我一直在使用带有Tesla K80 GPU的AWS EC2实例来运行TensorFlow代码。我已经安装了CUDA 9.0和cuDNN 7.1.4，我使用的是TF 1.12，所有这些都在Ubuntu 16.04上
到昨天为止一切正常，但今天看来NVidia驱动程序由于某种原因已停止运行：
ubuntu@ip-10-0-0-13:~$ nvidia-smi NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.
我检查了驱动程序：
ubuntu@ip-10-0-0-13:~$ dpkg -l | grep nvidia rc nvidia-367 367.48-0ubuntu1 amd64 NVIDIA binary driver - version 367.48 ii nvidia-396 396.37-0ubuntu1 amd64 NVIDIA binary driver - version 396.37 ii nvidia-396-dev 396.37-0ubuntu1 amd64 NVIDIA binary Xorg driver development files ii nvidia-machine-learning-repo-ubuntu1604 1.0.0-1 amd64 nvidia-machine-learning repository configuration files ii nvidia-modprobe 396.37-0ubuntu1 amd64 Load the NVIDIA kernel driver and create device files rc nvidia-opencl-icd-367 367.48-0ubuntu1 amd64 NVIDIA OpenCL ICD ii nvidia-opencl-icd-396 396.37-0ubuntu1 amd64 NVIDIA OpenCL ICD ii nvidia-prime 0.8.2 amd64 Tools to enable NVIDIA's Prime ii nvidia-settings 396.37-0ubuntu1 amd64 Tool for configuring the NVIDIA graphics driver
看来目前有2个不同的版本，这可能是个问题吗？（但是我无法理解为什么一切都可以正常工作）。
找到这个线程后，我检查了我的内核，该内核显然与该线程中提到的内核不同：
ubuntu@ip-10-0-0-13:~$ uname -a Linux ip-10-0-0-13 4.4.0-143-generic #169-Ubuntu SMP Thu Feb 7 07:56:38 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux
有没有人遇到这个问题，知道如何解决？在此先感谢您的帮助 ！
编辑：
尝试使用@Dehydrated_Mud的方法升级驱动程序时，出现以下错误：
ERROR: The installation was canceled due to the availability or presence of an alternate driver installation. Please see /var/log/nvidia-installer.log for more details.
以及日志文件的内容：
nvidia-installer log file '/var/log/nvidia-installer.log'
creation time: Thu Mar 21 10:56:46 2019
installer version: 384.183
PATH: /usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/snap/bin
nvidia-installer command line:
./nvidia-installer
--no-drm
--disable-nouveau
--dkms
--silent
--install-libglvnd
Using built-in stream user interface
-> Detected 4 CPUs online; setting concurrency level to 4.
-> Installing NVIDIA driver version 384.183.
-> The NVIDIA driver appears to have been installed previously using a different installer. To prevent potential conflicts, it is recommended either to update the existing installation using the same mechanism by which it was originally installed, or to uninstall the existing installation before installing this driver.
Please review the message provided by the maintainer of this alternate installation method and decide how to proceed:
The package that is already installed is named nvidia-396.
You can upgrade the driver by running:
`apt-get install nvidia-396 nvidia-modprobe nvidia-settings`
You can remove nvidia-396, and all related packages, by running:
`apt-get remove --purge nvidia-396 nvidia-modprobe nvidia-settings`
This package is maintained by NVIDIA (cudatools@nvidia.com).
(Answer: Abort installation)
ERROR: The installation was canceled due to the availability or presence of an alternate driver installation. Please see /var/log/nvidia-installer.log for more details.
运行apt-cache search nvidia | grep -P '^nvidia-[0-9]+\s'给出：
nvidia-331 - Transitional package for nvidia-331 nvidia-346 - Transitional package for nvidia-346 nvidia-304 - NVIDIA legacy binary driver - version 304.135 nvidia-340 - NVIDIA binary driver - version 340.107 nvidia-361 - Transitional package for nvidia-367 nvidia-352 - Transitional package for nvidia-375 nvidia-367 - Transitional package for nvidia-387 nvidia-375 - Transitional package for nvidia-418 nvidia-387 - NVIDIA binary driver - version 387.26 nvidia-418 - NVIDIA binary driver - version 418.39 nvidia-384 - NVIDIA binary driver - version 384.183 nvidia-390 - NVIDIA binary driver - version 390.116 nvidia-410 - NVIDIA binary driver - version 410.104 nvidia-396 - NVIDIA binary driver - version 396.82
Dehydrated_M.. 9
我通过更新到最新的Nvidia驱动程序来解决此问题。使用：
nvcc --version
获取cuda工具包的版本号。对于9.0，最新驱动程序是384.183，而CUDA 10.0是410.104。
然后运行：
wget http://us.download.nvidia.com/tesla/384.183/NVIDIA-Linux-x86_64-384.183.run
下载驱动程序。
然后运行：
sudo sh ./NVIDIA-Linux-x86_64-384.183.run --no-drm --disable-nouveau --dkms --silent --install-libglvnd
安装驱动程序。
跑：
nvidia-smi
检查问题是否已解决。
我通过更新到最新的Nvidia驱动程序来解决此问题。使用：
nvcc --version
获取cuda工具包的版本号。对于9.0，最新驱动程序是384.183，而CUDA 10.0是410.104。
然后运行：
wget http://us.download.nvidia.com/tesla/384.183/NVIDIA-Linux-x86_64-384.183.run
下载驱动程序。
然后运行：
sudo sh ./NVIDIA-Linux-x86_64-384.183.run --no-drm --disable-nouveau --dkms --silent --install-libglvnd
安装驱动程序。
跑：
nvidia-smi
检查问题是否已解决。
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