Breaking the mold: Overcoming the time constraints of molecular dynamics on general-purpose hardware.

IF 3.1 2区 化学 Q3 CHEMISTRY, PHYSICAL Journal of Chemical Physics Pub Date : 2025-02-21 DOI:10.1063/5.0249193
Danny Perez, Aidan Thompson, Stan Moore, Tomas Oppelstrup, Ilya Sharapov, Kylee Santos, Amirali Sharifian, Delyan Z Kalchev, Robert Schreiber, Scott Pakin, Edgar A Leon, James H Laros, Michael James, Sivasankaran Rajamanickam
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Abstract

The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have, however, failed to provide strong scaling for MD, as scale-out central processing unit (CPU) and graphics processing unit (GPU) platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras wafer scale engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144 M steps/s for 200 000 atoms whose interactions are described by an embedded atom method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. In this paper, we provide an overview of advances in MD over the last 60 years and present our recent result in the context of historical MD performance trends.

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打破常规:在通用硬件上克服分子动力学的时间限制。
分子动力学(MD)模拟的发展与计算机硬件的发展密切相关。在MD创建后的几十年里,模拟的计算能力在精度、原子数(空间尺度)和持续时间(时间尺度)这三个主要维度上得到了改进。然而,自2000年代中期以来,计算机平台未能为MD提供强大的可伸缩性,因为可向外扩展的中央处理器(CPU)和图形处理单元(GPU)平台提供了空间尺度的大幅增加,但并未导致时间尺度的成比例增加。因此,重要的科学问题仍然无法直接模拟,这促使越来越复杂的算法的发展,这些算法呈现出显著的复杂性、准确性和效率挑战。虽然定制的纯md硬件解决方案为特定物理系统提供了更长的时间尺度,但由于对新方法和潜力的适应性有限,它们对更广泛的社区的影响已经减弱。在这项工作中,我们展示了一种新的计算架构,即Cerebras晶圆规模引擎,通过为20万个原子提供前所未有的高模拟速率(高达1.144 M步/秒),从而彻底改变了缩放路径,这些原子的相互作用由嵌入原子方法势描述。这使得使用通用可编程硬件在毫秒时间尺度上直接模拟材料的演变,大大增加了可以进行的直接MD模拟的空间。在本文中,我们概述了过去60年来MD的进展,并在历史MD性能趋势的背景下介绍了我们最近的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Chemical Physics
Journal of Chemical Physics 物理-物理:原子、分子和化学物理
CiteScore
7.40
自引率
15.90%
发文量
1615
审稿时长
2 months
期刊介绍: The Journal of Chemical Physics publishes quantitative and rigorous science of long-lasting value in methods and applications of chemical physics. The Journal also publishes brief Communications of significant new findings, Perspectives on the latest advances in the field, and Special Topic issues. The Journal focuses on innovative research in experimental and theoretical areas of chemical physics, including spectroscopy, dynamics, kinetics, statistical mechanics, and quantum mechanics. In addition, topical areas such as polymers, soft matter, materials, surfaces/interfaces, and systems of biological relevance are of increasing importance. Topical coverage includes: Theoretical Methods and Algorithms Advanced Experimental Techniques Atoms, Molecules, and Clusters Liquids, Glasses, and Crystals Surfaces, Interfaces, and Materials Polymers and Soft Matter Biological Molecules and Networks.
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