Exploring the performance and mapping of HPC applications to platforms in the cloud

Abhishek Gupta, Laxmikant V. Kalé, Filippo Gioachin, Verdi March, Chun Hui Suen, Bu Sung Lee, Paolo Faraboschi, Richard Kaufmann, Dejan Milojicic

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

Abstract

This paper presents a scheme to optimize the mapping of HPC applications to a set of hybrid dedicated and cloud resources. First, we characterize application performance on dedicated clusters and cloud to obtain application signatures. Then, we propose an algorithm to match these signatures to resources such that performance is maximized and cost is minimized. Finally, we show simulation results revealing that in a concrete scenario our proposed scheme reduces the cost by 60% at only 10-15% performance penalty vs. a non optimized configuration. We also find that the execution overhead in cloud can be minimized to a negligible level using thin hypervisors or OS-level containers.

Original languageEnglish (US)
Title of host publicationHPDC '12 - Proceedings of the 21st ACM Symposium on High-Performance Parallel and Distributed Computing
Pages121-122
Number of pages2
DOIs
StatePublished - Jul 23 2012
Event21st ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC '12 - Delft, Netherlands
Duration: Jun 18 2012Jun 22 2012

Publication series

NameHPDC '12 - Proceedings of the 21st ACM Symposium on High-Performance Parallel and Distributed Computing

Other

Other21st ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC '12
CountryNetherlands
CityDelft
Period6/18/126/22/12

Keywords

  • Clouds
  • High Performance Computing
  • Resource Scheduling

ASJC Scopus subject areas

  • Software

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