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Design Issues for Optimistic Distributed Discrete Event Simulation

Yi‐Bing Lin

Open publisher page 4 citations

Abstract

Simulation is a powerful tool for studying the dynamics of a system. However, simulation is time-consuming. Thus, it is natural to attempt to use multiple processors to speed up the simulation process. Many protocols have been proposed to perform discrete event simulation in multi-processor environments. Most of these distributed discrete event simulation protocols are either conservative or optimistic. The most common optimistic distributed simulation protocol is called Time Warp. Several issues must be considered when designing a Time Warp simulation; examples are reducing the state saving overhead and designing the global control mechanism (i. e., global virtual time computation, memory management, distributed termination, and fault tolerance). This paper addresses these issues. We propose a heuristic to select the checkpoint interval to reduce the state saving overhead, generalize a previously proposed global virtual time computation algorithm, and present new algorithms for memory management, distributed termination, and fault tolerance. The main contribution of this paper is to provide guidelines for designing an efficient Time Warp simulation.

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What this paper is about

Simulation is a powerful tool for studying the dynamics of a system. However, simulation is time-consuming. Thus, it is natural to attempt to use multiple processors to speed up the simulation process. Many protocols have been proposed to perform discrete event simulation in multi-processor environments. Most of these distributed discrete event simulation protocols are either conservative or optimistic. The most common optimistic distributed simulation protocol is called Time Warp. Several issues must be considered when designing a Time Warp simulation; examples are reducing the state saving overhead and designing the global control mechanism (i. e., global virtual time computation, memory management, distributed termination, and fault tolerance). This paper addresses these issues. We propose a heuristic to select the checkpoint interval to reduce the state saving overhead, generalize a previously proposed global virtual time computation algorithm, and present new algorithms for memory management, distributed termination, and fault tolerance. The main contribution of this paper is to provide guidelines for designing an efficient Time Warp simulation.

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Available abstract

Simulation is a powerful tool for studying the dynamics of a system. However, simulation is time-consuming. Thus, it is natural to attempt to use multiple processors to speed up the simulation process. Many protocols have been proposed to perform discrete event simulation in multi-processor environments. Most of these distributed discrete event simulation protocols are either conservative or optimistic. The most common optimistic distributed simulation protocol is called Time Warp. Several issues must be considered when designing a Time Warp simulation; examples are reducing the state saving overhead and designing the global control mechanism (i. e., global virtual time computation, memory management, distributed termination, and fault tolerance). This paper addresses these issues. We propose a heuristic to select the checkpoint interval to reduce the state saving overhead, generalize a previously proposed global virtual time computation algorithm, and present new algorithms for memory management, distributed termination, and fault tolerance. The main contribution of this paper is to provide guidelines for designing an efficient Time Warp simulation.

Key concepts: Computer science, Discrete event simulation, Distributed computing, Event (particle physics), Real-time computing, Simulation, Quantum mechanics, Physics

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