Superscalability of the random batch Ewald method
Jiuyang Liang, Pan Tan, Yue Zhao, Lei Li, Shi Jin, Liang Hong and, Zhenli Xu

TL;DR
This paper introduces a scalable, efficient molecular dynamics algorithm using the random batch Ewald method, enabling simulations of extremely large all-atom systems with linear complexity and significant speed improvements.
Contribution
The paper presents a novel random batch Ewald algorithm that achieves linear scaling and perfect scalability for Coulomb interactions in large-scale molecular dynamics simulations.
Findings
Simulates up to 100 million particles efficiently
Achieves almost perfect linear scalability
Provides results consistent with existing algorithms
Abstract
Coulomb interaction, following an inverse-square force-law, quantifies the amount of force between two stationary and electrically charged particles. The long-range nature of Coulomb interactions poses a major challenge to molecular dynamics simulations which are major tools for problems at the nano-/micro- scale. Various algorithms are developed to calculate the pairwise Coulomb interactions to a linear scaling but the poor scalability limits the size of simulated systems. Here, we conduct an efficient molecular dynamics algorithm with the random batch Ewald method on all-atom systems where the complete Fourier components in the Coulomb interaction are replaced by randomly selected mini-batches. By simulating the -body systems up to 100 million particles using thousand CPU cores, we show that this algorithm furnishes complexity, almost perfect scalability and an order of…
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