A decoupled execution paradigm for data-intensive high-end computing

Yong Chen, Chao Chen, Xian He Sun, William D. Gropp, Rajeev Thakur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

High-end computing (HEC) applications in critical areas of science and technology tend to be more and more data intensive. I/O has become a vital performance bottleneck of modern HEC practice. Conventional HEC execution paradigms, however, are computing-centric for computation intensive applications. They are designed to utilize memory and CPU performance and have inherent limitations in addressing the critical I/O bottleneck issues of HEC. In this study, we propose a decoupled execution paradigm (DEP) to address the challenging I/O bottleneck issues. DEP is the first paradigm enabling users to identify and handle data-intensive operations separately. It can significantly reduce costly data movement and is better than the existing execution paradigms for data-intensive applications. The initial experimental tests have confirmed its promising potential. Its data-centric architecture could have an impact in future HEC systems, programming models, and algorithms design and development.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 IEEE International Conference on Cluster Computing, CLUSTER 2012
PublisherIEEE Computer Society
Pages200-208
Number of pages9
ISBN (Print)9780768548074
DOIs
StatePublished - Jan 1 2012
Event2012 IEEE International Conference on Cluster Computing, CLUSTER 2012 - Beijing, China
Duration: Sep 24 2012Sep 28 2012

Publication series

NameProceedings - 2012 IEEE International Conference on Cluster Computing, CLUSTER 2012

Other

Other2012 IEEE International Conference on Cluster Computing, CLUSTER 2012
CountryChina
CityBeijing
Period9/24/129/28/12

Keywords

  • data-intensive computing
  • decoupled execution paradigm
  • high-end computing
  • storage

ASJC Scopus subject areas

  • Software

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