RBMD: A Molecular Dynamics Package Enabling to Simulate 10 Million All-Atom Particles in a Single Graphics Processing Unit

作者：Weihang Gao, Teng Zhao, Yongfa Guo, Jiuyang Liang, Huan Liu, Maoying Luo, Zedong Luo, Wei Qin, Yichao Wang, Qi Zhou, Shi Jin, Zhenli Xu · 发表于：Communications in Computational Physics · 年份：2025 · DOI：10.4208/cicp.oa-2024-0156 · 被引用次数：3 · 研究领域：Protein Structure and Dynamics、Block Copolymer Self-Assembly、Nanopore and Nanochannel Transport Studies

This paper introduces a random-batch molecular dynamics (RBMD) package for simulations of particle systems at the nano/micro scale. Different from existing packages, the RBMD uses random batch methods for nonbonded interactions of particle systems. The long-range part of Coulomb interactions is calculated in Fourier space by the random batch Ewald algorithm, which achieves linear complexity and superscalability, surpassing classical lattice-based Ewald methods. For the short-range part, the random batch list algorithm is used to construct neighbor lists, significantly reducing computational and memory costs. The RBMD is implemented on GPU-CPU heterogeneous architectures, with classical force fields for all-atom systems. Benchmark systems are used to validate the accuracy and performance of the package. Comparison with the particle-particle particle-mesh and the Verlet list methods in the LAMMPS package is performed on three different NVIDIA GPUs, demonstrating high efficiency of the RBMD on heterogeneous architectures. Our results also show that the RBMD enables simulations on a single GPU with a CPU core up to 10 million particles. Typically, for systems of one million particles, the RBMD allows simulating all-atom systems with a high efficiency of 8.20 ms per step, demonstrating the attractive feature for running large-scale simulations of practical applications on a desktop machine.