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Article

Dynamic Malleability in Iterative MPI Applications

Published: 14 May 2007 Publication History

Abstract

Malleability enables a parallel application's execution system to split or merge processes modifying granularity. While process migration is widely used to adapt applications to dynamic execution environments, it is limited by the granularity of the application's processes. Malleability empowers process migration by allowing the application's processes to expand or shrink following the availability of resources. We have implemented malleability as an extension to the PCM (Process Checkpointing and Migration) library, a user-level library for iterative MPI applications. PCM is integrated with the Internet Operating System (IOS), a framework for middleware-driven dynamic application reconfiguration. Our approach requires minimal code modifications and enables transparent middlewaretriggered reconfiguration. Experimental results using a two-dimensional data parallel program that has a regular communication structure demonstrate the usefulness of malleability.

Cited By

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  • (2024)On the Performance of Malleable APGAS Programs and Batch Job SchedulersSN Computer Science10.1007/s42979-024-02641-75:4Online publication date: 27-Mar-2024
  • (2023)Evaluating the Potential of Elastic Jobs in HPC SystemsProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624199(1324-1333)Online publication date: 12-Nov-2023
  • (2023)Efficient data redistribution for malleable applicationsProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624110(416-426)Online publication date: 12-Nov-2023
  • Show More Cited By

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cover image Guide Proceedings
CCGRID '07: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
May 2007
900 pages
ISBN:0769528333

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IEEE Computer Society

United States

Publication History

Published: 14 May 2007

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Cited By

View all
  • (2024)On the Performance of Malleable APGAS Programs and Batch Job SchedulersSN Computer Science10.1007/s42979-024-02641-75:4Online publication date: 27-Mar-2024
  • (2023)Evaluating the Potential of Elastic Jobs in HPC SystemsProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624199(1324-1333)Online publication date: 12-Nov-2023
  • (2023)Efficient data redistribution for malleable applicationsProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624110(416-426)Online publication date: 12-Nov-2023
  • (2023)Malleable APGAS Programs and Their Support in Batch Job SchedulersEuro-Par 2023: Parallel Processing Workshops10.1007/978-3-031-48803-0_8(89-101)Online publication date: 28-Aug-2023
  • (2022)Resiliency in numerical algorithm design for extreme scale simulationsInternational Journal of High Performance Computing Applications10.1177/1094342021105518836:2(251-285)Online publication date: 1-Mar-2022
  • (2022)Towards Dynamic Resource Management with MPI Sessions and PMIxProceedings of the 29th European MPI Users' Group Meeting10.1145/3555819.3555856(57-67)Online publication date: 14-Sep-2022
  • (2021)Transparent Resource Elasticity for Task-Based Cluster Environments with Work Stealing50th International Conference on Parallel Processing Workshop10.1145/3458744.3473361(1-10)Online publication date: 9-Aug-2021
  • (2018)DROMWorkshop Proceedings of the 47th International Conference on Parallel Processing10.1145/3229710.3229752(1-10)Online publication date: 13-Aug-2018
  • (2015)A2L2Proceedings of the 8th International Workshop on Virtualization Technologies in Distributed Computing10.1145/2755979.2755983(11-19)Online publication date: 15-Jun-2015
  • (2014)Maximizing throughput of overprovisioned HPC data centers under a strict power budgetProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SC.2014.71(807-818)Online publication date: 16-Nov-2014
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