Thornton Lab policies and protocols

Lab computers

Setting up Pop OS on lab machines

Use LTS releases

Using LTS releases is critical. The 6 month “developer” releases can suffer from user interface lag due to the NVIDIA drivers. We have had issues with key commands taking over one second to register in the GNOME terminal. We have had the nouveau drivers freeze up on us. We’ve seen this with multiple different card of various ages. These issues all go away (knock on wood…) with the LTS releases.

An no, “force full composition” (in the NVIDIA X server settings) doesn’t fully solve these problems.

The procedure is simple:

• Download LTS release and flash it to a USB drive.
• Reboot and install.
• Use the advanced install options to custom partition the drives if needed.

It is possible that the boot device order will need to be adjusted in the machine’s BIOS!

Prior to such an install, it is prudent to:

• Back up /home to one of the secondary drives. To do so, use rsync -avr.

NVIDIA GPU setup

This section is current with 20.04.

This is very straightforward:

sudo apt install system76-cudnn-11.1 libcusolver* python3-pip
pip3 install tensorflow-gpu

Then,

python3
import tensorflow as tf
tf.config.list_physical_devices('GPU') 

The information printed to screen should tell you that the GPU have been found and “registered”.

AMD GPU setup

Follow instructions here.

The command that worked is:

amdgpu-install --usecase=opencl --no-dkms