Generative Coordination Environments Supporting Parallel Discrete Event Simulation

Abstract The utilization of coordination languages based on the generative paradigm for supporting the implementation of parallel discrete-event simulators is considered. A parallel simulation methodology called Active-Events (ActE) which is based on a sophisticated generative coordination model is proposed in order to make the task of designing a parallel simulator easier and to fully exploit the capabilities of coordination languages. An implementation of mechanisms of the coordination model by relying on the Linda coordination language is proposed. A simulator for queuing models based on ActE and developed in the coordination framework thus resulting is experimentally studied to assess the suitability of different mechanisms which implement the particular object retrieval criterion of the coordination model.

[1]  Nicholas Carriero,et al.  How to write parallel programs - a first course , 1990 .

[2]  David Jefferson,et al.  Fast Concurrent Simulation Using the Time Warp Mechanism. Part I. Local Control. , 1982 .

[3]  Nicholas Carriero,et al.  Linda in context , 1989, CACM.

[4]  Nicholas Carriero,et al.  Coordination languages and their significance , 1992, CACM.

[5]  Richard M. Fujimoto,et al.  Parallel discrete event simulation , 1990, CACM.

[6]  David Kaminsky Adaptive parallelism with Piranha , 1995 .

[7]  Richard M. Fujimoto,et al.  Feature Article - Parallel Discrete Event Simulation: Will the Field Survive? , 1993, INFORMS J. Comput..

[8]  Alessandro Fabbri,et al.  SQTW: a mechanism for state-dependent parallel simulation. Description and experimental study , 1997 .

[9]  Friedemann Mattern,et al.  Efficient Algorithms for Distributed Snapshots and Global Virtual Time Approximation , 1993, J. Parallel Distributed Comput..

[10]  David Gelernter,et al.  The Linda® Alternative to Message-Passing Systems , 1994, Parallel Comput..

[11]  David Gelernter,et al.  Turingware: an integrated approach to collaborative computing , 1996 .

[12]  Isi Mitrani Simulation techniques for discrete event systems , 1982, Cambridge computer science texts.

[13]  David R. Jefferson,et al.  Virtual time , 1985, ICPP.

[14]  David Gelernter,et al.  Supercomputing out of recycled garbage: preliminary experience with Piranha , 1992, ICS '92.

[15]  K. Mani Chandy,et al.  Distributed Simulation: A Case Study in Design and Verification of Distributed Programs , 1979, IEEE Transactions on Software Engineering.

[16]  Richard M. Fujimoto,et al.  The virtual time machine , 1989, SPAA '89.

[17]  Yehoshua Sagiv Concurrent Operations on B*-Trees with Overtaking , 1986, J. Comput. Syst. Sci..

[18]  R. M. Fujimoto,et al.  Parallel discrete event simulation , 1989, WSC '89.

[19]  Antony I. T. Rowstron,et al.  Solving the LINDA Multiple rd Problem , 1996, COORDINATION.

[20]  Charles H. Sauer,et al.  Elements of Practical Performance Modeling , 1984, Int. CMG Conference.

[21]  Robert G. Sargent,et al.  A New Process to Processor Assignment Criterion for Reducing Rollbacks in Optimistic Simulation , 1993, J. Parallel Distributed Comput..

[22]  Thilo Kielmann,et al.  Designing a Coordination Model for Open Systems , 1996, COORDINATION.