The title says it all.
My goal is to install the latest Nvidia Driver and CUDA for Ubuntu 18.04 that will work with Tensorflow 2.0
Tensorflow 2.0 says it supports CUDA 10 and CUDA 10 requires Nvidia Driver 410.x or later https://www.tensorflow.org/install/gpu
I installed Nvidia Driver using ppa:
sudo add-apt-repository ppa:graphics-drivers/ppa
start->software and updates → additional drivers (gui menu)
checkmark ‘Using Nvidia driver metapackage from nvidia-driver-430 (open source)’
hit apply, software starts updating, when its done hit close, reboot computer
I installed CUDA using package manager instructions found here:
https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=debnetwork
When I run
nvidia-smi
I get:
Failed to initialize NVML: Driver/library version mismatch
According to the table here: https://docs.nvidia.com/deploy/cuda-compatibility/index.html
Cuda 10.1 should work with versions greater than 418.39, but there’s nothing newer than 10.1.105 and 418.39 mentioned, so this table is probably out of date.
My question is what driver and CUDA library combinations are recommended? Is there a more up to date driver/library compatibility table?
Prompt replies are appreciated. Thank you!