Intro
Hi, I was recently given access to a remote machine with a GPU that I can use to accelerate my research. However, I am having a lot of trouble getting it set up. I went through the Nvidia Linux Install Guide a couple of times but am still not able to use Cuda with PyTorch (print(torch.cuda.is_available()) returns false).
Details
lspci | grep -i nvidia
00:0a.0 VGA compatible controller: NVIDIA Corporation GP102GL [Tesla P40] (rev a1)
Linux distribution is Ubuntu 16.04.6 LTS
Issue
After installation of the toolkit, I got success messages and running
nvcc --version results in
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
However, running nvidia-smi results in
NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running
I then ran
$ sudo /usr/bin/nvidia-uninstallto uninstall driversudo ./NVIDIA-Linux-x86_64–410.104.run --no-x-check
However, I got an error in the installation and these are the logs:
cat /var/log/nvidia-installer.log
nvidia-installer log file '/var/log/nvidia-installer.log'
creation time: Thu Jun 6 17:32:05 2019
installer version: 410.104
PATH: /usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/snap/bin
nvidia-installer command line:
./nvidia-installer
--no-x-check
Unable to load: nvidia-installer ncurses v6 user interface
Using: nvidia-installer ncurses user interface
-> Detected 8 CPUs online; setting concurrency level to 8.
-> Installing NVIDIA driver version 410.104.
-> Would you like to register the kernel module sources with DKMS? This will allow DKMS to automatically build a new module, if you install a different kernel later. (Answer: Yes)
WARNING: nvidia-installer was forced to guess the X library path '/usr/lib' and X module path '/usr/lib/xorg/modules'; these paths were not queryable from the system. If X fails to find the NVIDIA X driver module, please install the `pkg-config` utility and the X.Org SDK/development package for your distribution and reinstall the driver.
-> Installing both new and classic TLS OpenGL libraries.
-> Installing classic TLS 32bit OpenGL libraries.
-> Install NVIDIA's 32-bit compatibility libraries? (Answer: Yes)
-> Will install GLVND GLX client libraries.
-> Will install GLVND EGL client libraries.
-> Skipping GLX non-GLVND file: "libGL.so.410.104"
-> Skipping GLX non-GLVND file: "libGL.so.1"
-> Skipping GLX non-GLVND file: "libGL.so"
-> Skipping EGL non-GLVND file: "libEGL.so.410.104"
-> Skipping EGL non-GLVND file: "libEGL.so"
-> Skipping EGL non-GLVND file: "libEGL.so.1"
-> Skipping GLX non-GLVND file: "./32/libGL.so.410.104"
-> Skipping GLX non-GLVND file: "libGL.so.1"
-> Skipping GLX non-GLVND file: "libGL.so"
-> Skipping EGL non-GLVND file: "./32/libEGL.so.410.104"
-> Skipping EGL non-GLVND file: "libEGL.so"
-> Skipping EGL non-GLVND file: "libEGL.so.1"
Looking for install checker script at ./libglvnd_install_checker/check-libglvnd-install.sh
executing: '/bin/sh ./libglvnd_install_checker/check-libglvnd-install.sh'...
Checking for libglvnd installation.
Checking libGLdispatch...
Can't load library libGLdispatch.so.0: libGLdispatch.so.0: cannot open shared object file: No such file or directory
Will install libglvnd libraries.
Will install libEGL vendor library config file to /usr/share/glvnd/egl_vendor.d
-> Searching for conflicting files:
-> done.
-> Installing 'NVIDIA Accelerated Graphics Driver for Linux-x86_64' (410.104):
executing: '/sbin/ldconfig'...
-> done.
-> Driver file installation is complete.
-> Installing DKMS kernel module:
-> done.
ERROR: Unable to load the 'nvidia-drm' kernel module.
ERROR: Installation has failed. Please see the file '/var/log/nvidia-installer.log' for details. You may find suggestions on fixing installation problems in the README available on the Linux driver download page at www.nvidia.com
Anyone have any idea on how to fix my setup and install the driver properly so that I can get Pytorch to recognize cuda?
