Integrating Abstractions to Enhance the Execution of Distributed Applications

Matteo Turilli, Feng Liu, Zhao Zhang, Andre Merzky, Michael Wilde, Jon Weissman, Daniel S. Katz, Shantenu Jha

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

6 Scopus citations

Abstract

One of the factors that limits the scale, performance, and sophistication of distributed applications is the difficulty of concurrently executing them on multiple distributed computing resources. In part, this is due to a poor understanding of the general properties and performance of the coupling between applications and dynamic resources. This paper addresses this issue by integrating abstractions representing distributed applications, resources, and execution processes into a pilot-based middleware. The middleware provides a platform that can specify distributed applications, execute them on multiple resource and for different configurations, and is instrumented to support investigative analysis. We analyzed the execution of distributed applications using experiments that measure the benefits of using multiple resources, the late-binding of scheduling decisions, and the use of backfill scheduling.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages953-962
Number of pages10
ISBN (Electronic)9781509021406
DOIs
StatePublished - Jul 18 2016
Event30th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016 - Chicago, United States
Duration: May 23 2016May 27 2016

Publication series

NameProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016

Other

Other30th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016
Country/TerritoryUnited States
CityChicago
Period5/23/165/27/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Abstractions
  • Distributed systems
  • Execution strategies
  • Middleware

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