Then define your chart like this:
The following steps are good only if the NVIdia card is used for GPU acceleration computing only, not for display. My machine has 2 graphic cards: a Rodeon ATI (not built-in) for display and the NVIdia GForce for computing. Before starting, make sure to save all your work.
step0: Download the driver from NVIdia website.**
Make note of the directory where the file is saved (usually it is in the folder Downloads/)
step1. Get into the text-only console (TTY)
step2: Enter login and password
step3 4. kill the current X-server session
step4: 5. Optional: purge all NVidia drivers (there is no need to do that but in case you want a fresh start)
step 5: Enter runlevel 3**
step6: Run the install. Go to the directory where the file NVIDIA∗.run file is saved. If you have 1 install file, type:
It is important to include the option no-opengl--files in the command. If it is not included, the install would overwrite the opengl files used by the Graphic Card for Display. And you would end up with a machine stucked into a login loop.
**8. If some error messages prompt up, dismiss them **
9. Do not update Xconfig
You will be asked if you wish to update Xconfig: select NO. If you choose YES, the NVIdia Card will take over the display work and that will create conflicts with the other graphic card.
Otherwise, replace NVI∗.run by the full name of the file.
10. Start X-server session
11. Exit the TTY mode
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`"CTRL"` + `"ALT"` + `"F1"`
#Enter login and passwrod
sudo service lightdm stop
sudo apt-get purge nvidia-*
sudo init 3
cd {location_of_nvidia_file}
`sudo sh NVI*.run --no-opengl-files`
{ Follow the instructions }
`sudo service lightdm start`
`"CTRL"` + `"ALT"` + `"F7"`
Voila! You are all set with the installation of the driver!
The next and final step is to make sure that TensorFlow detects the GPU. Here is a short script:
The script calculates the matrix multiplication: , where a is a (2,1) and b is a (1,2) matrix.
If the GPU is detected by TF, you should see something like this:
