InforLorV4, Main, Exploration, bibRecord, 000E30

Versatile, scalable, and accurate simulation of distributed applications and platforms

Identifieur interne : 000E30 ( Main/Exploration ); précédent : 000E29; suivant : 000E31

Versatile, scalable, and accurate simulation of distributed applications and platforms

Auteurs : Henri Casanova [États-Unis] ; Arnaud Giersch [France] ; Arnaud Legrand [France] ; Martin Quinson [France] ; Frédéric Suter [France]

Source :

Journal of parallel and distributed computing : (Print) [ 0743-7315 ] ; 2014.

RBID : Pascal:15-0026261

Descripteurs français

Pascal (Inist)
- Calcul réparti, Grille, Poste à poste, Haute performance, Ordinateur personnel, Extensibilité, Simulateur, Volontariat, Modélisation, Simulation ordinateur, Amas, Algorithmique, Validation, ., Informatique dans les nuages.

English descriptors

KwdEn :
- Algorithmics, Cloud computing, Cluster, Computer simulation, Distributed computing, Grid, High performance, Modeling, Peer to peer, Personal computer, Scalability, Simulator, Validation, Volunteering.

Abstract

The study of parallel and distributed applications and platforms, whether in the cluster, grid, peer-to-peer, volunteer, or cloud computing domain, often mandates empirical evaluation of proposed algorithmic and system solutions via simulation. Unlike direct experimentation via an application deployment on a real-world testbed, simulation enables fully repeatable and configurable experiments for arbitrary hypothetical scenarios. Two key concerns are accuracy (so that simulation results are scientifically sound) and scalability (so that simulation experiments can be fast and memory-efficient). While the scalability of a simulator is easily measured, the accuracy of many state-of-the-art simulators is largely unknown because they have not been sufficiently validated. In this work we describe recent accuracy and scalability advances made in the context of the SimGrid simulation framework. A design goal of SimGrid is that it should be versatile, i.e., applicable across all aforementioned domains. We present quantitative results that show that SimGrid compares favorably with state-of-the-art domain-specific simulators in terms of scalability, accuracy, or the trade-off between the two. An important implication is that, contrary to popular wisdom, striving for versatility in a simulator is not an impediment but instead is conducive to improving both accuracy and scalability.

Url:

https://hal.inria.fr/hal-01017319

Affiliations:

Le document en format XML

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<front><div type="abstract" xml:lang="en">The study of parallel and distributed applications and platforms, whether in the cluster, grid, peer-to-peer, volunteer, or cloud computing domain, often mandates empirical evaluation of proposed algorithmic and system solutions via simulation. Unlike direct experimentation via an application deployment on a real-world testbed, simulation enables fully repeatable and configurable experiments for arbitrary hypothetical scenarios. Two key concerns are accuracy (so that simulation results are scientifically sound) and scalability (so that simulation experiments can be fast and memory-efficient). While the scalability of a simulator is easily measured, the accuracy of many state-of-the-art simulators is largely unknown because they have not been sufficiently validated. In this work we describe recent accuracy and scalability advances made in the context of the SimGrid simulation framework. A design goal of SimGrid is that it should be versatile, i.e., applicable across all aforementioned domains. We present quantitative results that show that SimGrid compares favorably with state-of-the-art domain-specific simulators in terms of scalability, accuracy, or the trade-off between the two. An important implication is that, contrary to popular wisdom, striving for versatility in a simulator is not an impediment but instead is conducive to improving both accuracy and scalability.</div>
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Versatile, scalable, and accurate simulation of distributed applications and platforms

Versatile, scalable, and accurate simulation of distributed applications and platforms

Source :

Descripteurs français

English descriptors

Abstract

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