Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a molecular dynamics program from Sandia National Laboratories.[1] LAMMPS makes use of Message Passing Interface (MPI) for parallel communication and is free and open-source software, distributed under the terms of the GNU General Public License.[1]

Large-scale Atomic/Molecular Massively Parallel Simulator
Original author(s)Steve Plimpton, Aidan Thompson, Stan Moore, Axel Kohlmeyer, Richard Berger
Developer(s)Sandia National Laboratories
Temple University
Initial release1995 (1995)
Stable release
23June2022 / June 23, 2022 (2022-06-23)
Written inC++
Operating systemCross-platform: Linux, macOS, Windows, FreeBSD
Platformx86, x86-64, ARM, POWER9
Size480 MB
Available inEnglish
TypeMolecular dynamics
LicenseGNU General Public License

LAMMPS was originally developed under a Cooperative Research and Development Agreement (CRADA) between two laboratories from United States Department of Energy and three other laboratories from private sector firms.[1] As of 2016, it is maintained and distributed by researchers at the Sandia National Laboratories and Temple University.[1]


For computing efficiency, LAMMPS uses neighbor lists (Verlet lists) to keep track of nearby particles. The lists are optimized for systems with particles that repel at short distances, so that the local density of particles never grows too large.[2]

On parallel computers, LAMMPS uses spatial-decomposition techniques to partition the simulation domain into small 3d sub-domains, one of which is assigned to each processor. Processors communicate and store ghost atom information for atoms that border their subdomain. LAMMPS is most efficient (in a parallel computing sense) for systems whose particles fill a 3D rectangular box with approximately uniform density.

LAMMPS also allows for coupled spin and molecular dynamics in an accelerated fashion.[3]

LAMMPS is coupled to many analysis tools and engines as well.[4][5][6]

See also


  1. "LAMMPS Molecular Dynamics Simulator". Sandia National Laboratories. Retrieved 2022-07-13.
  2. Plimpton, S. (1993-05-01). "Fast parallel algorithms for short-range molecular dynamics". doi:10.2172/10176421. {{cite journal}}: Cite journal requires |journal= (help)
  3. Tranchida, Julien Guy; Wood, Mitchell; Moore, Stan Gerald (2018-09-01). "Coupled Magnetic Spin Dynamics and Molecular Dynamics in a Massively Parallel Framework: LDRD Final Report". doi:10.2172/1493836. OSTI 1493836. S2CID 127973739. {{cite journal}}: Cite journal requires |journal= (help)
  4. Stukowski, Alexander (2009-12-15). "Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool". Modelling and Simulation in Materials Science and Engineering. 18 (1): 015012. doi:10.1088/0965-0393/18/1/015012. ISSN 0965-0393. S2CID 42073422.
  5. Goswami, Rohit; Goswami, Amrita; Singh, Jayant K. (2019). "dSEAMS: Deferred Structural Elucidation Analysis for Molecular Simulations". Journal of Chemical Information and Modeling. arXiv:1909.09830. doi:10.1021/acs.jcim.0c00031.s001.
  6. McGibbon, Robert T; Beauchamp, Kyle A; Schwantes, Christian R; Wang, Lee-Ping; Hernández, Carlos X; Harrigan, Matthew P; Lane, Thomas J; Swails, Jason M; Pande, Vijay S (2014-09-09). "MDTraj: a modern, open library for the analysis of molecular dynamics trajectories". Biophysical Journal. 109 (8): 1528–32. bioRxiv 10.1101/008896. doi:10.1016/j.bpj.2015.08.015. PMC 4623899. PMID 26488642.
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