Thornton Lab policies and protocols

Lab manual for the Thornton lab at UC Irvine

Working remotely
Note taking, lab notebooks, etc..
Content generation with R Markdown
Manuscript preparation
Backing up data
Text editors for coding
Git and GitHub best practices
Programming guidelines
Software dependency management
Lab computers
Thornton lab main page

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:

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:


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


import tensorflow as tf

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

AMD GPU setup

TBD–waiting for 6700xt to become available!