LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials.

自经典分子动力学模拟器LAMMPS于2004年以开源代码形式发布以来，它已成为广泛应用于跨尺度（从原子尺度、介观尺度到连续介质尺度）粒子基材料建模的主流工具。其广受青睐的原因主要有三：其一，可为各类材料提供丰富多样的粒子相互作用模型；其二，可兼容从单个CPU核心到搭载加速器的顶级超级计算机的全平台运行；其三，支持用户通过输入脚本或新增代码灵活掌控模拟细节，例如添加新的原子间势、约束条件、诊断工具或其他建模所需功能。正因如此，已有数百位开发者为LAMMPS贡献了新功能，其代码体量也从2004年的5万行增长至如今的百万行。本文详述了LAMMPS所采用的多项核心算法，以及使其同时兼顾用户易用性与开发者灵活性的设计策略。此外，本文还重点介绍了依托该灵活性新近加入代码库的多项新增功能，包括动态负载均衡、实时可视化、自旋磁动力学模型，以及量子精度机器学习原子间势。