1.前提
已经安装过cuda和cudnn，现在想在不同环境（如anaconda虚拟环境）中使用不同版本的cuda并可以灵活切换。即需要安装多个cuda版本，且已经安装过一个版本的cuda。
2.实现过程
1. 下载cuda和cudnn
# cuda下载网站：https://developer.nvidia.com/cuda-toolkit-archive
# cudnn下载网站：https://developer.nvidia.com/rdp/cudnn-archive
2.安装cuda （以11.3为例）
get https://developer.download.nvidia.com/compute/cuda/11.3.0/local_installers/cuda_11.3.0_465.19.01_linux.run
sudo sh cuda_11.3.0_465.19.01_linux.run
# 文字描述过程，具体图像描述过程见参考资料（1）
# continue -> accept -> 仅选择CUDA Toolkit 11.3,其他全部取消 -> 进入Options/Toolkit Options -> 进入Change Toolkit Install Path可以看到安装路径，复制路径后enter键退出 -> 取消全部选项 -> Done -> 进入Library install path（xxx） -> 粘贴刚才复制的路径并退出 -> None -> Install -> 等待安装 -> 看到Driver：Not Selected ...Samples:Not Selected 表示安装完毕
3.安装cudnn
# 解压下载的cudnn的tgz文件
tar -zxvf cudnn-linux-x86_64-8.9.0.131_cuda11-archive.tar.xz
# 复制解压后的文件到cuda文件夹
sudo cp cuda/lib64/* /usr/local/cuda-11.3/lib64/
sudo cp cuda/include/* /usr/local/cuda-11.3/include/
# 增加读写权限
sudo chmod a+r /usr/local/cuda-11.3/include/cudnn.h
sudo chmod a+r /usr/local/cuda-11.3/lib64/libcudnn*
# 测试cudnn是否拷贝正确
cat /usr/local/cuda-11.3/include/cudnn_version.h | grep CUDNN_MAJOR -A 2
4.更换cuda版本
# home下新建一个switch-cuda.sh文件（touch switch-cuda.sh）
# 拷贝以下内容到switch-cuda.sh
#!/usr/bin/env bash
# Copyright (c) 2018 Patrick Hohenecker
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# author: Patrick Hohenecker <mail@paho.at>
# version: 2018.1
# date: May 15, 2018
set -e
# ensure that the script has been sourced rather than just executed
if [[ "${BASH_SOURCE[0]}" = "${0}" ]]; then
echo "Please use 'source' to execute switch-cuda.sh!"
exit 1
fi
INSTALL_FOLDER="/usr/local" # the location to look for CUDA installations at
TARGET_VERSION=${1} # the target CUDA version to switch to (if provided)
# if no version to switch to has been provided, then just print all available CUDA installations
if [[ -z ${TARGET_VERSION} ]]; then
echo "The following CUDA installations have been found (in '${INSTALL_FOLDER}'):"
ls -l "${INSTALL_FOLDER}" | egrep -o "cuda-[0-9]+\\.[0-9]+$" | while read -r line; do
echo "* ${line}"
done
set +e
return
# otherwise, check whether there is an installation of the requested CUDA version
elif [[ ! -d "${INSTALL_FOLDER}/cuda-${TARGET_VERSION}" ]]; then
echo "No installation of CUDA ${TARGET_VERSION} has been found!"
set +e
return
fi
# the path of the installation to use
cuda_path="${INSTALL_FOLDER}/cuda-${TARGET_VERSION}"
# filter out those CUDA entries from the PATH that are not needed anymore
path_elements=(${PATH//:/ })
new_path="${cuda_path}/bin"
for p in "${path_elements[@]}"; do
if [[ ! ${p} =~ ^${INSTALL_FOLDER}/cuda ]]; then
new_path="${new_path}:${p}"
fi
done
# filter out those CUDA entries from the LD_LIBRARY_PATH that are not needed anymore
ld_path_elements=(${LD_LIBRARY_PATH//:/ })
new_ld_path="${cuda_path}/lib64:${cuda_path}/extras/CUPTI/lib64"
for p in "${ld_path_elements[@]}"; do
if [[ ! ${p} =~ ^${INSTALL_FOLDER}/cuda ]]; then
new_ld_path="${new_ld_path}:${p}"
fi
done
# update environment variables
export CUDA_HOME="${cuda_path}"
export CUDA_ROOT="${cuda_path}"
export LD_LIBRARY_PATH="${new_ld_path}"
export PATH="${new_path}"
echo "Switched to CUDA ${TARGET_VERSION}."
set +e
return
# 查看已经安装的cuda版本
source switch-cuda.sh
# 切换到对应的版本(可在虚拟环境中使用)
source switch-cuda.sh 11.3
# 确认当前环境的cuda版本
nvcc -V
# 测试cuda和cudnn的python脚本：
import torch
from torch.backends import cudnn
#判断是否安装了cuda
print("是否安装了cuda: ",torch.cuda.is_available()) #返回True则说明已经安装了cuda
#判断是否安装了cuDNN
print("是否安装了cudnn: ",cudnn.is_available()) #返回True则说明已经安装了cuDNN
print(torch.__version__)
print(torch.version.cuda)
print(torch.backends.cudnn.version())
到这就结束啦~，创作不易，大家记得点赞收藏关注我哦~
大家的支持是up持续更新的动力~
# 如果要卸载cuda的话
sudo rm -rf /usr/local/cuda-11.3
参考资料
（1）https://zhuanlan.zhihu.com/p/581634820
（2）https://blog.csdn.net/weixin_37926734/article/details/123033286?spm=1001.2014.3001.5506
（3）https://blog.csdn.net/KRISNAT/article/details/134870009?spm=1001.2014.3001.5506
