『heqingchun-ubuntu系统下安装cuda与cudnn』

ubuntu系统下安装cuda与cudnn 一、安装依赖 1.更新 sudo apt update sudo apt upgrade -y 2.基础工具 sudo apt install -y build-essential python 二、安装CUDA 1.文件下载

网址

developer.nvidia /cuda-toolkit-archive

依次点击

(1)“CUDA Toolkit 11.6.2” (2)“Linux” (3)“x86_64” (4)“Ubuntu” (5)“20.04” (6)“runfile(local)”

在"Installation Instructions:"下方为下载安装指令 下载指令(文件需下载到英文路径)，如：

cd /home/heqingchun/soft/nvidia wget developer.download.nvidia /compute/cuda/11.6.2/local_installers/cuda_11.6.2_510.47.03_linux.run

在“/home/heqingchun/soft/nvidia”路径中下载得到“cuda_11.6.2_510.47.03_linux.run”文件 以下是安装时使用的指令

sudo sh cuda_11.6.2_510.47.03_linux.run 2.cuda安装 (1)赋予可执行权限 chmod 755 cuda_11.6.2_510.47.03_linux.run (2)运行安装 sudo sh cuda_11.6.2_510.47.03_linux.run

期间会弹出对话框，需手动输入"accept"回车，在之后再弹出对话框中取消勾选“Driver”

CUDA Installer │ │ - [ ] Driver │ │ [ ] 510.47.03 │ │ + [X] CUDA Toolkit 11.6 │ │ [X] CUDA Samples 11.6 │ │ [X] CUDA Demo Suite 11.6 │ │ [X] CUDA Documentation 11.6 │ │ Options │ │ Install

向下选择"install"后等待安装完毕即可。 安装完毕信息：

=========== = Summary = =========== Driver: Not Selected Toolkit: Installed in /usr/local/cuda-11.6/ Please make sure that - PATH includes /usr/local/cuda-11.6/bin - 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 the CUDA Driver. A driver of version at least 510.00 is required for CUDA 11.6 functionality to work. To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file: sudo <CudaInstaller>.run --silent --driver Logfile is /var/log/cuda-installer.log (3)配置环境变量 str='export PATH=/usr/local/cuda-11.6/bin:"$"PATH' && \ sudo sh -c "echo $str >> /etc/profile" && \ source /etc/profile && \ str='export LD_LIBRARY_PATH=/usr/local/cuda-11.6/lib64:"$"LD_LIBRARY_PATH' && \ sudo sh -c "echo $str >> /etc/profile" && \ source /etc/profile (4)重启电脑 3.验证安装 (1)版本信息 nvcc -V

显示如下:

nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2022 NVIDIA Corporation Built on Tue_Mar__8_18:18:20_PST_2022 Cuda compilation tools, release 11.6, V11.6.124 Build cuda_11.6.r11.6/compiler.31057947_0 (2)库信息 cat /usr/local/cuda/version.json

显示如下:

{ "cuda" : { "name" : "CUDA SDK", "version" : "11.6.20220318" }, "cuda_cccl" : { "name" : "CUDA C++ Core Compute Libraries", "version" : "11.6.55" }, "cuda_cudart" : { "name" : "CUDA Runtime (cudart)", "version" : "11.6.55" }, "cuda_cuobjdump" : { "name" : "cuobjdump", "version" : "11.6.124" }, "cuda_cupti" : { "name" : "CUPTI", "version" : "11.6.124" }, "cuda_cuxxfilt" : { "name" : "CUDA cu++ filt", "version" : "11.6.124" }, "cuda_demo_suite" : { "name" : "CUDA Demo Suite", "version" : "11.6.55" }, "cuda_gdb" : { "name" : "CUDA GDB", "version" : "11.6.124" }, "cuda_memcheck" : { "name" : "CUDA Memcheck", "version" : "11.6.124" }, "cuda_nsight" : { "name" : "Nsight Eclipse Plugins", "version" : "11.6.124" }, "cuda_nvcc" : { "name" : "CUDA NVCC", "version" : "11.6.124" }, "cuda_nvdisasm" : { "name" : "CUDA nvdisasm", "version" : "11.6.124" }, "cuda_nvml_dev" : { "name" : "CUDA NVML Headers", "version" : "11.6.55" }, "cuda_nvprof" : { "name" : "CUDA nvprof", "version" : "11.6.124" }, "cuda_nvprune" : { "name" : "CUDA nvprune", "version" : "11.6.124" }, "cuda_nvrtc" : { "name" : "CUDA NVRTC", "version" : "11.6.124" }, "cuda_nvtx" : { "name" : "CUDA NVTX", "version" : "11.6.124" }, "cuda_nvvp" : { "name" : "CUDA NVVP", "version" : "11.6.124" }, "cuda_samples" : { "name" : "CUDA Samples", "version" : "11.6.101" }, "cuda_sanitizer_api" : { "name" : "CUDA Compute Sanitizer API", "version" : "11.6.124" }, "libcublas" : { "name" : "CUDA cuBLAS", "version" : "11.9.2.110" }, "libcufft" : { "name" : "CUDA cuFFT", "version" : "10.7.2.124" }, "libcurand" : { "name" : "CUDA cuRAND", "version" : "10.2.9.124" }, "libcusolver" : { "name" : "CUDA cuSOLVER", "version" : "11.3.4.124" }, "libcusparse" : { "name" : "CUDA cuSPARSE", "version" : "11.7.2.124" }, "libnpp" : { "name" : "CUDA NPP", "version" : "11.6.3.124" }, "libnvjpeg" : { "name" : "CUDA nvJPEG", "version" : "11.6.2.124" }, "nsight_compute" : { "name" : "Nsight Compute", "version" : "2022.1.1.2" }, "nsight_systems" : { "name" : "Nsight Systems", "version" : "2021.5.2.53" }, "nvidia_driver" : { "name" : "NVIDIA Linux Driver", "version" : "510.47.03" } } (3)计算能力 cd /usr/local/cuda/extras/demo_suite ./deviceQuery

显示:

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.6, CUDA Runtime Version = 11.6, NumDevs = 1, Device0 = NVIDIA GeForce RTX 3050 Laptop GPU Result = PASS

CUDA安装完毕

三、安装cuDNN 1.文件下载

网址

developer.nvidia /rdp/cudnn-archive

依次点击

(1)“Download cuDNN v8.4.0 (April 1st, 2022), for CUDA 11.x” (2)“Local Installer for Linux x86_64 (Tar)”

注:需要登陆，登陆成功后即可下载 下载得到“cudnn-linux-x86_64-8.4.0.27_cuda11.6-archive.tar.xz”文件放入“/home/heqingchun/soft/nvidia”目录

2.cuDNN安装

进入文件所在目录、解压文件、解压后进入文件夹、拷贝文件

cd /home/heqingchun/soft/nvidia tar -xvf cudnn-linux-x86_64-8.4.0.27_cuda11.6-archive.tar.xz && \ cd cudnn-linux-x86_64-8.4.0.27_cuda11.6-archive && \ sudo cp include/* /usr/local/cuda-11.6/include && \ sudo cp -P lib/* /usr/local/cuda-11.6/lib64 && \ sudo chmod a+r /usr/local/cuda-11.6/include/cudnn*.h /usr/local/cuda-11.6/lib64/libcudnn*

重启电脑

3.验证安装 cat /usr/local/cuda/include/cudnn_version.h

显示如下:

/** * \file: The master cuDNN version file. */ #ifndef CUDNN_VERSION_H_ #define CUDNN_VERSION_H_ #define CUDNN_MAJOR 8 #define CUDNN_MINOR 4 #define CUDNN_PATCHLEVEL 0 #define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL) #endif /* CUDNN_VERSION_H */

cuDNN安装完毕 ubuntu系统下安装cuda与cudnn-完毕