RUN apt-get update && apt-get install -y cuda ENV PATH="/usr/local/cuda/bin:${PATH}" ENV LD_LIBRARY_PATH="/usr/local/cuda/lib64:${LD_LIBRARY_PATH}" 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 以上代码使用了nvidia/cuda:10.0-base作为基础镜像,并在其中安装了CUDA。通过环境变量PATH...
将CUDA加入环境变量 vim ~/.bashrc export PATH=/usr/local/cuda/bin:$PATH export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PAT source ~/.bashrc 验证CUDA是否安装成功:显示Result = PASS $ /usr/local/cuda-11.8/extras/demo_suite/bandwidthTest $ /usr/local/cuda-11.8/extras/demo_suite/...
- PATH includes /usr/local/cuda-11.2/bin - LD_LIBRARY_PATH includes /usr/local/cuda-11.2/lib64, or, add /usr/local/cuda-11.2/lib64 to /etc/ld.so.conf and run ldconfig as root To uninstall the CUDA Toolkit, run cuda-uninstaller in /usr/local/cuda-11.2/bin 需要cuda环境加入到环境变量...
- LD_LIBRARY_PATH includes /usr/local/cuda-11.6/lib64, or, add /usr/local/cuda-11.6/lib64 to /etc/ld.so.conf and run ldconfig as root To uninstall the CUDA Toolkit, run cuda-uninstaller in /usr/local/cuda-11.6/bin ***WARNING: Incomplete installation! This installation did not install...
在Ubuntu上配置CUDA的环境变量,命令行输入: sudovim~/.bashrc 在末尾添加(注意:将地址里面的11.5换成自己安装的版本!): exportPATH=/usr/local/cuda-11.5/bin${PATH:+:${PATH}}exportLD_LIBRARY_PATH=/usr/local/cuda-11.5/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} ...
文件最后添加(cuda的版本号要对应的进行修改): export PATH=/usr/local/cuda-11.6/bin/${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usr/local/cuda-11.6/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} ed6786e9f6fbaf1880100c0f49b26a5.png ...
export LD_LIBRARY_PATH=${CUDA_HOME}/lib64 export PATH=${CUDA_HOME}/bin:${PATH} source ~/...
安装cuda sudo sh cuda_你的版本_linux.run 配置环境变量 sudo vim ~/.bashrc 将下面的命令复制进去 export PATH=/usr/local/cuda-10.2/bin${PATH:+:$PATH}}export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64${LD_LIBRARY_PATH:+:${LD_...
Target和Executable选择你的可执行Target Environment variables增加LD_LIBRARY_PATH,可以在WSL2命令行里查看echo $LD_LIBRARY_PATH 我的系统是:LD_LIBRARY_PATH=/mnt/e/catkin_ws/devel/lib:/opt/ros/melodic/lib:/usr/local/cuda/lib64 开心享受windows上开发ros吧...
conda install paddlepaddle-gpu==2.4.2 cudatoolkit=11.2-chttps://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/Paddle/-cconda-forge pip安装 pip install paddlepaddle-gpu==2.4.2.post112 -fhttps://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html ...