做网站赚钱有哪些途径,网站设计文案,网络有限公司简介,精品建设课程网站一、驱动安装
1、更新系统包
sudo apt-get updatesudo apt-get upgrade
2、安装显卡驱动
使用apt方式安装驱动#xff0c;多数情况不容易成功#xff0c;
使用一下方法更佳#xff1a;
1.查看合适显卡的驱动版本
ubuntu-drivers devices
NVIDIA GeForce 驱动程序 - …一、驱动安装
1、更新系统包
sudo apt-get updatesudo apt-get upgrade
2、安装显卡驱动
使用apt方式安装驱动多数情况不容易成功
使用一下方法更佳
1.查看合适显卡的驱动版本
ubuntu-drivers devices
NVIDIA GeForce 驱动程序 - N 卡驱动 | NVIDIANVIDIA GeForce 驱动程序官方提供下载最新版的 Geforce 驱动程序可提升 PC 游戏体验和应用程序速度。更多关于更新显卡驱动程序以及显卡驱动程序下载的信息请访问 NVIDIA 官网。https://www.nvidia.cn/geforce/drivers/选择合适版本的驱动下载后直接可以安装 下载推荐版本 两种方式①有桌面的直接双击进行安装。
②命令行 sudo dpkg -i XXX.deb
2.minicoda 见前面的文章 。Miniconda — conda documentationhttps://docs.conda.io/en/latest/miniconda.html#linux-installers
3、安装cuda
查看版本对应
CUDA 12.2 Release Notes — cuda-toolkit-release-notes 12.2 documentationThe Release Notes for the CUDA Toolkit.https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html 查看pytorch版本对应
Previous PyTorch Versions | PyTorchAn open source machine learning framework that accelerates the path from research prototyping to production deployment.https://pytorch.org/get-started/previous-versions/
安装 11.7版本cuda比较通用
CUDA Toolkit 11.7 Update 1 Downloads | NVIDIA DeveloperResources CUDA Documentation/Release NotesMacOS Tools Training Sample Code Forums Archive of Previous CUDA Releases FAQ Open Source PackagesSubmit a BugTarball and Zip Archive Deliverableshttps://developer.nvidia.com/cuda-11-7-1-download-archive?target_osLinuxtarget_archx86_64DistributionUbuntutarget_version20.04target_typedeb_local
不要使用network版本安装它会直接安装最新版本使用离线安装两个时间差不多 4、安装cudnn
cuDNN Archive | NVIDIA DeveloperExplore and download past releases from cuDNN GPU-accelerated primitive library for deep neural networks.https://developer.nvidia.com/rdp/cudnn-archive
主要对应版本intel 选86_64 , 系统 20.04.只需要下载一个文件这里和老版本不太一样。同样双击就可以安装。 最后一把配置环境变量
export PATH/usr/local/cuda-11.7/bin${PATH::${PATH}}
export LD_LIBRARY_PATH/usr/local/cuda-11.7/lib64${LD_LIBRARY_PATH::${LD_LIBRARY_PATH}} torch安装参考18.04版本
Ubuntu 18.04 深度学习环境快速配置命令记录_瑾怀轩的博客-CSDN博客sudo apt-get install ubuntu-drivers-common #安装。4、在线安装不行离线安装ok。5、安装miniconda。10、安装cudann。6、初始化conda。https://blog.csdn.net/ckq707718837/article/details/130884384?spm1001.2014.3001.5502
二、驱动卸载
卸载cuda
sudo apt-get --purge remove *cuda* *cublas* *cufft* *cufile* *curand* \*cusolver* *cusparse* *gds-tools* *npp* *nvjpeg* nsight* *nvvm* 卸载nvidia驱动
sudo apt-get --purge remove *nvidia* libxnvctrl* 卸载不用的依赖包
sudo apt-get autoremove
三、可能会遇到的问题
问题一、
ERROR: An NVIDIA kernel module nvidia-uvm appears to already be loaded in your kernel
ERROR: An NVIDIA kernel module nvidia-drm appears to already be loaded in your kernel
安装驱动的报错信息为 ERROR: An NVIDIA kernel module nvidia-uvm appears to already be loaded in your kernel. This may be because it is in use (for example, by an X server, a CUDA program, or the NVIDIA Persistence Daemon), but this may also happen if your kernel was configured without support for module unloading. Please be sure to exit any programs that may be us ing the GPU(s) before attempting to upgrade your driver. If no GPU-based programs are running, you know that your k ernel supports module unloading, and you still receive this message, then an error may have occurred that has corrup ted an NVIDIA kernel modules usage count, for which the simplest remedy is to reboot your computer. or ERROR: An NVIDIA kernel module nvidia-drm appears to already be loaded in your kernel. This may be because it is in use (for example, by an X server, a CUDA program, or the NVIDIA Persistence Daemon), but this may also happen if your kernel was configured without support for module unloading. Please be sure to exit any programs that may be us ing the GPU(s) before attempting to upgrade your driver. If no GPU-based programs are running, you know that your k ernel supports module unloading, and you still receive this message, then an error may have occurred that has corrup ted an NVIDIA kernel modules usage count, for which the simplest remedy is to reboot your computer. 正常情况
解决办法如下 目的是移去kernel中包含NVIDIA的进程举个栗子
命令
lsmod | grep nvidia nvidia_uvm 995356 2 nvidia_drm 53134 0 nvidia_modeset 1195268 1 nvidia_drm nvidia 35237551 14 nvidia_modeset,nvidia_uvm drm_kms_helper 179394 2 i915,nvidia_drm drm 429744 5 i915,drm_kms_helper,nvidia,nvidia_drm 数字代表依赖进程数量卸载时需要重后置位不存在依赖项的开始卸载比如这里要从
nvidia-smi开始
sudo rmmod nvidia-drm
sudo rmmod nvidia-moddeset
sudo rmmod nvidia
现在再使用
lsmod | grep nvidia
会发现基本上没有信息了打印了如何还有就用上面的命令卸载过程中还会出现意外情况就是 某个模块被占用卸载不掉 rmmod: ERROR: Module nvidia_drm is in use 如果是 nvidia-uvm可以使用top命令查看进程kill掉进程再执行上面步骤。
如果是 nvidia-drm 会发现没在进程中这是进入无图形化界面
sudo systemctl isolate multi-user.target
这个过程可能黑屏不用慌张关机重启再尝试该操作登录账号后同样的操作
lsmod | grep nvidia
sudo rmmod nvidia-drm
也可以使用下面命令
sudo modprobe -r nvidia-drm
如果还有其他的一次性卸载完。卸载完后使用下面命令进入图形化界面
sudo systemctl start graphical.target
进入后 检查一下
lsmod | grep nvidia
没有依赖项可以安装了
问题二、安装是要注意版本安装时注意选项选择
sudo sh NVIDIA-Linux-x86_64-535.42.run -no-x-check -no-nouveau-check -no-opengl-files 后面可加参数选择选项跟着默认项选即可。
这里注意的是安装32位库会根据显卡版本修改系统内核。所以在安装前选好版本后尽量和系统推荐版本与内核版本保持一致。
查看内核版本
less /proc/version
cat /proc/driver/nvidia/version
ubuntu-drivers devices
安装好后nvidia驱动使用nvidia-smi如果不需要低版本cuda需求尽量使用nvidia-smi上面推荐的cuda版本
问题3
Failed to initialize NVML: Driver
这个问题 一般情况重启就能解决 注意前提
1、安装好显卡驱动
2、安装好cuda和cudnn
3、配置好环境变量
解决办法 关机 --》开机
如果还解决不了从头再来大概率是安装显卡驱动版本选错了或者提示选项选错了。
