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Authors: Paul Marshall 1 ; Henry Tufo 2 ; Kate Keahey 3 ; David La Bissoniere 3 and Matthew Woitaszek 4

Affiliations: 1 University of Colorado, United States ; 2 University of Colorado at Boulder and National Center for Atmospheric Research, United States ; 3 Argonne National Laboratory and University of Chicago, United States ; 4 National Center for Atmospheric Research, United States

Keyword(s): Infrastructure-as-a-Service, Cloud Computing, Elastic Computing, Recontextualization.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Context ; Context Sensitive Applications ; Paradigm Trends ; Service Technology and Infrastructure Issues ; Services ; Services Applications ; Software Engineering

Abstract: Infrastructure-as-a-service (IaaS) clouds, such as Amazon EC2, offer pay-for-use virtual resources on-demand. This allows users to outsource computation and storage when needed and create elastic computing environments that adapt to changing demand. However, existing services, such as cluster resource managers (e.g. Torque), do not include support for elastic environments. Furthermore, no recontextualization services exist to reconfigure these environments as they continually adapt to changes in demand. In this paper we present an architecture for a large-scale elastic cluster environment. We extend an open-source elastic IaaS manager, the Elastic Processing Unit (EPU), to support the Torque batch-queue scheduler. We also develop a lightweight REST-based recontextualization broker that periodically reconfigures the cluster as nodes join or leave the environment. Our solution adds nodes dynamically at runtime and supports MPI jobs across dis-tributed resources. For experimental evalua tion, we deploy our solution using both NSF FutureGrid and Amazon EC2. We demonstrate the ability of our solution to create multi-cloud deployments and run batch-queued jobs, recontextualize 256 node clusters within one second of the recontextualization period, and scale to over 475 nodes in less than 15 minutes. (More)

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Paper citation in several formats:
Marshall, P.; Tufo, H.; Keahey, K.; La Bissoniere, D. and Woitaszek, M. (2012). Architecting a Large-scale Elastic Environment - Recontextualization and Adaptive Cloud Services for Scientific Computing. In Proceedings of the 7th International Conference on Software Paradigm Trends - ICSOFT; ISBN 978-989-8565-19-8; ISSN 2184-2833, SciTePress, pages 409-418. DOI: 10.5220/0004081704090418

@conference{icsoft12,
author={Paul Marshall. and Henry Tufo. and Kate Keahey. and David {La Bissoniere}. and Matthew Woitaszek.},
title={Architecting a Large-scale Elastic Environment - Recontextualization and Adaptive Cloud Services for Scientific Computing},
booktitle={Proceedings of the 7th International Conference on Software Paradigm Trends - ICSOFT},
year={2012},
pages={409-418},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004081704090418},
isbn={978-989-8565-19-8},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Software Paradigm Trends - ICSOFT
TI - Architecting a Large-scale Elastic Environment - Recontextualization and Adaptive Cloud Services for Scientific Computing
SN - 978-989-8565-19-8
IS - 2184-2833
AU - Marshall, P.
AU - Tufo, H.
AU - Keahey, K.
AU - La Bissoniere, D.
AU - Woitaszek, M.
PY - 2012
SP - 409
EP - 418
DO - 10.5220/0004081704090418
PB - SciTePress