SimGrid: a Generic Framework for Large-Scale Distributed Experiments
Identifieur interne : 004566 ( Hal/Corpus ); précédent : 004565; suivant : 004567SimGrid: a Generic Framework for Large-Scale Distributed Experiments
Auteurs : Henri Casanova ; Arnaud Legrand ; Martin QuinsonSource :
Abstract
Distributed computing is a very broad and active research area comprising fields such as cluster computing, computational grids, desktop grids and peer-to-peer (P2P) systems. Unfortunately, it is often impossible to obtain theoretical or analytical results to compare the performance of algorithms targeting such systems. One possibility is to conduct large numbers of back-to-back experiments on real platforms. While this is possible on tightly-coupled platforms, it is infeasible on modern distributed platforms as experiments are labor-intensive and results typically not reproducible. Consequently, one must resort to simulations, which enable reproducible results and also make it possible to explore wide ranges of platform and application scenarios. In this paper we describe the SimGrid framework, a simulation-based framework for evaluating cluster, grid and P2P algorithms andheuristics. This paper focuses on SimGrid v3, which greatly improves on previous versions thanks to a novel and validated modular simulation engine that achieves higher simulation speed without hindering simulation accuracy. Also, two new user interfaces were added to broaden the targeted research community. After surveying existing tools and methodologies we describe the key features and benefits of SimGrid.
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Unfortunately, it is often impossible to obtain theoretical or analytical results to compare the performance of algorithms targeting such systems. One possibility is to conduct large numbers of back-to-back experiments on real platforms. While this is possible on tightly-coupled platforms, it is infeasible on modern distributed platforms as experiments are labor-intensive and results typically not reproducible. Consequently, one must resort to simulations, which enable reproducible results and also make it possible to explore wide ranges of platform and application scenarios. In this paper we describe the SimGrid framework, a simulation-based framework for evaluating cluster, grid and P2P algorithms andheuristics. This paper focuses on SimGrid v3, which greatly improves on previous versions thanks to a novel and validated modular simulation engine that achieves higher simulation speed without hindering simulation accuracy. Also, two new user interfaces were added to broaden the targeted research community. After surveying existing tools and methodologies we describe the key features and benefits of SimGrid.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">SimGrid: a Generic Framework for Large-Scale Distributed Experiments</title><author role="aut"><persName><forename type="first">Henri</forename><surname>Casanova</surname></persName><email></email><idno type="halauthor">77184</idno><affiliation ref="#struct-10703"></affiliation></author><author role="aut"><persName><forename type="first">Arnaud</forename><surname>Legrand</surname></persName><email>arnaud.legrand@imag.fr</email><idno type="halauthor">293762</idno><affiliation ref="#struct-37506"></affiliation></author><author role="aut"><persName><forename type="first">Martin</forename><surname>Quinson</surname></persName><email>martin.quinson@loria.fr</email><idno type="idhal">martin-quinson</idno><idno type="halauthor">151305</idno><affiliation ref="#struct-2346"></affiliation></author><editor role="depositor"><persName><forename>Martin</forename><surname>Quinson</surname></persName><email>martin.quinson@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2008-03-04 17:31:50</date><date type="whenModified">2016-05-18 08:56:24</date><date type="whenReleased">2008-03-04 17:33:10</date><date type="whenProduced">2008-04</date><date type="whenEndEmbargoed">2008-03-04</date><ref type="file" target="https://hal.inria.fr/inria-00260697/document"><date notBefore="2008-03-04"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/inria-00260697/file/uksim.pdf"><date notBefore="2008-03-04"></date></ref></edition><respStmt><resp>contributor</resp><name key="113845"><persName><forename>Martin</forename><surname>Quinson</surname></persName><email>martin.quinson@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00260697</idno><idno type="halUri">https://hal.inria.fr/inria-00260697</idno><idno type="halBibtex">casanova:inria-00260697</idno><idno type="halRefHtml">10th IEEE International Conference on Computer Modeling and Simulation - EUROSIM / UKSIM 2008, Apr 2008, Cambrige, United Kingdom. IEEE, 2008</idno><idno type="halRef">10th IEEE International Conference on Computer Modeling and Simulation - EUROSIM / UKSIM 2008, Apr 2008, Cambrige, United Kingdom. IEEE, 2008</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="UNIV-GRENOBLE1" p="UGA">Université Joseph Fourier - Grenoble I</idno><idno type="stamp" n="UNIV-PMF_GRENOBLE" p="UGA">Université Pierre-Mendès-France - Grenoble II</idno><idno type="stamp" n="INRIA-RHA">INRIA Grenoble - Rhône-Alpes</idno><idno type="stamp" n="LIG" p="UGA">Laboratoire d'Informatique de Grenoble</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA-NSS" p="LORIA">Réseaux, systèmes et services</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="GRID5000">Grid'5000</idno><idno type="stamp" n="UGA">HAL Grenoble Alpes</idno><idno type="stamp" n="INPG" p="UGA">Institut polytechnique de Grenoble</idno><idno type="stamp" n="INRIA2">INRIA 2</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">SimGrid: a Generic Framework for Large-Scale Distributed Experiments</title><author role="aut"><persName><forename type="first">Henri</forename><surname>Casanova</surname></persName><idno type="halAuthorId">77184</idno><affiliation ref="#struct-10703"></affiliation></author><author role="aut"><persName><forename type="first">Arnaud</forename><surname>Legrand</surname></persName><email>arnaud.legrand@imag.fr</email><idno type="halAuthorId">293762</idno><affiliation ref="#struct-37506"></affiliation></author><author role="aut"><persName><forename type="first">Martin</forename><surname>Quinson</surname></persName><email>martin.quinson@loria.fr</email><idno type="idHal">martin-quinson</idno><idno type="halAuthorId">151305</idno><affiliation ref="#struct-2346"></affiliation></author></analytic><monogr><meeting><title>10th IEEE International Conference on Computer Modeling and Simulation - EUROSIM / UKSIM 2008</title><date type="start">2008-04</date><settlement>Cambrige</settlement><country key="GB">United Kingdom</country></meeting><imprint><publisher>IEEE</publisher><date type="datePub">2008</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><classCode scheme="halDomain" n="info.info-dc">Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">Distributed computing is a very broad and active research area comprising fields such as cluster computing, computational grids, desktop grids and peer-to-peer (P2P) systems. Unfortunately, it is often impossible to obtain theoretical or analytical results to compare the performance of algorithms targeting such systems. One possibility is to conduct large numbers of back-to-back experiments on real platforms. While this is possible on tightly-coupled platforms, it is infeasible on modern distributed platforms as experiments are labor-intensive and results typically not reproducible. Consequently, one must resort to simulations, which enable reproducible results and also make it possible to explore wide ranges of platform and application scenarios. In this paper we describe the SimGrid framework, a simulation-based framework for evaluating cluster, grid and P2P algorithms andheuristics. This paper focuses on SimGrid v3, which greatly improves on previous versions thanks to a novel and validated modular simulation engine that achieves higher simulation speed without hindering simulation accuracy. Also, two new user interfaces were added to broaden the targeted research community. After surveying existing tools and methodologies we describe the key features and benefits of SimGrid.</abstract><particDesc><org type="consortium">Grid'5000</org></particDesc></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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