Overview
LAMMPS is a versatile, classical molecular dynamics (MD) code designed for high-performance computing environments. Originally developed by Sandia National Laboratories, it has evolved into the dominant engine for simulating materials at the atomic, meso, and continuum scales. Its technical architecture relies on spatial decomposition, allowing it to scale linearly across millions of CPU/GPU cores. In 2026, LAMMPS is at the forefront of the 'AI for Science' movement, providing the primary inference engine for Machine Learning Interatomic Potentials (MLIPs) like SNAP, NequIP, and DeepMD. It supports a vast array of force fields, from simple Lennard-Jones to complex reactive models (ReaxFF). Its modular C++ design allows for extensive customization, while its Python interface enables seamless integration into AI workflows and automated high-throughput screening pipelines. Whether modeling crack propagation in alloys or the self-assembly of lipid bilayers, LAMMPS remains the critical infrastructure for researchers bridging the gap between quantum accuracy and macroscopic behavior.