LAMMPS is a classical molecular dynamics code with a focus on materials modeling. It's an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. LAMMPS has potentials for solid-state materials (metals, semiconductors) and soft matter (biomolecules, polymers) and coarse-grained or mesoscopic systems.

There were ~405,000 downloads of LAMMPS from Sept 2004 thru mid-year 2021. At that point we migrated our website to https://www.lammps.org and a different server, and stopped logging downloads. LAMMPS molecular dynamics package:

LAMMPS reads commands from standard input, so if all you see is the LAMMPS version number, it is probably waiting for input. You could type in commands but that would be tedious. You need to put commands in a text file or input script like in.lj and run LAMMPS like this:

Axel Kohlmeyer organized a LAMMPS Users and Developers Workshop and Symposium at the International Centre for Theroretical Phyics (ICTP) in Trieste, Italy in March 2014. See details of the program at this link. Steve Plimpton: LAMMPS Overview; Simple LAMMPS Examples; Modeling Thermal Transport and Viscosity with MD; Modifying and Extending LAMMPS

There are two kinds of movies on this page. Some are from large-scale simulations performed with LAMMPS and submitted by users. Others are simple animations of (mostly) 2d problems that illustrate the kinds of simulations that LAMMPS can be easliy used to run. This page has additional snapshots from LAMMPS simulations but without animations.

The forum replaces the lammps-users mailing list which was discontinued on June 30th, 2022.

LUNAR stands for LAMMPS Utility (for) Network Analysis (and) Reactivity and is a stand alone Python (3.7+) toolkit to supplement LAMMPS. LUNAR is focused on pre-processing and post-processing inputs and outputs of LAMMPS with emphasis of using LAMMPS for producing structure-property relationships for ICME process modeling of polymers.

LAMMPS was compiled using the Intel icc compiler, version 11.1. The 4-processor runs were made on 4 cores of the same system. The number of neighbors per atom is based on what LAMMPS tallied at the end of the short run within the neighbor cutoff = force cutoff + …

Porting LAMMPS to GPUs Still largely a research effort Marc Adams (Nvidia) Pratul Agarwal (ORNL) Sarah Anderson (Cray) Mike Brown (Sandia) Paul Crozier (Sandia) Massimiliano Fatica (Nvidia) Scott Hampton (ORNL) Ricky Kendall (ORNL) Hyesoon Kim (Ga Tech) Axel Kohlmeyer (Temple) Doug Kothe (ORNL) Scott LeGrand (Nvidia) Ben Levine (Temple)

Citing LAMMPS in your papers The following CPC paper is the canonical reference to use for citing LAMMPS. It gives an overview of the code including its parallel algorithms, design features, performance, and brief highlights of many of its materials modeling capabilities.