安装NVIDIA显卡驱动CUDA磁盘分区

Posted 2020-11-28 pidgey

安装NVIDIA显卡驱动和CUDA-8.0运算平台

• 准备工作：下载安装包
  1. 查看显卡信息lspci | grep -i vga lspci -v -s 00:02.0
  2. 查看几张GPU卡 lspci | grep NVIDIA
  3. cuda_8.0.61_375.26_linux.run
  4. NVIDIA-Linux-x86_64-384.66.run
  5. 依赖kernels-3.10.0-514.21.2.el7.x86_64内核源码
     编译环境需要安装gcc

内核版本

内核下载地址 https://opsx.alibaba.com/ https://www.kernel.org/

查看内核版本 uname -r ls /boot | grep vmlinuz

查看已安装的内核包 rpm -aq | grep -i kernel

内核源码存放位置 ll /usr/src/kernels/

步骤

1. 卸载 cuda 

   sudo sh /usr/local/cuda-8.0/bin/uninstall_cuda_8.0.pl

2. 然后卸载驱动

   nvidia-installer --uninstall 

   • 命令路径 /usr/bin/nvidia-installer
   • 注意：正常卸载后，nvidia-smi 命令就没了

3. 安装内核

   解压 kernels-3.10.0-514.21.2.el7.x86_64.tar.gz 到 /usr/src/kernels/

4. 安装英伟达显卡驱动

   sudo sh NVIDIA-Linux-x86_64-384.66.run

   • 安装后可测试nvidia-smi命令

5. 安装cuda-8.0

   sudo sh cuda_8.0.61_375.26_linux.run

卸载NVIDIA-Linux-x86_64-384.66.run详细步骤

1. TODO这步不是很明白什么意思？

If you plan to no longer use the NVIDIA driver, you should make sure that no X screens are configured to use the NVIDIA X driver in your X configuration file. If you used nvidia-xconfig to configure X, it may have created a backup of your original configuration. Would you like to run nvidia-xconfig --restore-original-backup to attempt restoration of the original X configuration file? 

            [Yes]选中yes回车                              No

安装 NVIDIA-Linux-x86_64-384.66.run详细步骤

1. 进入安装包目录执行 sudo sh NVIDIA-Linux-x86_64-384.66.run

2. Accept 接受许可证并继续安装

Please read the following LICENSE and then select either "Accept" to accept the license and continue with the installation, or select "Do Not Accept" to abort the installation. 

            [Accept]选中Accept回车      Do Not Accept   

3. 安装Nvidia的32位兼容库？

Install NVIDIA‘s 32-bit compatibility libraries? 

            Yes                           [No]选中NO回车     

4.测试命令 nvidia-smi

安装 cuda_8.0.61_375.26_linux.run详细步骤

1. 进入安装包目录执行 sudo sh cuda_8.0.61_375.26_linux.run

2. 阅读协议，按s下一页，直到100%阅读完毕

3. 按照一下步骤执行

Do you accept the previously read EULA? 
accept/decline/quit: accept

Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 375.26? 
(y)es/(n)o/(q)uit: y(若已安装其它版本选择no)

Install the CUDA 8.0 Toolkit? 
(y)es/(n)o/(q)uit: y

Enter Toolkit Location 
[ default is /usr/local/cuda-8.0 ]:

Do you want to install a symbolic link at /usr/local/cuda?
(y)es/(n)o/(q)uit: n

Install the CUDA 8.0 Samples?
(y)es/(n)o/(q)uit: n

4. 耐心等待，显示如下信息安装成功

---

Installing the CUDA Toolkit in /usr/local/cuda-8.0 ...

= Summary =

Driver: Not Selected Toolkit: Installed in /usr/local/cuda-8.0 Samples: Not Selected

Please make sure that - PATH includes /usr/local/cuda-8.0/bin - LDLIBRARYPATH includes /usr/local/cuda-8.0/lib64, or, add /usr/local/>cuda-8.0/lib64 to /etc/ld.so.conf and run ldconfig as root

To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-8.0/bin

Please see CUDAInstallationGuide_Linux.pdf in /usr/local/cuda-8.0/doc/pdf for detailed information on setting up CUDA.

***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 361.00 is required for CUDA 8.0 functionality to work. To install the driver using this installer, run the following command, replacing with the name of this run file: sudo .run -silent -driver

Logfile is /tmp/cudainstall8566.log

---

5. 添加环境变量,在管理员用户根目录下，找到.bashrc文件并打开，在最后添加下面三行文本，保存退出即可

vim ~/.bashrc

# added by cuda_8.0 installer
export PATH="/usr/local/cuda-8.0/bin:$PATH"
export LD_LIBRARY_PATH="/usr/local/cuda-8.0/lib64:$LD_LIBRARY_PATH"

source ~/.bashrc

6. 检测cuda是否安装成功

• 方案一
  执行nvcc -V，若显示以下信息，则安装cuda成功

  nvcc: NVIDIA (R) Cuda compiler driver
  Copyright (c) 2005-2016 NVIDIA Corporation
  Built on TueJan1013:22:03CST_2017
  Cuda compilation tools, release 8.0, V8.0.61

• 方案二
  依次输入以下命令，测试cuda的执行结果

  cd /usr/local/cuda-8.0/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery

• 若最后显示Result = PASS，表明cuda查询显卡信息成功

• 最后执行sudo make clean清除垃圾文件，并重启终端

  ---

  CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "GeForce GTX 1080" CUDA Driver Version / Runtime Version 9.1 / 8.0 CUDA Capability Major/Minor version number: 6.1 Total amount of global memory: 8118 MBytes (8511881216 bytes) (20) Multiprocessors, (128) CUDA Cores/MP: 2560 CUDA Cores GPU Max Clock rate: 1734 MHz (1.73 GHz) Memory Clock rate: 5005 Mhz Memory Bus Width: 256-bit L2 Cache Size: 2097152 bytes Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384) Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 2048 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 2 copy engine(s) Run time limit on kernels: Yes Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device PCI Domain ID / Bus ID / location ID: 0 / 1 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

  deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.1, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GTX 1080
  Result = PASS

• 安装NVIDIA-Linux-x86_64-384.66.run提示先安装kernle-source或kernle-devel解决方案

  下载kernle-source源码包并解压到/usr/src/kernles/目录下

 

 Linux下磁盘分区，格式化以及挂载