 将cudnn64_7改为cudnn64_6 如下: #Creates a graph. a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a...