Collaborative Research: DOT -- Distributed Optical Testbed to Facilitate the Development of Techniques for Efficient Execution of Distributed Applications

合作研究:DOT——分布式光学测试台,促进分布式应用高效执行技术的开发

基本信息

  • 批准号:
    0224187
  • 负责人:
  • 金额:
    $ 8.19万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2002
  • 资助国家:
    美国
  • 起止时间:
    2002-09-15 至 2005-08-31
  • 项目状态:
    已结题

项目摘要

EIA 02-24187Foster, IanUniversity of Chicago Title: CISE RR: (Collaborative) DOT--Distributed Optical Testbed to Facilitate the Development of Techniques for Efficient Execution of Distributed Applications This collaborative proposal with Illinois Institute of Technology (Sun, 02-24377) and Northwestern University (Taylor, 02-24427), acquiring data nodes and compute nodes at five sites, contributes to build a Distributed Optical Testbed (DOT). The DOT system, a product of the paradigm shift from large-scale applications running on large parallel systems at single sites to those running on distributed systems, has come about by the availability of high-speed optical networks (E.g., Starlight, TeraGrid 40 Gb/s network, the PacificRail 10 Gb/s network). This shift necessitates techniques that allow applications to efficiently utilize distributed systems. In contrast to parallel systems, these systems must exploit two characteristics:Heterogeneity of resources (processors and networks) and Dynamic changes in performance of shared resources, especially wide area networks. The system, consisting of Linux clusters at six geographically different sites interconnected via two existing research DWDM networks, I-WIRE and OMNInet, involves the following sites: Argonne National Laboratory (ANL), Illinois Institute of Technology (IIT), National Center for Supercomputer Applications (NCSA), Northwester University Chicago Campus (NU-C), Northwestern University Evanston Campus (NU-E), and the University of Chicago (UC). DOT will facilitate the following research activities in the area of distributed applications:Dynamic Load Balancing (Taylor)Performance Monitoring and Prediction (Dinda, Sun, Taylor)Data Management (Choudhary, Foster)The first activity develops techniques utilizing network performance predictions that take into consideration the heterogeneity of the processors and networks of distributed systems to dynamically balance the load during execution. The second extends performance monitoring, modeling and prediction techniques that have been focused on parallel systems and broadband network to distributed systems with optical networks and different topologies. The last develops techniques that manage the distributed data such that the actual data location is transparent and the data is accessed efficiently. These research activities are driven by three applications that have been parallelized using MPI, such that the applications can be easily ported to DOT:ENZO, an adaptive cosmological application,Cactus, an open framework used to solve Einstein's equations, andAudioVoice, a virtualized distributed audio application with physical simulations that have real-time deadlines and varying computational demands.Each application presents challenges, which include adaptivity, flexible framework, and simulations with real-time deadlines.
EIA 02- 24187福斯特,伊恩芝加哥大学标题:CISE RR:(协作)DOT--分布式光学测试平台,以促进分布式应用程序的有效执行技术的发展(Sun,02-24377)和西北大学(Taylor,02-24427),在五个站点获取数据节点和计算节点,有助于建立分布式光学测试床(DOT)。DOT系统是从在单个站点处的大型并行系统上运行的大规模应用到在分布式系统上运行的那些应用的范式转变的产物,其是由高速光网络(例如,Starlight、TeraGrid 40 Gb/s网络、PacificRail 10 Gb/s网络)。这种转变需要一些技术来允许应用程序有效地利用分布式系统。与并行系统相比,这些系统必须利用两个特性:资源(处理器和网络)的异构性和共享资源(特别是广域网)性能的动态变化。该系统由位于六个地理位置不同的站点的Linux群集组成,这些站点通过两个现有的研究DWDM网络(I-WIRE和OMNInet)互连,包括以下站点:阿贡国家实验室(ANL)、伊利诺伊理工学院(IIT)、国家超级计算机应用中心(NCSA)、西北大学芝加哥校区(NU-C)、西北大学埃文斯顿校区(NU-E)、和芝加哥大学(UC)。DOT将促进分布式应用领域的以下研究活动:动态负载平衡(Taylor)性能监测和预测(Dinda,Sun,Taylor)数据管理(Choudhary,Foster)第一项活动开发利用网络性能预测的技术,该技术考虑到分布式系统的处理器和网络的异质性,以动态平衡执行期间的负载。第二个扩展的性能监测,建模和预测技术,一直专注于并行系统和宽带网络的分布式系统与光网络和不同的拓扑结构。最后开发了管理分布式数据的技术,使得实际数据位置是透明的,并且可以有效地访问数据。这些研究活动是由三个应用程序驱动的,这些应用程序已经使用MPI并行化,以便应用程序可以很容易地移植到DOT:ENZO,一个自适应宇宙学应用程序,Cactus,一个用于求解爱因斯坦方程的开放框架,和AudioVoice,一个虚拟化的分布式音频应用程序,具有实时截止日期和不同的计算需求的物理模拟。每个应用程序都提出了挑战,其中包括自适应性,灵活的框架,并与实时截止日期的模拟。

项目成果

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Ian Foster其他文献

GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS
GreenFaaS:利用 FaaS 最大限度提高 HPC 工作负载的能源效率
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alok V. Kamatar;Valerie Hayot;Y. Babuji;André Bauer;Gourav Rattihalli;Ninad Hogade;D. Milojicic;Kyle Chard;Ian Foster
  • 通讯作者:
    Ian Foster
An optical microscopy system for 3 D dynamic imagingRandy
用于 3D 动态成像的光学显微镜系统Randy
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    R. Hudson;John N. Aarsvold;Chin;Jie Chen;Peter Davies;T. Disz;Ian Foster;Melvin Griem;Man K Kwong;B. Lin
  • 通讯作者:
    B. Lin
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
DeepSpeed4Science 计划:通过复杂的人工智能系统技术实现大规模科学发现
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Song;Bonnie Kruft;Minjia Zhang;Conglong Li;Shiyang Chen;Chengming Zhang;Masahiro Tanaka;Xiaoxia Wu;Jeff Rasley;A. A. Awan;Connor Holmes;Martin Cai;Adam Ghanem;Zhongzhu Zhou;Yuxiong He;Christopher Bishop;Max Welling;Tie;Christian Bodnar;Johannes Brandsetter;W. Bruinsma;Chan Cao;Yuan Chen;Peggy Dai;P. Garvan;Liang He;E. Heider;Pipi Hu;Peiran Jin;Fusong Ju;Yatao Li;Chang Liu;Renqian Luo;Qilong Meng;Frank Noé;Tao Qin;Janwei Zhu;Bin Shao;Yu Shi;Wen;Gregor Simm;Megan Stanley;Lixin Sun;Yue Wang;Tong Wang;Zun Wang;Lijun Wu;Yingce Xia;Leo Xia;Shufang Xie;Shuxin Zheng;Jianwei Zhu;Pete Luferenko;Divya Kumar;Jonathan Weyn;Ruixiong Zhang;Sylwester Klocek;V. Vragov;Mohammed Alquraishi;Gustaf Ahdritz;C. Floristean;Cristina Negri;R. Kotamarthi;V. Vishwanath;Arvind Ramanathan;Sam Foreman;Kyle Hippe;T. Arcomano;R. Maulik;Max Zvyagin;Alexander Brace;Bin Zhang;Cindy Orozco Bohorquez;Austin R. Clyde;B. Kale;Danilo Perez;Heng Ma;Carla M. Mann;Michael Irvin;J. G. Pauloski;Logan Ward;Valerie Hayot;M. Emani;Zhen Xie;Diangen Lin;Maulik Shukla;Thomas Gibbs;Ian Foster;James J. Davis;M. Papka;Thomas Brettin;Prasanna Balaprakash;Gina Tourassi;John P. Gounley;Heidi Hanson;T. Potok;Massimiliano Lupo Pasini;Kate Evans;Dan Lu;D. Lunga;Junqi Yin;Sajal Dash;Feiyi Wang;M. Shankar;Isaac Lyngaas;Xiao Wang;Guojing Cong;Peifeng Zhang;Ming Fan;Siyan Liu;A. Hoisie;Shinjae Yoo;Yihui Ren;William Tang;K. Felker;Alexey Svyatkovskiy;Hang Liu;Ashwin Aji;Angela Dalton;Michael Schulte;Karl Schulz;Yuntian Deng;Weili Nie;Josh Romero;Christian Dallago;Arash Vahdat;Chaowei Xiao;Anima Anandkumar;R. Stevens
  • 通讯作者:
    R. Stevens
Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept
化学与材料科学低成本自动驾驶实验室综述:“节俭双胞胎”概念
  • DOI:
    10.1039/d3dd00223c
  • 发表时间:
    2024-05-15
  • 期刊:
  • 影响因子:
    5.600
  • 作者:
    Stanley Lo;Sterling G. Baird;Joshua Schrier;Ben Blaiszik;Nessa Carson;Ian Foster;Andrés Aguilar-Granda;Sergei V. Kalinin;Benji Maruyama;Maria Politi;Helen Tran;Taylor D. Sparks;Alán Aspuru-Guzik
  • 通讯作者:
    Alán Aspuru-Guzik
Exploring Benchmarks for Self-Driving Labs using Color Matching
使用颜色匹配探索自动驾驶实验室的基准
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Tobias Ginsburg;Kyle Hippe;Ryan Lewis;Aileen Cleary;D. Ozgulbas;Rory Butler;Casey Stone;Abraham Stroka;Rafael Vescovi;Ian Foster
  • 通讯作者:
    Ian Foster

Ian Foster的其他文献

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{{ truncateString('Ian Foster', 18)}}的其他基金

Collaborative Research: NSF Workshop on Automated, Programmable and Self Driving Labs
合作研究:NSF 自动化、可编程和自动驾驶实验室研讨会
  • 批准号:
    2335910
  • 财政年份:
    2023
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
Frameworks: Garden: A FAIR Framework for Publishing and Applying AI Models for Translational Research in Science, Engineering, Education, and Industry
框架:Garden:用于发布和应用人工智能模型进行科学、工程、教育和工业转化研究的公平框架
  • 批准号:
    2209892
  • 财政年份:
    2022
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
Collaborative Research: OAC Core: ScaDL: New Approaches to Scaling Deep Learning for Science Applications on Supercomputers
协作研究:OAC 核心:ScaDL:在超级计算机上扩展深度学习科学应用的新方法
  • 批准号:
    2107511
  • 财政年份:
    2021
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
NSF Convergence Accelerator Track D: The Data Hypervisor: Orchestrating Data and Models
NSF 融合加速器轨道 D:数据管理程序:编排数据和模型
  • 批准号:
    2040718
  • 财政年份:
    2020
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
Collaborative Research: Frameworks: funcX: A Function Execution Service for Portability and Performance
协作研究:框架:funcX:可移植性和性能的函数执行服务
  • 批准号:
    2004894
  • 财政年份:
    2020
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
Virtual Data Set Services Enabling New Science at NSF Facilities
虚拟数据集服务在 NSF 设施中实现新科学
  • 批准号:
    1841531
  • 财政年份:
    2018
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
Framework: Software: HDR Globus Automate: A Distributed Research Automation Platform
框架:软件:HDR Globus Automate:分布式研究自动化平台
  • 批准号:
    1835890
  • 财政年份:
    2018
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
EAGER: Designing the OSN Software Platform
EAGER:设计 OSN 软件平台
  • 批准号:
    1836357
  • 财政年份:
    2018
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
BD Spokes: SPOKE: MIDWEST: Collaborative: Integrative Materials Design (IMaD): Leverage, Innovate, and Disseminate
BD 辐条:辐条:中西部:协作:集成材料设计 (IMaD):利用、创新和传播
  • 批准号:
    1636950
  • 财政年份:
    2017
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant
Collaborative Research: CyberSEES:Type 2: Framework to Advance Climate, Economics, and Impact Investigations with Information Technology (FACE-IT)
合作研究:Cyber​​SEES:类型 2:利用信息技术推进气候、经济和影响调查的框架 (FACE-IT)
  • 批准号:
    1331922
  • 财政年份:
    2013
  • 资助金额:
    $ 8.19万
  • 项目类别:
    Standard Grant

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