I have gone through the GPU tensorflow install on a dualboot system (
Windows 10 and
both OSs have roughly the same versions of drivers
Lenovo P50 laptop with Nvidia Quadro M1000M Windows 376.51 nvidia driver version Ubuntu 375.66 nvidia driver version
I train a Deep Learning Model, each training set takes a vastly different amount of time
Windows 10 + Tensorflow 1.3 GPU + CUDA = 8 min. per epoch Ubuntu 16.04 + Tensorflow 1.3 GPU + CUDA = 45 min. per epoch
Ubuntu install was via all the defaults from
apt-get (not sources install), and
My one thought so far... is that I must be using the NVIDIA GPU to paint the graphics.. and not getting to utilize ALL of the GPU for compute.. is there a way to check this? I've installed everything on both the same.. including the patches for
I'm not even clear what the issue is but it looks like the drivers are setup to use Optimus.. maybe I need to switch it into a different profile?
Idea One: I might try tomorrow is recompile tensorflow from sources.. with all CPU optimizations inside Ubuntu 16.x .. perhaps the pip install is more painful than the binary install on Windows...
Idea Two : If above does nothing, I will go into BIOS and force intel integrated graphics .. do a reinstall and try to install the noveua graphics.. kind of like this :
Seems this is an "Optimus" enabled laptop.. I cannot completely shut off the nvidia gpu for rendering, only enable hybrid mode. Perhaps I'll do a fresh install.. remove all nvidia drivers and see if I can get X working that way..?
"So I went to BIOS and set the integrated graphics as default and restart. Remember to switch the HDMI from the port on GTX1080 to that on the motherboard. Now the display works well. I successfully installed Ubuntu following its prompt guides."
When installing the NVIDIA display driver, be sure to: 1. not install the openGL libs (there are command line options with driver runfile installers or CUDA runfile installers to allow this) 2. make sure not to make any changes to the xorg.conf configuration.