A performance and scalability analysis framework for parallel discrete event simulators

Balakrishnan, Vijay; Radhakrishnan, R.; Rao, Dhananjai M.; Abu-Ghazaleh, Nael; Wilsey, Philip A.

doi:10.1016/s0928-4869(01)00033-7

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…A substantial amount of work has been directed at generating synthetic simulation models to exercise parallel simulation kernels [2,7,9,18]. These synthetic models are commonly used by the research community to evaluate and report performance results.…”

Section: Background and Motivationmentioning

confidence: 99%

Some Properties of Events Executed in Discrete-Event Simulation Models

Wilsey

2016

Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

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The field of computer architecture uses quantitative methods to drive the computer system design process. By quantitatively profiling the run time characteristics of computer programs, the principal processing needs of commonly used programs became well understood and computer architects can focus their design solutions toward those needs. The DESMetrics project is established to follow this quantitative model by profiling the execution of Discrete Event Simulation (DES) models in order to focus optimization efforts within DES execution frameworks (and especially parallel DES engines). In particular, the DESMetrics project is designed to capture the run time characteristics of event execution in DES models. Because DES models tend to have fine grained computational processing requirements, the DESMetrics project focuses on the event dependencies and their exchange between the objects in the simulation. For now, we assume that optimization of the actual event processing is well served by conventional compiler and architecture solutions. Although, as will become clear later in Section 6, the possibility of identifying scheduling blocks of events that could potentially be schedule together can be achieved -at least within a single simulation object.

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Section: Background and Motivationmentioning

confidence: 99%

Some Properties of Events Executed in Discrete-Event Simulation Models

Wilsey

2016

Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

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“…The classical performance factors of a PDES system are depicted in Figure 1, similarly to Figure 2 of [2]. Most works of the PDES literature focus on the simulation engine itself.…”

Section: Context and State Of The Artmentioning

confidence: 99%

Parallel Simulation of Peer-to-Peer Systems

Quinson

Rosa

Thiéry

2012

2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (Ccgrid 2012)

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International audienceDiscrete Event Simulation (DES) is one of the major experimental methodologies in several scientific and engineering domains. Parallel Discrete Event Simulation (PDES) constitutes a very active research field for at least three decades, to surpass speed and size limitations. In the context of Peer-to-Peer (P2P) protocols, most studies rely on simulation. Surprisingly enough, none of the mainstream P2P discrete event simulators allows parallel simulation although the tool scalability is considered as the major quality metric by several authors. This paper revisits the classical PDES methods in the light of distributed system simulation and proposes a new parallelization design specifically suited to this context. The constraints posed on the simulator internals are presented, and an OS-inspired architecture is proposed. In addition, a new thread synchronization mechanism is introduced for efficiency despite the very fine grain parallelism inherent to the target scenarios. This new architecture was implemented into the general-purpose open-source simulation framework SimGrid. We show that the new design does not hinder the tool scalability. In fact, the sequential version of SimGrid remains orders of magnitude more scalable than state of the art simulators, while the parallel execution allows to save up to 33% of the execution time on Chord simulation

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“…Diversas pesquisas , Suppi et al, 2000, Liljenstam et al, 2001, Ferscha & Malony, 2001, Balakrishnan et al, 2001, Xu & Chung, 2004, Teo & Onggo, 2004, Teo et al, 2005, Wilmarth et al, 2005 (Alonso et al, 1998, Boukerche & Tropper, 2001, Teo et al, 2002, Park et al, 2004 …”

Section: Comparação Entre Os Protocolos Conservadores E Otimistasmentioning

confidence: 99%

"Simulação distribuída utilizando protocolos independentes e troca dinâmica nos processos lógicos"

Kawabata¹

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A performance and scalability analysis framework for parallel discrete event simulators

Cited by 5 publications

References 24 publications

Some Properties of Events Executed in Discrete-Event Simulation Models

Some Properties of Events Executed in Discrete-Event Simulation Models

Parallel Simulation of Peer-to-Peer Systems

"Simulação distribuída utilizando protocolos independentes e troca dinâmica nos processos lógicos"

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