Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation.

James C Phillips, Yanhua Sun, Nikhil Jain, Eric J Bohm, Laxmikant V Kalé
{"title":"Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation.","authors":"James C Phillips,&nbsp;Yanhua Sun,&nbsp;Nikhil Jain,&nbsp;Eric J Bohm,&nbsp;Laxmikant V Kalé","doi":"10.1109/SC.2014.12","DOIUrl":null,"url":null,"abstract":"<p><p>Currently deployed petascale supercomputers typically use toroidal network topologies in three or more dimensions. While these networks perform well for topology-agnostic codes on a few thousand nodes, leadership machines with 20,000 nodes require topology awareness to avoid network contention for communication-intensive codes. Topology adaptation is complicated by irregular node allocation shapes and holes due to dedicated input/output nodes or hardware failure. In the context of the popular molecular dynamics program NAMD, we present methods for mapping a periodic 3-D grid of fixed-size spatial decomposition domains to 3-D Cray Gemini and 5-D IBM Blue Gene/Q toroidal networks to enable hundred-million atom full machine simulations, and to similarly partition node allocations into compact domains for smaller simulations using multiple-copy algorithms. Additional enabling techniques are discussed and performance is reported for NCSA Blue Waters, ORNL Titan, ANL Mira, TACC Stampede, and NERSC Edison.</p>","PeriodicalId":90723,"journal":{"name":"SC ... conference proceedings. SC (Conference : Supercomputing)","volume":"2014 ","pages":"81-91"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/SC.2014.12","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SC ... conference proceedings. SC (Conference : Supercomputing)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC.2014.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31

Abstract

Currently deployed petascale supercomputers typically use toroidal network topologies in three or more dimensions. While these networks perform well for topology-agnostic codes on a few thousand nodes, leadership machines with 20,000 nodes require topology awareness to avoid network contention for communication-intensive codes. Topology adaptation is complicated by irregular node allocation shapes and holes due to dedicated input/output nodes or hardware failure. In the context of the popular molecular dynamics program NAMD, we present methods for mapping a periodic 3-D grid of fixed-size spatial decomposition domains to 3-D Cray Gemini and 5-D IBM Blue Gene/Q toroidal networks to enable hundred-million atom full machine simulations, and to similarly partition node allocations into compact domains for smaller simulations using multiple-copy algorithms. Additional enabling techniques are discussed and performance is reported for NCSA Blue Waters, ORNL Titan, ANL Mira, TACC Stampede, and NERSC Edison.

Abstract Image

Abstract Image

Abstract Image

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
不规则环面拓扑映射及其他千万亿级生物分子模拟技术。
目前部署的千万亿次超级计算机通常使用三维或多维的环形网络拓扑结构。虽然这些网络在几千个节点上对拓扑无关的代码表现良好,但拥有20000个节点的领导机器需要拓扑感知,以避免通信密集型代码的网络争用。由于输入/输出节点专用或硬件故障,导致节点分配形状不规则,存在孔洞,拓扑适应非常复杂。在流行的分子动力学程序NAMD的背景下,我们提出了将固定大小的空间分解域的周期性3d网格映射到3-D Cray Gemini和5-D IBM Blue Gene/Q环形网络的方法,以实现数亿原子的全机器模拟,并使用多副本算法将节点分配到紧凑的域以进行较小的模拟。讨论了NCSA Blue Waters、ORNL Titan、ANL Mira、TACC Stampede和NERSC Edison的其他使能技术,并报告了其性能。
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
Big Omics Data Experience. Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation.
×
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