Advanced use of LAMMPS

This lesson provides an overview of some more advanced techniques and uses of LAMMPS. Specifically, we will be discussing:

Measuring and improving LAMMPS performance
- Strong vs weak scaling for a range of systems
- Smarter domain decomposition
- Accelerators and what they do
Using LAMMPS with Python
Analysing systems through reruns
Advanced sampling methods with a focus on replica exchange
Target Audience:

For this lesson, we expect attendees to be familiar with LAMMPS. We will not be covering how to prepare and run a parallel LAMMPS simulation (and we will assume that all attendees know how to do this already). This lesson is aimed at anyone who:

has experience using bash (or any other shell)
has experience running LAMMPS on multiple processors
would like to learn more about some of the LAMMPS functionalities stated above
would like to learn more about tricks and methods for getting LAMMPS to perform efficiently.

Requirements:

Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on.

They are also required to abide by the ARCHER2 Code of Conduct.