CSR: Medium: Collaborative Research: Decoupled Execution Paradigm for Data-Intensive High-End Computing
CSR:中:协作研究:数据密集型高端计算的解耦执行范式
基本信息
- 批准号:1161507
- 负责人:
- 金额:$ 27.01万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-06-01 至 2016-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
/O on High-End Computing (HEC) machines is increasingly becoming the killing performance bottleneck. However, conventional execution paradigms for HEC are computing-centric and have inherent limitations in addressing critical I/O issues of data-intensive applications. There is a great need for developing unconventional execution paradigms to meet the growing I/O demand of high-end computing.In this project, the PIs propose a decoupled execution paradigm (DEP) to address I/O bottleneck issues. DEP is the first paradigm enabling users to identify and handle data-intensive operations separately. The objective of the proposed research is three-fold: 1) understanding the execution paradigm requirement from the data-centric point of view, 2) studying the feasibility of the proposed decoupled execution paradigm, and 3) providing a partially implemented prototyping of DEP and its associated system design to support the first two objectives. Several technical hurdles have been identified, which include system architecture, programming model, and runtime system. Solutions are proposed and detailed plans are provided to evaluate the newly proposed decoupled execution paradigm.
高端计算(HEC)机器上的/O正日益成为致命的性能瓶颈。然而,传统的HEC执行范例是以计算为中心的,并且在解决数据密集型应用的关键I/O问题方面具有固有的局限性。在本项目中,PI提出了一种解耦的执行范式(DEP)来解决I/O瓶颈问题。DEP是第一个使用户能够单独识别和处理数据密集型操作的范例。建议的研究的目标是三个方面:1)理解的执行范式的要求,从数据为中心的观点,2)研究的可行性,提出的解耦执行范式,和3)提供一个部分实现的原型DEP及其相关的系统设计,以支持前两个目标。已经确定了几个技术障碍,其中包括系统架构,编程模型和运行时系统。提出了解决方案,并提供了详细的计划,以评估新提出的解耦执行范例。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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William Gropp其他文献
CommBench: Micro-Benchmarking Hierarchical Networks with Multi-GPU, Multi-NIC Nodes
CommBench:使用多 GPU、多 NIC 节点对分层网络进行微基准测试
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Mert Hidayetoğlu;Simon Garcia De Gonzalo;Elliott Slaughter;Yu Li;Christopher Zimmer;Tekin Bicer;Bin Ren;William Gropp;Wen;Alexander Aiken - 通讯作者:
Alexander Aiken
Multiprocessors
多处理器
- DOI:
- 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
David A. Padua;Amol Ghoting;J. Gunnels;M. Squillante;J. Meseguer;James H. Cownie;Duncan Roweth;Sarita V. Adve;Hans J. Boehm;Sally A. McKee;Robert W. Wisniewski;G. Karypis;Allen D. Malony;Steven Gottlieb;R. Riesen;Arthur B. Maccabe;G. Bilardi;A. Pietracaprina;A. Kejariwal;Alexandru Nicolau;Christian Lengauer;John L. Gustafson;William Gropp;J. Prost;Geoff Lowney;P. Amestoy;A. Buttari;I. Duff;A. Guermouche;J. L’Excellent;B. Uçar;Robert H. Halstead;M. Nemirovsky;S. Pakin - 通讯作者:
S. Pakin
Thread-safety in an MPI implementation: Requirements and analysis
- DOI:
10.1016/j.parco.2007.07.002 - 发表时间:
2007-09-01 - 期刊:
- 影响因子:
- 作者:
William Gropp;Rajeev Thakur - 通讯作者:
Rajeev Thakur
Enabling real-time multi-messenger astrophysics discoveries with deep learning
利用深度学习实现实时多信使天体物理学发现
- DOI:
10.1038/s42254-019-0097-4 - 发表时间:
2019-10-03 - 期刊:
- 影响因子:39.500
- 作者:
E. A. Huerta;Gabrielle Allen;Igor Andreoni;Javier M. Antelis;Etienne Bachelet;G. Bruce Berriman;Federica B. Bianco;Rahul Biswas;Matias Carrasco Kind;Kyle Chard;Minsik Cho;Philip S. Cowperthwaite;Zachariah B. Etienne;Maya Fishbach;Francisco Forster;Daniel George;Tom Gibbs;Matthew Graham;William Gropp;Robert Gruendl;Anushri Gupta;Roland Haas;Sarah Habib;Elise Jennings;Margaret W. G. Johnson;Erik Katsavounidis;Daniel S. Katz;Asad Khan;Volodymyr Kindratenko;William T. C. Kramer;Xin Liu;Ashish Mahabal;Zsuzsa Marka;Kenton McHenry;J. M. Miller;Claudia Moreno;M. S. Neubauer;Steve Oberlin;Alexander R. Olivas;Donald Petravick;Adam Rebei;Shawn Rosofsky;Milton Ruiz;Aaron Saxton;Bernard F. Schutz;Alex Schwing;Ed Seidel;Stuart L. Shapiro;Hongyu Shen;Yue Shen;Leo P. Singer;Brigitta M. Sipocz;Lunan Sun;John Towns;Antonios Tsokaros;Wei Wei;Jack Wells;Timothy J. Williams;Jinjun Xiong;Zhizhen Zhao - 通讯作者:
Zhizhen Zhao
William Gropp的其他文献
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{{ truncateString('William Gropp', 18)}}的其他基金
Category I: Bridging the Gap Between AI/ML Computing Demands and Today's Capabilities
第一类:缩小 AI/ML 计算需求与当今能力之间的差距
- 批准号:
2320345 - 财政年份:2023
- 资助金额:
$ 27.01万 - 项目类别:
Cooperative Agreement
Category I: Crossing the Divide Between Today's Practice and Tomorrow's Science
第一类:跨越今天的实践和明天的科学之间的鸿沟
- 批准号:
2005572 - 财政年份:2020
- 资助金额:
$ 27.01万 - 项目类别:
Cooperative Agreement
MRI: Development of an Instrument for Deep Learning Research
MRI:深度学习研究仪器的开发
- 批准号:
1725729 - 财政年份:2017
- 资助金额:
$ 27.01万 - 项目类别:
Standard Grant
BD Hubs: MIDWEST: SEEDCorn: Sustainable Enabling Environment for Data Collaboration
BD 中心:中西部:SEEDCorn:数据协作的可持续支持环境
- 批准号:
1550320 - 财政年份:2015
- 资助金额:
$ 27.01万 - 项目类别:
Standard Grant
Collaborative Research: System Software for Scalable Applications
合作研究:可扩展应用的系统软件
- 批准号:
1036137 - 财政年份:2011
- 资助金额:
$ 27.01万 - 项目类别:
Standard Grant
NSF Workshop on Software Development Environment for Science & Engineering Applications
NSF 科学软件开发环境研讨会
- 批准号:
1048964 - 财政年份:2010
- 资助金额:
$ 27.01万 - 项目类别:
Standard Grant
Programming Models and Application Requirements for an Exascale Computing Point Design Study
百亿亿次计算点设计研究的编程模型和应用要求
- 批准号:
0837719 - 财政年份:2008
- 资助金额:
$ 27.01万 - 项目类别:
Standard Grant
ITR: Collaborative Research - ASE - (sim+dmc): Image-based Biophysical Modeling: Scalable Registration and Inversion Algorithms and Distributed Computing
ITR:协作研究 - ASE - (sim dmc):基于图像的生物物理建模:可扩展配准和反演算法以及分布式计算
- 批准号:
0849301 - 财政年份:2007
- 资助金额:
$ 27.01万 - 项目类别:
Continuing Grant
ITR: Collaborative Research - ASE - (sim+dmc): Image-based Biophysical Modeling: Scalable Registration and Inversion Algorithms and Distributed Computing
ITR:协作研究 - ASE - (sim dmc):基于图像的生物物理建模:可扩展配准和反演算法以及分布式计算
- 批准号:
0427912 - 财政年份:2004
- 资助金额:
$ 27.01万 - 项目类别:
Continuing Grant
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