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
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.
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.
This course is part-funded by the PRACE project and is free to all.