PARM: Physics Aware Runtime Manager for large-scale scientific and engineering applications

Yeliang Zhang, Salim Hariri, Jianwei Xiang, Jim Yeh

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

Abstract

Choosing the ideal algorithms and solutions for a scientific application is difficult because of the heterogeneity and dynamism of the application execution phases at runtime. In this paper we present an autonomic programming framework that is capable of self-configuring and self-composing the application solution methods in order to exploit the heterogeneity and the dynamism of the application execution states. We focus our approach on Partial Differential Equation (PDE) problems involving multiple computational phases that are defined in terms of their spatial and temporal characteristics. We have implemented a Physics Aware Runtime Manager (FARM) that periodically monitors and analyzes the spatial and temporal characteristics of the application to identify its current execution phase (state). Then FARM will determine an appropriate numerical schemes and algorithms that will most efficiently exploit the current state. Our preliminary results show a significant speedup can be achieved by using PARM.

Original languageEnglish (US)
Title of host publicationProceedings of the 15th IEEE International Symposium on High Performance Distributed Computing, HPDC-15
Pages363-364
Number of pages2
StatePublished - 2006
Event15th IEEE International Symposium on High Performance Distributed Computing, HPDC-15 - Paris, France
Duration: Jun 19 2006Jun 23 2006

Publication series

NameProceedings of the IEEE International Symposium on High Performance Distributed Computing
Volume2006
ISSN (Print)1082-8907

Other

Other15th IEEE International Symposium on High Performance Distributed Computing, HPDC-15
Country/TerritoryFrance
CityParis
Period6/19/066/23/06

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

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