A Scalable, Linear-Time Dynamic Cutoff Algorithm for Molecular Dynamics
Paul Springer, Ahmed E. Ismail, Paolo Bientinesi
TL;DR
This paper introduces a linear-time, scalable dynamic cutoff algorithm for molecular dynamics that improves performance on large systems and supercomputers by efficiently detecting interfaces without global communication.
Contribution
The paper presents a novel dynamic cutoff method with linear-time algorithms for interface detection, enabling efficient large-scale molecular dynamics simulations on massively parallel systems.
Findings
Comparable accuracy to PPPM algorithm
Significant performance improvements for large systems
Nearly perfect scaling on supercomputers
Abstract
Recent results on supercomputers show that beyond 65K cores, the efficiency of molecular dynamics simulations of interfacial systems decreases significantly. In this paper, we introduce a dynamic cutoff method (DCM) for interfacial systems of arbitrarily large size. The idea consists in adopting a cutoff-based method in which the cutoff is cho- sen on a particle-by-particle basis, according to the distance from the interface. Computationally, the challenge is shifted from the long-range solvers to the detection of the interfaces and to the computation of the particle-interface distances. For these tasks, we present linear-time algorithms that do not rely on global communication patterns. As a result, the DCM algorithm is suited for large systems of particles and mas- sively parallel computers. To demonstrate its potential, we integrated DCM into the LAMMPS open-source molecular dynamics…
Click any figure to enlarge with its caption.
Figure 1Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
See pages - of dcm_sc15.pdf