Alignment Properties in Ordinal Comparison of Discrete Event Dynamic Systems

In the design and optimization of discrete event dynamic systems, it is often necessary to order alternative designs based on their relative performance, i.e., to rank them from best to worst. In this paper, alignment of observed performance orders with true orders is considered and properties of the alignment are investigated. Spearman's rank correlation coefficient is a measure of agreement between the observed performance orders and the true ones. It is shown that Spearman's coefficient converges exponentially in the simulation time or observation time, which gives a strong evidence of the efficiency of order comparison for discrete event dynamic systems. In the context of simulation, the effect of simulation dependence on the alignment is also discussed. It is found that neither independent simulation nor the scheme of common random numbers (CRN), a popular scheme for variance reduction, can yield dominant performance. Finally, numerical examples based on a networking optimization problem are provided to illustrate the convergence of Spearman's coefficient. In these examples, the standard clock (SC) simulation technique provides much faster convergence than either independent simulations or CRN simulations. Both the SC and CRN methods use the same random number sequence to drive many events in parallel; however, under SC the events driving the parallel experiments are all identical, whereas under CRN they may be different.     

保守PDES中时间管理问题研究

并行离散事件仿真是一种非常有用的分析求解大规模复杂问题的工具,近年来成为仿真界研究热点之一.而并行仿真算法则是并行离散事件仿真中的核心问题,对于具体的应用系统,采用不同的并行仿真算法将导致其仿真性能大的差异.从保守PDES的基础出发,阐述其在时间管理中所遇到的问题,并进行分析和解决,然后给出一种简单的保守PDES系统结构.     

基于事件图的离散事件仿真模型并行检验方法

非形式化仿真模型验证方法易受主观因素的影响且具有不完备性,而传统的形式化模型检验方法由于受到状态空间爆炸问题的影响,很难处理大规模的仿真模型.并行模型检验方法以其完备性、高效性已经在工业界中得到了成功的应用,但是由于涉及到形式化规约、逻辑学以及并行计算等多项技术,应用难度较大.针对上述问题,提出了基于事件图的离散事件仿真模型并行检验方法.该方法首先对事件图在模型同步方面进行了扩展,给出了扩展事件图的形式化定义、语法及语义;然后将扩展事件图模型转换到分布并行验证环境的DVE模型,成功地将并行模型检验方法应用于仿真模型验证领域.该方法使得仿真人员无须学习新的形式化验证语言就能采用并行模型检验方法对仿真模型进行形式化验证,可降低模型并行验证的难度,从而有效提高模型验证的效率和完备性.实验结果表明了该方法的有效性,有利于扩展并行模型检验方法在仿真领域中的应用.     

Extending the DEVS formalism for massively parallel simulation

The use of multiprocessors for discrete event simulation is an active research area where work has focused on strategies for model execution with little regard for the underlying formalism in which models may be expressed. However, a formalism-based approach offers several advantages including the ability to migrate models from sequential to parallel platforms and the ability to calibrate simulation architectures to model structural properties. In this article, we extend the DEVS (discrete event system specification) formalism, originally developed for sequential simulation, to accommodate the full potential of parallel processing. The extension facilitates exploitation of both internal and external event parallelism manifested in hierarchical, modular DEVS models. After developing a mapping of the extended formalism to parallel architectures, we describe an implementation of the approach on a massively parallel architecture, the Connection Machine. Execution results are discussed for a class of models exhibiting high external and internal event parallelism, the so-called broadcast models. These verify the tenets of the underlying theory and demonstrate that significant reduction in execution time is possible compared to the same model executed in serial simulation.     

改进粗粒度并行遗传算法在网格任务调度中的应用

现有并行遗传算法采用随机方法划分子种群,算法收敛性能不高,并且不可避免的破坏种群的较优模式;为了改进这些缺陷,设计了一种新的多点交叉算子,提出了一种改进的粗粒度并行遗传算法;取资源数为6,任务数为50,种群的规模为60,遗传代数为600;采用相同的控制参数进行仿真实验;仿真实验表明,与传统并行遗传算法相比较,提出的改进算法在收敛速度和寻优空间方面有很大的提升。     

时间偏差算法中通讯接口的研究及实现

时间偏差算法是一种实现并行离散事件模拟的协议,其目的在于利用并行平台并发地执行大规模离散事件的模拟,以缩短仿真时间。为保证结果的正确性,并行模拟必须解决同步问题。时间偏差算法利用虚拟时间来同步各模拟部分之间的执行,通讯接口是利用虚拟时间及回退策略实现同步的部分。对该部分进行了深入的研究,提出了一种优化的实现方案,并对其性能进行了分析。     

Asynchronous self-organizing maps

A recently defined energy function which leads to a self-organizing map is used as a foundation for an asynchronous neural-network algorithm. We generalize the existing stochastic gradient approach to an asynchronous parallel stochastic gradient method for generating a topological map on a distributed computer system (MIMD). A convergence proof is presented and simulation results on a set of problems are included. A practical problem using the energy function approach is that a summation over the entire network is required during the computation of updates. Using simulations we demonstrate effective algorithms that use efficient sampling for the approximation of these sums.     

Performance analysis of optimistic parallel simulations with limited rolled back events

Using the parallel simulation approach is not always the best choice. There are situations in which the sequential approach works better, in terms of simulation effectiveness.Indeed, the optimistic parallel simulation time consists of two basic components: the forward execution time, and the rollback mechanism time-overhead. It is convenient to parallelize a simulation until the latter component is not predominant with respect to the former one.The breakeven point depends on the nature of the model to simulate, on the characteristics of the simulation platform, and on the choice of tuning parameters such as the number of processors and the checkpoint interval.This paper deals with an evaluation of the performances of the sequential and parallel approach, in case the optimistic parallel method is used. An analytical model is introduced to study the sensitivity of the parallel simulation effectiveness to the forward event time, in case each event is rolled back no more than once.The model is first experimentally validated and then used to determine the breakeven point between the parallel and sequential approach.     

Parallel simulation of DEDS via event synchronization

In this paper we use the event synchronization scheme to develop a new method for parallel simulation of many discrete event dynamic systems simultaneously. Though a few parallel simulation methods have been developed during the last several years, such as the well-known Standard Clock method, most of them are largely limited to Markovian systems. The main advantage of our method is its applicability to non-Markovian systems. For Markovian systems a comparison study on efficiency between our method and the Standard Clock method is done on Connection Machine CM-5. CM-5 is a parallel machine with both SIMD (Single Instruction, Multiple Data) and MIMD (Multiple Instruction Multiple Data) architectures. The simulation results show that if event rates of Markovian systems do not differ by much then both methods are compatible but the Standard Clock method performs better in most cases. For Markovian systems with very different event rates, our method often yields better results. Most importantly, our simulation results also show that our method works as efficiently for non-Markovian systems as for Markovian systems.     

Nonblocking checkpointing for optimistic parallel simulation: description and an implementation

Describes a nonblocking checkpointing mode in support of optimistic parallel discrete event simulation. This mode allows real concurrency in the execution of state saving and other simulation specific operations (e.g, event list update, event execution) with the aim of removing the cost of recording state information from the completion time of the parallel simulation application. We present an implementation of a C library supporting nonblocking checkpointing on a myrinet based cluster, which demonstrates the practical viability of this checkpointing mode on standard off-the-shelf hardware. By the results of an empirical study on classical parameterized synthetic benchmarks, we show that, except for the case of minimal state granularity applications, nonblocking checkpointing allows improvement of the speed of the parallel execution, as compared to commonly adopted, optimized checkpointing methods based on the classical blocking mode. A performance study for the case of a personal communication system (PCS) simulation is additionally reported to point out the benefits from nonblocking checkpointing for a real world application.     

Convergent results about the use of fuzzy simulation in fuzzy optimization problems

We discuss the convergence of fuzzy simulation as it is employed in fuzzy optimization problems. Several convergence concepts for sequences of fuzzy variables are defined such as convergence in optimistic value. A new approach to approximating essentially bounded fuzzy variables with continuous possibility distributions is introduced. Applying the proposed approximation method to our previous work, we prove three convergence theorems about the use of fuzzy simulation in computing the credibility of a fuzzy event, finding the optimistic value of a return function, and calculating the expected value of a fuzzy variable.     

国民经济动员仿真演练混合仿真策略研究

国民经济动员仿真演练是一个复杂的基于HLA的分布式离散事件仿真过程,包括人在回路与无人在回路的混合仿真环节,且一次演练中参演单位数量非常多,需要解决高效的实时与超实时混合仿真控制问题.在分析仿真演练特点的基础上,将并行离散事件仿真(PDES)技术应用于联邦成员仿真控制过程,提出联邦成员离散事件仿真与成员内部PDES混合仿真策略.在分析时间推进过程的基础上,设计全局仿真时间控制机制.混合仿真策略可以支持实时与超实时混合仿真模式,并能充分地提高仿真并行能力,而全局时间控制则保证了系统时间的有效推进.     

并行离散事件模拟系统容错功能设计

基于时间偏差的并行离散事件模拟是提高模拟速度的有效手段,其通用系统实现结构是分布式逻辑进程模拟结构。提出了在并行离散事件模拟系统中实现容错功能的基本框架,并针对系统本身特点对容错框架各个方面的实现方案给予描述。     

基于乐观策略的并行离散事件模拟研究

并行离散事件模拟（PDES）又称分布式模拟,通过将一个离散事件模拟程序在多个处理器上并行执行来提高模拟性能。乐观策略在解决并行模拟中各模拟部分之间的同步关系时具有较好的性能。介绍了基于乐观策略的并行离散事件模拟的原理,讨论了存在的问题,并给出相应的解决方法。     

并行仿真多样本任务分发与调度工具的设计

并行离散事件仿真具有更高的运行效率,已在分析仿真领域得到了广泛的关注.分析仿真往往要对多组参数组合进行比较,要求仿真应用运行多次才能得到所需的结果数据.针对目前并行仿真应用进行多样本多次运行时需要进行大量手工配置、仿真运行效率低下这一问题,论文在对并行仿真应用多次连续运行控制技术进行深入研究的基础上,提出了一种多样本任务分发与调度框架,并设计了多样本任务分发与调度工具.该工具能够将样本运行信息自动部署到局域网内多个节点上,并调度各节点上的样本并行运行.应用表明工具减少了仿真试验人员仿真运行配置工作量,大大缩短了仿真任务运行所需时间.     

多重网格格子Boltzmann方法的并行算法

针对复杂流动数值模拟中的格子Boltzmann方法存在计算网格量大、收敛速度慢的缺点,提出了基于三维几何边界的多重笛卡儿网格并行生成算法,并基于该网格生成方法提出了多重网格并行格子Boltzmann方法（LBM）。该方法结合不同尺度网格间的耦合计算,有效减少了计算网格量,提高了收敛速度;而且测试结果也表明该并行算法具有良好的可扩展性。     

Trade-off between sequential and time warp-based parallelsimulation

Discrete event simulation is a methodology to study the behavior of complex systems. Its drawback is that, in order to get reliable results, simulations usually have to be run over a long stretch of time. This time requirement could decrease through the usage of parallel or distributed computing systems. In this paper, we analyze the Time Warp synchronization protocol for parallel discrete event simulation and present an analytical model evaluating the upper bound on the completion time of a Time Warp simulation. In our analysis, we consider the case of a simulation model with homogeneous logical processes, where “homogeneous” means they have the same average event routine time and the same state saving cost. Then we propose a methodology to determine when it is time-convenient to use a Time Warp synchronized simulation, instead of a sequential one, for a simulation model with features matching those considered in our analysis. We give an answer to this question without the need to preliminary generate the simulation code. Examples of methodology usage are reported for the case of both a synthetic benchmark and a real world model     

基于时间偏差的并行逻辑模拟的动态负载平衡

随着大规模集成电路的复杂性日益增加,逻辑模拟开始采用并行离散事件模拟技术。在现有的基于时间偏差协议的并行逻辑模拟系统的基础上,提出了一个动态负载平衡模型,模型能够针对模拟时的负载变化,进行以一组模拟对象为单位的迁移以实现负载平衡。提出模拟推进度的概念,作为对并行逻辑模拟过程中的负载进行准确的衡量标准。     

基于消息的离散事件仿真方法

本文提出了一种基于沙息的离散事件仿真方法,它将面向对象的程序设计方法,分布式仿真和并行算法的概念结合在一起,与传统的离散事件仿真方法相比,是一种更加灵活而直观的模型仿真方法。     

自适应惯性权重的分组并行粒子群优化算法

针对岛屿模型的并行粒子群算法没有根本改变粒子速度更新的问题,提出一种自适应惯性权重的分组并行粒子群优化算法。该算法在迭代过程中能自适应地选择加入分组的数量,同时对各组粒子的惯性权重按照组内最优位置的变化进行自适应调整。各组运用多线程技术并行处理,粒子间采用新的信息共享的方式。仿真结果证实,该算法具有较高的收敛速度和收敛精度。