I have downloaded and installed CUDA several times, and every time it fails to pass the test samples deviceQuery and checkBandwidth. Also tensorflow is never listing the GPU between accessible devices, only the CPU.
My current nvidia driver is 384.111, where as the upgraded version 384.130 always generates a library mismatch on nvidia-smi and makes ubuntu unbootable.
Every time I try to install CUDA 9.0 with the .run file, which is the only way to install it without upgrading the nvidia drivers, it finishes with an "incomplete install message.". Runs on the tests are always negative, with the following output:
Installing CUDA 9.0 .deb with dpkg from the nvidia website https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1710&target_type=deblocal it also upgrades the nvidia driver.
How can I install CUDA 9.0 for Ubuntu 17.10, with nvidia 384.111 without upgrading to 384.130, so that it correctly performs on the sample tests and allows tensorflow-gpu to access the graphic-card?
PS: Whenever I say "it fails", the error message is always "UNKNOWN ERROR"
The graphics card in my system is a NVIDIA GeForce GTX 1080
I too have gone thru similar struggles. After trying to install CUDA 9.0, 9.1, 9.2 I found each toolkit requires a specific Nvidia driver version.
The official Nvidia CUDA installation guide calls for you to uninstall your Nvidia drivers. I think it's unavoidable if you want to do a local machine install unless you use Docker + Nvidia Docker.
This will allow your local machine to keep the same Nvidia drivers, and you install your specific CUDA toolkit in different container images.
This is the approach I went with.