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Application global state monitoring in optimization of parallel event‐driven simulation
Author(s) -
Maśko Łukasz,
Tudruj Marek
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5015
Subject(s) - computer science , synchronizer , discrete event simulation , queue , timestamp , synchronization (alternating current) , event (particle physics) , state (computer science) , distributed computing , real time computing , parallel computing , simulation , algorithm , computer network , channel (broadcasting) , physics , quantum mechanics , programming language
Summary The paper is concerned with discrete event‐driven simulation, which is a well‐known technique used for modeling and simulating complex parallel systems. The focus of the paper is on distributed simulation, in which multiple simulated event queues are processed in parallel according to the Time Warp approach. With this approach, parallel simulation based on event queues is allowed to progress in an optimistic way until event correlation errors appear in parallel simulation branches what results in simulation rollbacks. In the absence of synchronization between simulator parallel queues, massive processing rollbacks can strongly slow down simulation. The paper presents a distributed optimistic event‐driven simulation control based on simulator global state monitoring. A systematic control of the simulator global states prevents excessive rollbacks in the Time Warp simulation. Each simulation event queue reports its progress to a global synchronizer which monitors the global simulation state based on virtual timestamps of recently processed events. Based on the global state, the synchronizer checks the simulation progress and sends control signals which asynchronously slow down servicing too advanced queues. The paper describes the principles of the proposed approach and experimental results of its basic program implementation. Comparisons to existing parallel simulation methods are provided.

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