Description
This lesson provides an overview of some more advanced techniques and uses of LAMMPS. Specifically, we will be discussing:
- Measuring and improving LAMMPS performance
- 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 that already). This lesson is aimed at anyone who:
- has experience using
bash(or any other shell) - has experience running LAMMPS on multiple processors
General Information
Requirements: Participants must have a working laptop or desktop computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have access to a terminal (Max and Linux users should have a terminal installed by default; Windows users should get either MobaXterm or PuTTY. They are also required to abide by the ARCHER2 Training Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
- The room is wheelchair / scooter accessible.
- Accessible restrooms are available.
Materials will be provided in advance of the lesson and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email R.Apostolo@epcc.ed.ac.uk for more information.
Prerequisites
You should have used remote HPC facilities before. In particular, you should be happy with connecting using SSH, know what a batch scheduling system is and be familiar with using the Linux command line. You should also be happy editing plain text files in a remote terminal (or, alternatively, editing them on your local system and copying them to the remote HPC system using
scp).