Autonomic proactive runtime partitioning strategies for SAMR applications

Yeliang Zhang, Jingmei Yang, Salim Hariri, Sumir Chandra, Manish Parashar

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

7 Scopus citations

Abstract

Dynamic structured adaptive mesh refinement (SAMR) techniques along with the emergence of the computational Grid offer the potential for realistic scientific and engineering simulations of complex physical phenomena. However, the inherent dynamic nature of SAMR applications coupled with the heterogeneity and dynamism of the underlying Grid environment present significant research challenges. This paper presents proactive runtime partitioning strategies based on performance prediction functions that are experimentally formulated in terms of system parameters such as CPU load and available memory. These proactive partitioning strategies form a part of the GridARM autonomic framework which enables self-managing, self-adapting, and self-optimizing SAMR applications on the Grid. Experimental evaluation of the proactive schemes using the 3-D Richtmyer-Meshkov compressible fluid dynamics kernel for different system configurations and workloads demonstrates the improvement in overall runtime performance.

Original languageEnglish (US)
Title of host publicationProceedings - 18th International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM)
Pages2783-2790
Number of pages8
StatePublished - 2004
EventProceedings - 18th International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM) - Santa Fe, NM, United States
Duration: Apr 26 2004Apr 30 2004

Publication series

NameProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM)
Volume18

Other

OtherProceedings - 18th International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM)
Country/TerritoryUnited States
CitySanta Fe, NM
Period4/26/044/30/04

ASJC Scopus subject areas

  • General Engineering

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