Utilizing Averaged Configuations from Molecular Dynamics Simulation Trajectories

P. Kusalik, K. Gillis, J. Vatamanu
{"title":"Utilizing Averaged Configuations from Molecular Dynamics Simulation Trajectories","authors":"P. Kusalik, K. Gillis, J. Vatamanu","doi":"10.1109/HPCS.2007.34","DOIUrl":null,"url":null,"abstract":"One of the challenges in the large-scale simulations required for many molecular systems (such as those of biological interested) is the recording, monitoring and visualization of configurational information from molecular dynamics trajectories spanning millions, and sometimes billions, of timesteps. A detailed record of instantaneous configurations along the full trajectory can quickly become unmanageable. In this paper we will describe an alternative approach that utilizes time coarse-graining, where configurations averaged over trajectory segments are used to follow the detailed molecular behaviour of a system over multiple-nanosecond simulations. We will demonstrate that the sensitivity of structural measures (order parameters) can be dramatically enhanced when applied to averaged configurations. We then specifically discuss the successful application of this approach to molecular dynamics simulations of crystal growth.","PeriodicalId":354520,"journal":{"name":"21st International Symposium on High Performance Computing Systems and Applications (HPCS'07)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st International Symposium on High Performance Computing Systems and Applications (HPCS'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCS.2007.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

One of the challenges in the large-scale simulations required for many molecular systems (such as those of biological interested) is the recording, monitoring and visualization of configurational information from molecular dynamics trajectories spanning millions, and sometimes billions, of timesteps. A detailed record of instantaneous configurations along the full trajectory can quickly become unmanageable. In this paper we will describe an alternative approach that utilizes time coarse-graining, where configurations averaged over trajectory segments are used to follow the detailed molecular behaviour of a system over multiple-nanosecond simulations. We will demonstrate that the sensitivity of structural measures (order parameters) can be dramatically enhanced when applied to averaged configurations. We then specifically discuss the successful application of this approach to molecular dynamics simulations of crystal growth.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用分子动力学模拟轨迹的平均构型
对于许多分子系统(如生物系统)来说,大规模模拟的挑战之一是记录、监控和可视化分子动力学轨迹的构型信息,这些信息跨越数百万,有时甚至数十亿的时间步长。沿着整个轨迹的瞬时配置的详细记录很快就会变得难以管理。在本文中,我们将描述一种利用时间粗粒度的替代方法,其中使用轨迹段上的平均配置来跟踪系统在多纳秒模拟中的详细分子行为。我们将证明,当应用于平均构型时,结构测量(序参数)的灵敏度可以显着增强。然后,我们具体讨论了这种方法在晶体生长的分子动力学模拟中的成功应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Effect of Medium Dispersivity on the Viscous Fingering Instability in Porous Media The GridX1 computational Grid: from a set of service-specific protocols to a service-oriented approach Resource Assessment using Market Indices: Toward an Economic Grid Exchange Model Domain coupling in the ABC transporter system BtuCD/BtuF: molecular dynamics simulation, normal mode analysis and protein-protein docking Gyrokinetic simulation of micro-turbulence in magnetically confined plasmas
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1