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 application/system sensitive reactive and proactive partitioning strategies that form a part of the GridARM autonomic runtime management framework. An evaluation using different SAMR kernels and system workloads is presented to demonstrate the improvement in overall application performance.
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S. Chandra M. Parashar S. Hariri (December 2003) GridARM: An Autonomic Runtime Management Framework for SAMR Applications in Grid Environments, Autonomic Applications Workshop High Performance Computing (HiPC’03) India. 286–295
S. Chandra M. Parashar (November 2002) ARMaDA: An Adaptive Application-Sensitive Partitioning Framework for Structured Adaptive Mesh Refinement Applications Proc of Parallel and Distributed Computing Systems. (PDCS’02) Cambridge, MA. 446–451
M. Parashar, http://www.caip.rutgers.edu/TASSL/Projects/GrACE, GrACE homepage.
J. Steensland, http://www.caip.rutgers.edu/johans/vampire, Vampire homepage.
J. Steensland S. Chandra (December 2002) ArticleTitleParashar, An Application-Centric Characterization of Domain-Based SFC Partitioners for Parallel SAMR IEEE Trans. on Parallel and Distributed Sys. 13 IssueID12 1275–1289
R. Wolski N.T. Spring J. Hayes (October 1999) ArticleTitleThe Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing J. Future Generation Comput. Syst. 15 IssueID5–6 757–768
S. Sinha M. Parashar (2002) ArticleTitleAdaptive System-Sensitive Partitioning of AMR Applications on Heterogeneous Clusters, Cluster Computing: The J. Networks, Software Tools, and Applications Kluwer Academic Publishers. 5 IssueID4 343–352
H. Zhu, M. Parashar, J. Yang, Y. Zhang, S. Rao, and S.Hariri, Self Adapting, Self Optimizing Runtime Management of Grid Applications using PRAGMA, Proc. of NSF NGS Program Workshop, IEEE/ACM 17th IPDPS, Nice, France, CDROM, 7P. (April 2003).
S. Chandra S. Sinha M. Parashar Y. Zhang J. Yang S. Hariri (December 2002) ArticleTitleAdaptive Runtime Management of SAMR Applications Proc. of High Performance Computing (HiPC’02), LNCS, India. 2552 564–574
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Chandra, S., Parashar, M., Yang, J. et al. Investigating Autonomic Runtime Management Strategies for SAMR Applications. Int J Parallel Prog 33, 247–259 (2005). https://doi.org/10.1007/s10766-005-3589-z
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DOI: https://doi.org/10.1007/s10766-005-3589-z