Collaborative Research: CDS&E: ReaxFF2: Efficient and Scalable Methods for Long-time Reactive Molecular Dynamics Simulations
Collaborative Research: CDS&E: ReaxFF2: Efficient and Scalable Methods for Long-time Reactive Molecular Dynamics Simulations
批准号:
1807622
负责人:
Metin Aktulga
金额:
$25.08万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2022-08-31
中文摘要
该项目旨在通过高效和可扩展的技术实现对活性分子系统的长期模拟。长期的反应模拟对于几个科学问题至关重要,如催化、电池接口、涉及水的生物模拟以及表面氧化和化学气相沉积(CVD)生长等新兴领域。然而,这些方面的进展是有限的,因为使用现有方法进行大规模系统的长期模拟是非常困难的,如果不是不可能的话。反应力场(ReaxFF)方法原则上非常适合于这一目的。然而,当前ReaxFF模拟所需的短时间步长和计算代价高昂的力场公式限制了ReaxFF缩小模拟时间范围的时间能力。该项目旨在通过创建ReaxFF2来克服这些限制,它将把时间尺度延长一到两个数量级-从而使更广泛的社区能够访问大规模、长期的RMD模拟。开发的代码将公之于众,这个项目的结果将在一个专门的网站上突出显示,它们也将被PI纳入研讨会。在创建ReaxFF2时,PI将显著增强Reax力场公式,并为可扩展的模拟开发创新的算法和软件实现。更具体地说,将制定替代的ReaxFF交互作用,以消除能量方面的急剧导数,并将ReaxFF时间步长提高至少四倍。为了加速RMD所需的动态电荷分布模型,将为迭代求解器开发可扩展的并行预处理技术。计算交互的任务并行方法、层次化问题分解、关键核心的矢量化以及混合精度算法的使用构成了将被用来充分利用大型计算机集群的性能能力的主要技术。最后,将评估拟议的ReaxFF2配方中加速RMD概念的能力,并将开发用于RMD的内嵌轨迹分析工具,以促进长期RMD模拟的研究。这个项目将大大加强私人投资机构的软件开发、社区建设和为RMD社区提供支持的努力。开发的代码、函数形式和参数集将公开提供,从而能够快速准确地对超出本项目范围的各种反应系统进行建模。对于社区外展,这个项目的成果将在一个专门的网站上突出显示,它们也将被PIS纳入研讨会。这一奖项由高级网络基础设施办公室颁发,由NSF数学和物理科学局内的材料研究部和化学部联合支持。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to enable long-time simulations of reactive molecular systems through efficientand scalable techniques. Long-time reactive simulations are critical for several scientific problemssuch as catalysis, battery interfaces, biological simulations involving water, and emergingareas like surface oxidation and chemical vapor deposition (CVD) growth. However, progress onthese fronts is limited because long-time simulations of large-scale systems are very difficult, ifnot impossible, to perform using existing methods. The Reactive Force Field (ReaxFF) method is in principle ideally suited for this purpose. However, the short time steps required in current ReaxFF simulations and the computationally expensive force field formulation limit ReaxFF's temporal capabilities to narrow simulation time ranges. This project aims to overcome such limitations by creating ReaxFF2,which will extend time scales by one to two orders of magnitude - thus making large-scale, long-time RMD simulations accessible to a wide community. Codes developed will be made publicly available and results from this project will be highlighted on a dedicated website, and they will also be incorporated into workshops by the PIs.In creating ReaxFF2, the PIs will enhance the Reax force field formulation significantly, and develop innovative algorithms and software implementations for scalable simulations. More specifically, alternative ReaxFF interactions will be formulated to eliminate sharp derivatives in energy terms and enhance ReaxFF time step lengths by at least a factor of four. To accelerate the dynamic charge distribution models needed in RMD, scalable parallel preconditioning techniques for the iterative solvers will be developed. A task parallel approach to compute interactions, hierarchical problem decomposition, vectorization of the key kernels, and use of mixed precision arithmetics constitutethe main techniques that will be utilized to fully leverage the performance capabilities of largecomputer clusters. Finally, capabilities of accelerated RMD concepts in the proposed ReaxFF2 formulation will be evaluated and inlined trajectory analysis tools for RMD will be developed to facilitate the study of long-time RMD simulations. This project will significantly enhance the PIs' software development, community building, and sustenance efforts for the RMD community. Codes, functional forms, and parameter sets developed will be made publicly available, enabling fast and accurate modeling of diverse reactive systems beyond the scope of this project. For community outreach, results from this project will be highlighted on a dedicated website, and they will also be incorporated into workshops by the PIs.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Materials Research and the Division of Chemistry within the NSF Directorate for Mathematical and Physical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
Performance optimization of reactive molecular dynamics simulations with dynamic charge distribution models on distributed memory platforms
分布式存储平台上动态电荷分布模型的反应分子动力学模拟的性能优化
DOI:
10.1145/3330345.3330359
发表时间:
2019
期刊:
ICS '19 Proceedings of the ACM International Conference on Supercomputing
影响因子:
--
作者:
[O'Hearn, Kurt A., Alperen, Abdullah, Aktulga, Hasan Metin]
通讯作者:
Aktulga, Hasan Metin
CAREER: Scalable Sparse Linear Algebra for Extreme-Scale Data Analytics and Scientific Computing
-
批准号:1845208
-
项目类别:Continuing Grant
-
资助金额:$50.0万
-
财政年份:2019
-
负责人:Metin Aktulga
-
依托单位:
SPX: A Geometry and Architecture Agnostic Scalable Framework for N-body Problems with Oscillatory Potentials
-
批准号:1822932
-
项目类别:Standard Grant
-
资助金额:$67.45万
-
财政年份:2018
-
负责人:Metin Aktulga
-
依托单位:
CRII: ACI: Algorithms and Tools to Facilitate the Development of High Fidelity Reactive Molecular Dynamics Models
-
批准号:1566049
-
项目类别:Standard Grant
-
资助金额:$17.5万
-
财政年份:2016
-
负责人:Metin Aktulga
-
依托单位:
国内基金
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