tesla K80 显卡驱动以及配套的cuda下载

左手的ㄟ右手 2022-04-13 06:19 818阅读 0赞

本次打算使用docker安装环境。

首先安装docker：教程——[https://blog.csdn.net/ycx901221/article/details/79936035][https_blog.csdn.net_ycx901221_article_details_79936035]

安装后，需要先启动docker：$ : service docker start

这里有一篇切换cuda版本的文章：用软链接切换的，然而，如果两个人同时使用不同版本的cuda是否要直接程序配置改cuda路径地址？

[https://blog.csdn.net/yinxingtianxia/article/details/80462892][https_blog.csdn.net_yinxingtianxia_article_details_80462892]

查看自己显卡型号：

lspci | grep -i nvidia

cudnn7.3:

[https://developer.nvidia.com/rdp/cudnn-archive\#a-collapse730-9][https_developer.nvidia.com_rdp_cudnn-archive_a-collapse730-9]

[cuDNN v7.3.0 Developer Library for Ubuntu16.04 (Deb)][cuDNN v7.3.0 Developer Library for Ubuntu16.04 _Deb]

cuda9.0：

[https://developer.nvidia.com/cuda-90-download-archive?target\_os=Linux&target\_arch=x86\_64&target\_distro=Ubuntu&target\_version=1604&target\_type=deblocal][https_developer.nvidia.com_cuda-90-download-archive_target_os_Linux_target_arch_x86_64_target_distro_Ubuntu_target_version_1604_target_type_deblocal]

驱动支持cuda9.0：

安装教程：[https://www.cnblogs.com/sp-li/p/7680526.html][https_www.cnblogs.com_sp-li_p_7680526.html]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTMyNDk4NTM_size_16_color_FFFFFF_t_70][]

Installation of the NVIDIA Accelerated Graphics Driver for Linux-x86_64 (version: 384.145) is now 
      complete.  Please update your XF86Config or xorg.conf file as appropriate; see the file           
      /usr/share/doc/NVIDIA_GLX-1.0/README.txt for details.

[https://www.nvidia.cn/Download/driverResults.aspx/135493/cn][https_www.nvidia.cn_Download_driverResults.aspx_135493_cn]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTMyNDk4NTM_size_16_color_FFFFFF_t_70 1][]

版本限制是这样的：mask的docker中用的是16.04的ubuntu。

[https_blog.csdn.net_ycx901221_article_details_79936035]: https://blog.csdn.net/ycx901221/article/details/79936035
[https_blog.csdn.net_yinxingtianxia_article_details_80462892]: https://blog.csdn.net/yinxingtianxia/article/details/80462892
[https_developer.nvidia.com_rdp_cudnn-archive_a-collapse730-9]: https://developer.nvidia.com/rdp/cudnn-archive#a-collapse730-9
[cuDNN v7.3.0 Developer Library for Ubuntu16.04 _Deb]: https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.3.0/prod/9.0_2018920/Ubuntu16_04-x64/libcudnn7-dev_7.3.0.29-1-cuda9.0_amd64
[https_developer.nvidia.com_cuda-90-download-archive_target_os_Linux_target_arch_x86_64_target_distro_Ubuntu_target_version_1604_target_type_deblocal]: https://developer.nvidia.com/cuda-90-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1604&target_type=deblocal
[https_www.cnblogs.com_sp-li_p_7680526.html]: https://www.cnblogs.com/sp-li/p/7680526.html
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTMyNDk4NTM_size_16_color_FFFFFF_t_70]: /images/20220413/5bffde4f599242c0b4c437ac91f87447.png
[https_www.nvidia.cn_Download_driverResults.aspx_135493_cn]: https://www.nvidia.cn/Download/driverResults.aspx/135493/cn
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTMyNDk4NTM_size_16_color_FFFFFF_t_70 1]: /images/20220413/2c1d6a0348bf4a14a12a5181b2b04a46.png