An Object-Oriented Time Warp Simulation Kernel

Radhakrishnan, R.; Martin, Dale E.; Chetlur, Malolan; Rao, Dhananjai M.; Wilsey, Philip A.

doi:10.1007/3-540-49372-7_2

Cited by 50 publications

(42 citation statements)

References 8 publications

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“…Examples of such environments are: YADDES (Yet Another Distributed Discrete Event Simulator) [129], SPEEDES (Synchronous Parallel Environment for Emulation and Discrete Event Simulation) [130], WARPED [131], HLA (High-Level Architecture) [132], WarpIV [133], Parsec (Parallel Simulation Environment for Complex Systems) [139], POSE (Parallel Object-oriented Simulation Environment) [140], JAMES II (JAva-based Multipurpose Environment for Simulation) [141], lsik [134], and Unified Framework [142].…”

Section: Parallel and Distributed Environmentsmentioning

confidence: 99%

Synchronization methods in parallel and distributed discrete-event simulation

Jafer

Liu

Wainer

2013

Simulation Modelling Practice and Theory

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a b s t r a c tThis work attempts to provide insight into the problem of executing discrete event simulation in a distributed fashion. The article serves as the state of the art in Parallel DiscreteEvent Simulation (PDES) by surveying existing algorithms and analyzing the merits and drawbacks of various techniques. We discuss the main characteristics of existing synchronization methods for parallel and distributed discrete event simulation. The two major categories of synchronization protocols, namely conservative and optimistic, are introduced and various approaches within each category are presented. We also present the latest efforts towards PDES on emerging platforms such as heterogeneous multicore processors, Web services, as well as Grid and Cloud environment.Ó 2012 Elsevier B.V. All rights reserved. Parallel discrete-event simulationWith the computing power and advanced software available today, modeling and simulation has become a cost-effective tool for detailed analysis of a broad array of natural and artificial systems. Parallel and distributed simulation is widely accepted as the technology of choice to speed up large-scale discrete-event simulation and to promote reusability and interoperability of simulation components. Parallel Discrete-Event Simulation (PDES) has received increasing interest as simulations become more time consuming and geographically distributed. A rich literature has already been developed in the last three decades, taking advantage of the increasing availability of highly parallel and distributed computing platforms. It has been several years since the last survey by Perumalla [5] and a refreshed review of the latest developments would be needed for us to ponder new research initiatives, especially on emerging platforms such as many-core processors, Internetscale simulation environments, and cloud-based virtualized infrastructures.In parallel and distributed simulations, the entire simulation task is divided into a set of smaller subtasks with each executed on a different processor or node. Hence, the simulation system is viewed as a collection of concurrent processes, each modeling a different part of the physical system and executing on a dedicated processor in a sequential fashion. These processes communicate with each other by exchanging time-stamped event messages. An event refers to an update to simulation system state at a specific simulation time instant. Throughout the simulation, events arrive at destination processes, and depending on the delivery ordering system of the simulation, they are processed differently. The two commonly used orderings are (1) receive-order and (2) timestamp-order. With the first type, events are delivered to the destination processes when they arrive at the destination. On the other hand, with the timestamp-order, events are delivered in non-decreasing order of their timestamp, requiring runtime checks and buffering to ensure such ordering.1569-190X/$ -see front matter Ó

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Section: Parallel and Distributed Environmentsmentioning

confidence: 99%

Synchronization methods in parallel and distributed discrete-event simulation

Jafer

Liu

Wainer

2013

Simulation Modelling Practice and Theory

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“…Finally, the reverse engineering has been partially applied to DEVS/Schema and DEVSML. (2) Behavior limited by the corresponding SCXML Schema definition (3) Implemented for two simulation platforms (DEVSJAVA and xDEVS)…”

Section: Standardizing Devs Model Representationmentioning

confidence: 99%

An Introduction to DEVS Standardization

Wainer¹,

Al-Zoubi²,

Hill³

et al. 2010

Computational Analysis, Synthesis, &Amp; Design Dynamic Systems

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“…CCD++ supports both standalone and parallel conservative simulations. The simulator is built on top of the WARPED kernel [15], which provides services for defining different types of processes (simulation objects). Simulation objects on a physical processor are grouped into an LP, and they communicate through Message Passing Interface (MPI).…”

Section: Introductionmentioning

confidence: 99%

Global Lookahead Management (GLM) Protocol for Conservative DEVS Simulation

Jafer

Wainer

2010

2010 IEEE/ACM 14th International Symposium on Distributed Simulation and Real Time Applications

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An approach to carrying out asynchronous distributed simulation of multiprocessor message passing architectures is presented. Aiming at achieving better performance on Conservative DEVS-based simulations, we introduce the GLM protocol which borrows the idea of safe processing intervals from the conservative time window algorithm and maintains global synchronization in a fashion similar to the distributed snapshot technique. Under the GLM scheme, a central lookahead manager (LM) exists which is in charge of receiving every LP's lookahead, identifying the global minimum lookahead of the system, and broadcasting it via null messages to all LPs. The simulation is divided into cycles of two phases: Parallel phase and Broadcast phase. The GLM protocol is asynchronous and the central lookahead manager is not expected to be a bottleneck since the only message transmissions involving it take place when all LPs are blocked waiting for permission to advance their LVTs. The results presented in this paper show that the GLM protocol not only significantly reduces the total number of null messages, but it improves the performance and higher speedups are achieved.

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An Object-Oriented Time Warp Simulation Kernel

Cited by 50 publications

References 8 publications

Synchronization methods in parallel and distributed discrete-event simulation

Synchronization methods in parallel and distributed discrete-event simulation

An Introduction to DEVS Standardization

Global Lookahead Management (GLM) Protocol for Conservative DEVS Simulation

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