Cogent Engineering (Dec 2015)

Petri net modeling and simulation of pipelined redistributions for a deadlock-free system

  • Stavros I. Souravlas,
  • Manos Roumeliotis

DOI
https://doi.org/10.1080/23311916.2015.1057427
Journal volume & issue
Vol. 2, no. 1

Abstract

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The growing use of multiprocessing systems has given rise to the necessity for modeling, verifying, and evaluating their performance in order to fully exploit hardware. The Petri net (PN) formalism is a suitable tool for modeling parallel systems due to its basic characteristics, such as parallelism and synchronization. In addition, the PN formalism allows the incorporation of more details of the real system into the model. Examples of such details include contention for shared resources (like memory) or identification of blocked processes (a definition for blocked processes is found in the Introduction section). In this paper, PNs are considered as a modeling framework to verify and study the performance of parallel pipelined communications. The main strength of the pipelines is that if organized in a proper way, they lead to overlapping of computation, communication, and read/write costs that incur in parallel communications. Most of the well-known pipelined schemes have been evaluated by theoretical analysis, queueing networks, and simulations. Usually, the factors taken into account are scheduling, message classification, and buffer spacing. To the best of our knowledge, there is no work in the literature that uses PN as a modeling tool for verification of the pipeline-based scheme. Apart from verification, a more accurate and complete model should also consider other factors, such as contentions and blocked processes. These factors have a high impact on the performance of a parallel system. The PN model presented in this paper accurately captures the behavior of the pipeline-based parallel communication system. The model considers synchronization, message scheduling, and message classification, while it is proven to be free of deadlocks and contentions. Also, the model is characterized by symmetry, so it can be used for large and complex systems.

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