并行处理任务级仿真环境的研究及实现

并行处理仿真为并行系统的建模分析，并行算法的模拟执行以及并行环境的性能评价提供支持，本文利用任务相关仿真时钟和重叠时间片建立了一种支持完全并和用户并发方式的并行多任务模型，并结合对不同调度算法和互连结构的仿真实验，着重分析了任务调度对系统性能的影响以及互连网络技术与通信开销的关系。同时，仿真环境还提供模拟执行的并发度曲线和任务执行踪迹供和户分析调试并行程序。     

多机仿真系统研究

多机仿真系统研究孙华樵，陈波本文从多机系统的结构、并行算法和仿真程序的组次通信织等方面，阐述了如何对控制系统进行数字仿真问题。一、多机仿真系统的结构该多机系统建议设计在一块印制板上，有一台主机和三台从机，分别有本地内存，可独立工作，如图一所Ｒ。图一多...     

可扩展传感器网络模拟器SensorSSF及性能预测

仿真模型越来越复杂，受单机计算能力和存储容量的限制，模拟需要花费的时间也越来越长。PDES（Parallel Discrete Event Simulation）策略能够加快仿真程序的执行，因此一度成为研究热点。但是，并行仿真最终并没有在工业界得到广泛应用，其原因在于：并行仿真建模理论缺乏，并行仿真性能具有不可预测性，以及并行程序行为的不可预测性。本文在讨论模拟器并行化的一般方法基础上，给出了一个基于SSF的传感器网络并行仿真环境SensorSSF。SensorSSF设计遵循：可扩展性和简洁性。可扩展性保证CPU执行时间随求解问题的规模和仿真模型的复杂度线性增长；简洁性使得仿真应用人员无需了解太多并行程序设计知识，就可以编写出高效的仿真程序。实验结果表明，SensorSSF具有良好的可扩展性，同NS2相比具有较好的时间特性。     

集成化企业模型并行仿真系统中的仿真时钟

深入探讨了集成化企业模型并行仿真系统中的仿真时钟管理机制，解决了多个子过程共同使用一个独占型资源时的时钟同步问题和多事件仿真中活动数量限制造成的时钟同步问题以及多个线程之间的时钟同步问题。     

基于知识的数据自动分布模型

基于松散耦合的多自理机系统的发展，要求有相应的并行软件工具的支持，而在上前的大多并行软件系统中，用户必须显式给出顺序执行程序的划分方法以及在ＤＫＳＭ中不同处理器上的分配算法。针对这一问题，本首先介绍了一种基于知识的数据自动分布模型，以期对程序的划分和分布问题提供自动的支持然后讨论了ＫＢＤＭ设计的主要思想，并给出了该模型主要部件的详细描述。     

一个面向仿真程序的任务聚类算法

对仿真程序原始任务图的聚类运算是实现仿真程序并行化的关键。在研制面向仿真程序自动并行化系统AFPS的过程中,提出了一个基于状态变量一阶微分的并行任务聚类算法。使用结果表明,该算法可以最大限度地保证各处理机结点的负载均衡,减少通信次数,且易于实现通信变量的自动确定。     

面向对象的离散事件仿真建模与实现

该文论述了面向对象方法在离散事件仿真中的应用，提出了一种建模与开发仿真程序的新方法，其特点是易于在单进程操作系统、普通编程平台上实现对并发事件的准确描述和仿真执行。     

并行仿真任务的自动生成软件

本文阐述了一种将连续系统仿真模型－状态方程模型自动生成并行仿真多任务的软件。该软件实现了从仿真模型生成可并行多任务到仿真结果输出过程的自动化，而且生成的并行仿真任务均衡，并行加速比高，适用于基于机间通信的同构型ＭＩＭＤ系统。     

离散事件系统并发仿真环境

本文提出了并发仿真思想。并介绍了针对柔性制造系统仿真研制的离散事件系统并发仿真环境:将制造系统作为仿真对象部分,将控制、调度等管理方法作为决策部分,仿真对象部分和决策部分作为两个独立的作业并发执行,它们交互作用完成整个仿真过程。介绍了一个将上述两部分连接成一个完整仿真系统的接口(软件)。     

Transputer多机系统通信服务程序的研究

在Transputer多机系统中,由于各处理机通信链路数目的限制,系统可能无法按照任务的各并行进程之间的通信关系连接成对应的拓扑结构,使一些应用程序无法进行系统构形(configuration)。为此,本文将研究一个Transputer多机系统通信服务程序,作为任务的各并行进程之间的通信框架。在这运行环境下,程序员可以直接按照问题设计并行处理程序,然后根据程序的并行结构选择最佳的系统拓扑结构。     

基于Petri网结构的多处理机实时操作系统

多处理机环境下的实时系统具有并发事件驱动性质,其软件结构展现了多重同步点以及生产者与消费者之间的关系,这导致了复杂的控制结构.对于此类系统软件的开发缺少标准的方法和工具,造成了软件低效、程序结构不清晰、开发成本高、维护困难的现象的出现.根据Petri网易于描述并行/并发现象的特点,采用它来解决多处理机软件的描述问题,介绍了一种以Petri网图形方式在多处理机系统环境下进行程序设计的方法.该方法基于两种程序设计级别:任务级和作业级.前者负责描述基本操作,由单一控制线程完成;后者用于并行/并发程序建模,由整个多处理机系统来执行.在作业级程序设计中,用户采用面向对象Petri网来描述并行程序结构,以建立系统模型.该方法以一种接近于程序员的思维方式去设计并发软件,提供了一种可靠的并行结构的程序.阐述了支持此种程序设计方法的操作系统结构及其实现原理.     

Dynamic partitioning of multiprocessor systems

Partitioning of processors on a multiprocessor system involves logically dividing the system into processor partitions. Programs can be executed in the different partitions in parallel. Optimally setting the partition size can significantly improve the throughput of multiprocessor systems. The speedup characteristics of parallel programs can be defined by execution signatures. The execution signature of a parallel program on a multiprocessor system is the rate at which the program executes in the absence of other programs and depends upon the number of allocated processors, the specific architecture, and the specific program implementation. Based on the execution signatures, this paper analyzes simple Markovian models of dynamic partitioning. From the analysis, when there are at most two multiprocessor partitions, the optimal dynamic partition size can be found which maximizes throughput. Compared against other partitioning schemes, the dynamic partitioning scheme is shown to be the best in terms of throughput when thereconfiguration overhead is low. If the reconfiguration overhead is high, dynamic partitioning is to be avoided. An expression for the reconfiguration overhead threshold is derived. A general iterative partitioning technique is presented. It is shown that the technique gives maximum throughput forn partions.     

A comparison of multiprocessor task scheduling algorithms with communication costs

Both parallel and distributed network environment systems play a vital role in the improvement of high performance computing. Of primary concern when analyzing these systems is multiprocessor task scheduling. Therefore, this paper addresses the challenge of multiprocessor task scheduling parallel programs, represented as directed acyclic task graph (DAG), for execution on multiprocessors with communication costs. Moreover, we investigate an alternative paradigm, where genetic algorithms (GAs) have recently received much attention, which is a class of robust stochastic search algorithms for various combinatorial optimization problems. We design the new encoding mechanism with a multi-functional chromosome that uses the priority representation—the so-called priority-based multi-chromosome (PMC). PMC can efficiently represent a task schedule and assign tasks to processors. The proposed priority-based GA has show effective performance in various parallel environments for scheduling methods.     

Towards a portable and efficient environment for parallel computing

The availability of more and more cost-effective and powerful parallel computers has enhanced the ability of the operations research community to solve more laborious computational problems. In this paper an attempt has been made to implement a parallel simulation runs dispatcher with an objective to study the feasibility of establishing a portable and efficient parallel programming environment. This parallel simulation run dispatcher can be applied to both terminating type and steady-state type simulation models. The algorithm is then transferred and executed on various other shared-memory multiprocessor systems to illustrate its portability. Another contribution of this paper is to verify whether the performance of the portable code and the non-portable code of a same algorithm is significantly different on a specific parallel system using the analysis of covariance model.     

A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture

Parallel processing is one approach to achieving the large computational processing capabilities required by many real-time computing tasks. One of the problems that must be addressed in the use of reconfigurable multiprocessor systems is matching the architecture configuration to the algorithms to be executed. This paper presents a conceptual model that explores the potential of artificial intelligence tools, specifically expert systems, to design an Intelligent Operating System for multiprocessor systems. The target task is the implementation of image understanding systems on multiprocessor architectures. PASM is used as an example multiprocessor. The Intelligent Operating System concepts developed here could also be used to address other problems requiring real-time processing. An example image understanding task is presented to illustrate the concept of intelligent scheduling by the Intelligent Operating System. Also considered is the use of the conceptual model when developing an image understanding system in order to test different strategies for choosing algorithms, imposing execution order constraints, and integrating results from various algorithms.     

Asynchronous parallel simulation of parallel programs

Parallel simulation of parallel programs for large datasets has been shown to offer significant reduction in the execution time of many discrete event models. The paper describes the design and implementation of MPI-SIM, a library for the execution driven parallel simulation of task and data parallel programs. MPI-SIM can be used to predict the performance of existing programs written using MPI for message passing, or written in UC, a data parallel language, compiled to use message passing. The simulation models can be executed sequentially or in parallel. Parallel execution of the models are synchronized using a set of asynchronous conservative protocols. The paper demonstrates how protocol performance is improved by the use of application-level, runtime analysis. The analysis targets the communication patterns of the application. We show the application-level analysis for message passing and data parallel languages. We present the validation and performance results for the simulator for a set of applications that include the NAS Parallel Benchmark suite. The application-level optimization described in the paper yielded significant performance improvements in the simulation of parallel programs, and in some cases completely eliminated the synchronizations in the parallel execution of the simulation model     

A genetic algorithm for multiprocessor scheduling

The problem of multiprocessor scheduling can be stated as finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimized. This scheduling problem is known to be NP-hard, and methods based on heuristic search have been proposed to obtain optimal and suboptimal solutions. Genetic algorithms have recently received much attention as a class of robust stochastic search algorithms for various optimization problems. In this paper, an efficient method based on genetic algorithms is developed to solve the multiprocessor scheduling problem. The representation of the search node is based on the order of the tasks being executed in each individual processor. The genetic operator proposed is based on the precedence relations between the tasks in the task graph. Simulation results comparing the proposed genetic algorithm, the list scheduling algorithm, and the optimal schedule using random task graphs, and a robot inverse dynamics computational task graph are presented     

Simulation of hierarchical multiprocessor database systems

The paper is dedicated to issues concerning simulation and analysis of hierarchical multiprocessor systems oriented to database applications. Requirements for a parallel database system model are given. A survey and comparative analysis of known parallel database system models are presented. A new multiprocessor database system model is introduced. This model allows us to simulate and evaluate arbitrary hierarchical multiprocessor configurations in the context of the OLTP class database applications. Examples of using the database multiprocessor model for simulation study of multiprocessor database systems are presented.