Application-aware management parallel simulation collections

Siu Man Yau, Vijay Karamcheti, Denis Zorin, Kostadin Damevski, Steven G. Parker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a system deployed on parallel clusters to manage a collection of parallel simulations that make up a computational study. It explores how such a system can extend traditional parallel job scheduling and resource allocation techniques to incorporate knowledge specific to the study. Using a UINTAH-based helium gas simulation code (ARCHES) and the SimX system for multi-experiment computational studies, this paper demonstrates that, by using application-specific knowledge in resource allocation and scheduling decisions, one can reduce the run time of a computational study from over 20 hours to under 4.5 hours on a 32-processor cluster, and from almost 11 hours to just over 3.5 hours on a 64-processor cluster.

Original languageEnglish
Title of host publicationProceedings of the 2009 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP'09
Pages35-44
Number of pages10
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP'09 - Raleigh, NC, United States
Duration: 14 Feb 200918 Feb 2009

Publication series

NameProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP

Conference

Conference2009 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP'09
Country/TerritoryUnited States
CityRaleigh, NC
Period14/02/0918/02/09

Keywords

  • High-throughput computing
  • Parallel system

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