ubuntu20.04安装nvidia显卡驱动/CUDA/cuDNN
ubuntu20.04安装nvidia显卡驱动/CUDA/cuDNN
- 1 安装显卡驱动
-
- 1.1 禁止secure boot
- 1.2 安装闭源驱动
- 1.3 重启查看驱动
- 2 安装CUDA
-
- 2.1 下载
- 2.2 安装CUDA
- 2.3 配置环境
- 2.4 查看CUDA
- 3 安装cuDNN
-
- 3.1 下载
- 3.2 安装cuDNN
- 3.3 查看cuDNN
- 4 安装gpu版Pytorch
- 5 版本冲突解决方法
- 6 自动安装驱动的方法（简便）
1 安装显卡驱动
1.1 禁止secure boot
这一步很重要，如果bios中为enable，驱动将安装失败。
windows每次开机有可能自动开启secure boot，所以安装前要确认为禁用状态。
1.2 安装闭源驱动
- 图形模式安装
-
命令行模式安装
zjy@zjy-HP-ENVY-Laptop-13-ad0xx:~$ ubuntu-drivers devices == /sys/devices/pci0000:00/0000:00:1c.0/0000:01:00.0 == modalias : pci:v000010DEd00001D12sv0000103Csd0000834Cbc03sc02i00 vendor : NVIDIA Corporation model : GP108M [GeForce MX150] driver : nvidia-driver-390 - distro non-free driver : nvidia-driver-418-server - distro non-free driver : nvidia-driver-450-server - distro non-free driver : nvidia-driver-450 - distro non-free driver : nvidia-driver-455 - distro non-free recommended driver : nvidia-driver-440-server - distro non-free driver : xserver-xorg-video-nouveau - distro free builtin这里选择 recommended，即：
sudo apt install nvidia-driver-455
1.3 重启查看驱动
zjy@zjy-HP-ENVY-Laptop-13-ad0xx:~/桌面$ nvidia-smi
Sun Nov 29 16:12:30 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 455.38 Driver Version: 455.38 CUDA Version: 11.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce MX150 Off | 00000000:01:00.0 Off | N/A |
| N/A 58C P0 N/A / N/A | 263MiB / 2002MiB | 3% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 1337 G /usr/lib/xorg/Xorg 125MiB |
| 0 N/A N/A 1508 G /usr/bin/gnome-shell 137MiB |
+-----------------------------------------------------------------------------+
如上图所示，显卡安装成功。
如果不放心可以用下面的指令查看：
zjy@zjy-HP-ENVY-Laptop-13-ad0xx:~/桌面$ neofetch
.-/+oossssoo+/-. zjy@zjy-HP-ENVY-Laptop-13-ad0xx
`:+ssssssssssssssssss+:` -------------------------------
-+ssssssssssssssssssyyssss+- OS: Ubuntu 20.04.1 LTS x86_64
.ossssssssssssssssssdMMMNysssso. Host: HP ENVY Laptop 13-ad0xx
/ssssssssssshdmmNNmmyNMMMMhssssss/ Kernel: 5.4.0-54-generic
+ssssssssshmydMMMMMMMNddddyssssssss+ Uptime: 1 min
/sssssssshNMMMyhhyyyyhmNMMMNhssssssss/ Packages: 1741 (dpkg), 6 (snap)
.ssssssssdMMMNhsssssssssshNMMMdssssssss. Shell: bash 5.0.17
+sssshhhyNMMNyssssssssssssyNMMMysssssss+ Resolution: 2560x1440
ossyNMMMNyMMhsssssssssssssshmmmhssssssso DE: GNOME
ossyNMMMNyMMhsssssssssssssshmmmhssssssso WM: Mutter
+sssshhhyNMMNyssssssssssssyNMMMysssssss+ WM Theme: Adwaita
.ssssssssdMMMNhsssssssssshNMMMdssssssss. Theme: Yaru [GTK2/3]
/sssssssshNMMMyhhyyyyhdNMMMNhssssssss/ Icons: Yaru [GTK2/3]
+sssssssssdmydMMMMMMMMddddyssssssss+ Terminal: gnome-terminal
/ssssssssssshdmNNNNmyNMMMMhssssss/ CPU: Intel i5-7200U (4) @ 3.100GHz
.ossssssssssssssssssdMMMNysssso. GPU: Intel HD Graphics 620
-+sssssssssssssssssyyyssss+- GPU: NVIDIA GeForce MX150
`:+ssssssssssssssssss+:` Memory: 840MiB / 7715MiB
.-/+oossssoo+/-.
正确识别到了核显和独显。
2 安装CUDA
2.1 下载
下载地址：https://developer.nvidia.cn/cuda-downloads
安装指南：https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html
2.2 安装CUDA
执行：
sudo sh cuda_11.1.0_455.23.05_linux.run
x End User License Agreement x
x - x
x NVIDIA Software License Agreement and CUDA Supplement to x
x Software License Agreement. x
x x
x Preface x
x - x
x The Software License Agreement in Chapter 1 and the Supplement x
x in Chapter 2 contain license terms and conditions that govern x
x the use of NVIDIA software. By accepting this agreement, you x
x agree to comply with all the terms and conditions applicable x
x to the product(s) included herein. x
x x
x NVIDIA Driver x
x
x Do you accept the above EULA? (accept/decline/quit):
输入accept，回车。
│ CUDA Installer
│ - [ ] Driver
│ [ ] 455.23.05
│ + [X] CUDA Toolkit 11.1
│ [X] CUDA Samples 11.1
│ [X] CUDA Demo Suite 11.1
│ [X] CUDA Documentation 11.1
│ Options
│ Install
在对应选项上按空格（space）取消勾选Driver，再向下选中Install，回车。
安装完成后显示：
===========
= Summary =
===========
Driver: Not Selected
Toolkit: Installed in /usr/local/cuda-11.1/
Samples: Installed in /home/zjy/, but missing recommended libraries
Please make sure that
- PATH includes /usr/local/cuda-11.1/bin
- LD_LIBRARY_PATH includes /usr/local/cuda-11.1/lib64, or, add /usr/local/cuda-11.1/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run cuda-uninstaller in /usr/local/cuda-11.1/bin
***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least .00 is required for CUDA 11.1 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
2.3 配置环境
装完成后，需要配置环境变量，编辑~/.bashrc文件，如果其他用户需要使用cuda，再按照上述步骤添加环境变量并更新即可：
sudo gedit ~/.bashrc
在末尾添加：
export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${CUDA_HOME}/lib64
export PATH=${CUDA_HOME}/bin:${PATH}
添加后更新环境变量：
source ~/.bashrc
cuda安装目录为/usr/local/cuda-xxx，xxx为版本号，同时，cuda还会建立一个/usr/local/cuda同步链接，所以可以直接将该路径添加至环境变量，之后更换cuda版本，也不需要修改环境变量。
参考：Ubuntu18.04 LTS 使用CUDA11.1编译TensoFlow-GPU版本
2.4 查看CUDA
zjy@zjy-HP-ENVY-Laptop-13-ad0xx:~/下载$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Tue_Sep_15_19:10:02_PDT_2020
Cuda compilation tools, release 11.1, V11.1.74
Build cuda_11.1.TC455_06.29069683_0
3 安装cuDNN
3.1 下载
下载地址：https://developer.nvidia.cn/rdp/cudnn-download
这里选择cuDNN Library for Linux (x86_64)
安装指南：https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html
3.2 安装cuDNN
-
Navigate to your directory containing the cuDNN tar file.
-
Unzip the cuDNN package.
tar -xvf cudnn-linux-x86_64-8.x.x.x_cudaX.Y-archive.tar.xz -
Copy the following files into the CUDA Toolkit directory.
sudo cp cudnn-*-archive/include/cudnn*.h /usr/local/cuda/include sudo cp -P cudnn-*-archive/lib/libcudnn* /usr/local/cuda/lib64 sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
3.3 查看cuDNN
zjy@zjy-HP-ENVY-Laptop-13-ad0xx:~$ cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2
#define CUDNN_MAJOR 8
#define CUDNN_MINOR 0
#define CUDNN_PATCHLEVEL 5
--
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#endif /* CUDNN_VERSION_H */
安装成功。
4 安装gpu版Pytorch
选择对应版本的pytorch：https://pytorch.org/
在新环境中安装，并测试：
(pytorch_gpu) zjy@zjy-HP-ENVY-Laptop-13-ad0xx:~$ python
Python 3.7.9 (default, Aug 31 2020, 12:42:55)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
True #成功
5 版本冲突解决方法
Nvidia 显卡 Failed to initialize NVML Driver/library version mismatch 错误解决方案
6 自动安装驱动的方法（简便）
# zjy @ 3090-711 in ~ [12:30:32]
$ sudo ubuntu-drivers devices
== /sys/devices/pci0000:64/0000:64:00.0/0000:65:00.0/0000:66:10.0/0000:68:00.0 ==
modalias : pci:v000010DEd00002204sv000019DAsd00001625bc03sc00i00
vendor : NVIDIA Corporation
driver : nvidia-driver-470 - distro non-free
driver : nvidia-driver-470-server - distro non-free
driver : nvidia-driver-510 - distro non-free recommended
driver : xserver-xorg-video-nouveau - distro free builtin
如果是要安装recommended，则直接执行：
$ sudo ubuntu-drivers autoinstall
否则：
$ sudo apt-get install nvidia-driver-xxx
最后，记得重启，再查看nvidia-smi即可看到显卡。