A P2P approach to many tasks computing for scientific workflows

Authors:
Eduardo Ogasawara;Jonas Dias;Daniel Oliveira;Carla Rodrigues;Carlos Pivotto;Rafael Antas;Vanessa Braganholo;Patrick Valduriez;Marta Mattoso
Affiliations:
COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil and Federal Center of Technological Education, Rio de Janeiro, Brazil;COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;Fluminense Federal University;INRIA & LIRMM, Montpellier, France;COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Venue:
VECPAR'10 Proceedings of the 9th international conference on High performance computing for computational science
Year:
2010

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Abstract

Scientific Workflow Management Systems (SWfMS) are being used intensively to support large scale in silico experiments. In order to reduce execution time, current SWfMS have exploited workflow parallelization under the arising Many Tasks Computing (MTC) paradigm in homogeneous computing environments, such as multiprocessors, clusters and grids with centralized control. Although successful, this solution no longer applies to heterogeneous computing environments, such as hybrid clouds, which may combine users' own computing resources with multiple edge clouds. A promising approach to address this challenge is Peer-to-Peer (P2P) which relies on decentralized control to deal with scalability and dynamic behavior of resources. In this paper, we propose a new P2P approach to apply MTC in scientific workflows. Through the results of simulation experiments, we show that our approach is promising.