基于PVM的启发式搜索的并行计算模型设计

通过分析人工智能中的A和A^*启发式搜索,提出了通过PVM工具包,设计和实现A和A^*启发式搜索的并行计算模型。在启发搜索过程中同时进行评估函数计算,使计算的速度加快。解决了在搜索解空间庞大,评估函数计算复杂的情况下,使用单计算机计算速度慢的问题。该文实现了基于PVM的启发式搜索过程,该模型可应用于一般性启发式搜索问题的并行计算模型。     

Parallel,iterative solution of sparse linear systems: Models and architectures

Solving large, sparse, linear systems of equations is a fundamental problems in large scale scientific and engineering computation. A model of a general class of asynchronous, iterative solution methods for linear systems is developed. In the model, the system is solved by creating several cooperating tasks that each compute a portion of the solution vector. A data transfer model predicting both the probability that data must be transferred between two tasks and the amount of data to be transferred is presented. This model is used to derive an execution time model for predicting parallel execution time and an optimal number of tasks given the dimension and sparsity of the coefficient matrix and the costs of computation, synchronization, and communication.The suitability of different parallel architectures for solving randomly sparse linear systems is discussed. Based on the complexity of task scheduling, one parallel architecture, based on a broadcast bus, is presented and analyzed.     

两维时间域上的实时程序语义

超稠密计算模型是实时系统的一种重要抽象模型．该文首先简要介绍一种两维的超稠密时间域及在该域上定义的一种区间逻辑,然后用一个并行模型语言（类Ｏｃｃａｍ 语言）讨论用这种逻辑定义并行语言（在超稠密模型中）的时间语义的问题,最后讨论了在这种语义框架中实时系统性质的描述     

一种基于移动Agent的分布式并行计算模型

针对传统的分布式并行计算方案所存在的缺点,提出了一种基于移动Agent技术的分布式并行计算模型。在简单介绍移动Agent技术后,给出了基于移动Agent的分布式并行计算模型,并详细叙述了该模型的具体工作过程和实现方案。模型设计完成后,用此模型来解决计算量很大的数值计算问题。首先利用数学工具分析设计出该问题的适合于分布式并行计算的方案,然后依照模型实现实验程序。实验测试表明根据该模型实现的分布式并行计算程序具有较高的加速比和并行效率,并有效地提高了分布式并行计算的稳定性、灵活性、可扩展性和移动性。     

Time-Efficient Parallel Algorithms for the Longest Common Subsequence and Related Problems

Recently Aklet al. introduced a new model of parallel computation, called broadcasting with selective reduction (BSR), and showed that it is more powerful than any CRCW PRAM and yet requires no more resources for implementation than even EREW PRAM. The model allows constant time solutions to sorting, parallel prefix, and other problems. In this paper, we describe constant time solutions to the longest common subsequence problem and the sequence alignment problem using the BSR model. These are the first constant time solutions to these problems for any model of computation.     

一种异步BSP模型及其程序优化技术

基于BSP模型，该文提出了异步计算模型（CSA－BSP）。该模型更准确地描述了并行机的性能参数，引导用户编写高效率的并行程序，在CSA－BSP模型下，两个进程异步执行的位置至多相差p-1个超步；基于程序的执行时间，作者分析了BSP、A－BSP和CSA－BSP程序的效率，得出CSA－BSP程序的效率是最高的，在曙光并行机上，用“红黑格法”和“矩阵乘法”进行了验证，和BSP模型相比，这两个CSA－BSP程序的效率分别提高20％和37％；同时，其进程执行时间和最大可以降低8％，因此，按照CSA－BSP模型编程对于提高程序效率和改善系统的吞吐率，都有良好的效果。     

Models of computation for reactive control of autonomous mobile robots

The paper studies computation models for tasks performed by autonomous mobile robots. Such tasks can be accomplished by reactive control algorithms. Reactive control systems can be described using different models of computation which have as distinguishing feature the abstraction level of time. Thus, three computation models are defined: the untimed model, the synchronous model and the timed model. It is shown that the clocked-synchronous model of computation is more appropriate for describing the controller for a parallel parking task.     

SPEED: A parallel platform for solving and predicting the performance of PDEs on distributed systems

Distributed systems such as networks of workstations are becoming an increasingly viable alternative to traditional supercomputer systems for running complex scientific applications. A large number of these applications require solving sets of partial differential equations (PDEs). In this paper, we describe the implementation and performance of SPEED (Scalable Partial differential Equation Environment on Distributed systems), a parallel platform which provides an efficient solution for time-dependent PDEs. SPEED allows the inclusion of a wide range of parameters and programming aids. PVM is employed as the underlying message-passing system. The parallel implementation has been performed using two algorithms. The first algorithm is a two-phase scheme which uses the conventional technique of alternating phases of computation and communication. The second algorithm employs a pre-computation technique that allows overlapping of computation and communication. Both methods yield significant speedups. The pre-computation technique reduces the communication time between the workstations but incurs additional overhead in buffer management. Hence, if the saving in communication time is larger than the overhead, the pre-computation technique outperforms the two-phase algorithm. SPEED also provides a performance prediction methodology that can accurately predict the performance of a given application on the system before running the application. This methodology allows the user to tune various parameters in order to identify system bottlenecks and maximize the performance.     

命令式语言的化学语义

化学计算模型是基于化学反应和计算之间比喻的并行计算模型,其内在的并行性及不确定性可以有效的消除与计算逻辑本身无关的人为顺序性,但是难于描述特定的控制机制.高阶化学编程语言是对传统化学计算模型的扩展和泛化,可以描述传统的控制机制和定义新的控制机制.通过从简单命令式语言到高阶化学语言的转换,给出了命令式语言的一种化学语义描述,为结合命令式编程和化学编程提供了一种可能.     

一种更有效的并行系统可扩展性模型

文中首先分析了等效率、等速度和等并行开销计算比三种并行系统可扩展性模型的特点,论证了等效率、等速度和等并行开销计算比三种条件的等价性,并指出这三种模型在描描可扩展性时的不直观及其局限性。然后提出了一种新的可扩展性模型。此模型直观地反映出并行系统在机器规模和问题规模扩展时,其性能的扩展特性。实例研究表明,该模型能更有效地解决下列问题：（1）定量研究并行系统的可扩展性;（2）全面地反映程序、机器、环境方面的因素对可扩展性的影响;（3）指导如何保持并行系统的可扩展性。     

An Optimal Parallel Co-Connectivity Algorithm

In this paper we consider the problem of computing the connected components of the complement of a given graph. We describe a simple sequential algorithm for this problem, which works on the input graph and not on its complement, and which for a graph on n vertices and m edges runs in optimal O(n+m) time. Moreover, unlike previous linear co-connectivity algorithms, this algorithm admits efficient parallelization, leading to an optimal O(log n)-time and O((n+m)log n)-processor algorithm on the EREW PRAM model of computation. It is worth noting that, for the related problem of computing the connected components of a graph, no optimal deterministic parallel algorithm is currently available. The co-connectivity algorithms find applications in a number of problems. In fact, we also include a parallel recognition algorithm for weakly triangulated graphs, which takes advantage of the parallel co-connectivity algorithm and achieves an O(log² n) time complexity using O((n+m²) log n) processors on the EREW PRAM model of computation.     

An optimal algorithm for global termination detection inshared-memory asynchronous multiprocessor systems

In the literature, the problem of global termination detection in parallel systems is usually solved by message passing. In shared-memory systems, this problem can also be solved by using exclusively accessible variables with locking mechanisms. In this paper, we present an algorithm that solves the problem of global termination detection in shared-memory asynchronous multiprocessor systems without using locking. We assume a reasonable computation model in which concurrent reading does not require locking and concurrent writing different values without locking results in an arbitrary one of the values being actually written. For a system of n processors, the algorithm allocates a working space of 2n+1 bits. The worst case time complexity of the algorithm is n+2√+1, which we prove is the lower bound under a reasonable model of computation     

Algorithmic techniques for computer vision on a fine-grainedparallel machine

The authors describe several fundamentally useful primitive operations and routines and illustrate their usefulness in a wide range of familiar version processes. These operations are described in terms of a vector machine model of parallel computation. They use a parallel vector model because vector models can be mapped onto a wide range of architectures. They also describe implementing these primitives on a particular fine-grained machine, the connection machine. It is found that these primitives are applicable in a variety of vision tasks. Grid permutations are useful in many early vision algorithms, such as Gaussian convolution, edge detection, motion, and stereo computation. Scan primitives facilitate simple, efficient solutions of many problems in middle- and high-level vision. Pointer jumping, using permutation operations, permits construction of extended image structures in logarithmic time. Methods such as outer products, which rely on a variety of primitives, play an important role of many high-level algorithms     

广义可能性决策过程的计算树逻辑模型检测

模型检测作为一种形式化验证技术,已被广泛应用于各种并发系统的正确性验证。针对具有非确定性选择和广义可能性分布的并发系统,引入广义可能性决策过程作为此类系统的模型;给出描述其性质的规范语言广义可能性计算树逻辑的概念;研究此类系统的广义可能性计算树逻辑模型检测问题。结论表明,其模型检测算法的时间复杂度也为多项式时间。所获得的结果扩大了广义可能性测度在模型检测中的应用范围。     

Parallel search using transformation-ordering Lterative-Deepening-A*

Iterative-Deepening-A (IDA*) is an optimal search technique which is useful for large search spaces, because it requires no intermediate state storage. We show how Transformation-Ordering Iterative-Deepening-A* (TOIDA*) improves the performance of IDA* by dynamically modifying the node expansion order based on results from previous cost limits. We then describe a window parallel implementation of TOIDA* on a Hypercube, and present empirical evidence that the parallel implementation dramatically reduces time spent in search. Finally, we analyze the best and worst case results of sequential and parallel TOIDA*, and compare the results with those of standard IDA* search. Empirical and analytical results show that TOIDA* can provide significant improvements in search speed over IDA* with no penalty in storage requirements, and parallel TOIDA* offers substantial cost reduction over sequential TOIDA*, though at the cost of optimality. © 1993 John Wiley & Sons, Inc.     

A parallel sorting algorithm for a novel model of computation

The computational complexity of a parallel algorithm depends critically on the model of computation. We describe a simple and elegant rule-based model of computation in which processors apply rules asynchronously to pairs of objects from a global object space. Application of a rule to a pair of objects results in the creation of a new object if the objects satisfy the guard of the rule. The model can be efficiently implemented as a novel MIMD array processor architecture, the Intersecting Broadcast Machine. For this model of computation, we describe an efficient parallel sorting algorithm based on mergesort. The computational complexity of the sorting algorithm isO(nlog² n), comparable to that for specialized sorting networks and an improvement on theO(n ^1.5) complexity of conventional mesh-connected array processors.     

The design of an operating system for a scalable parallel computing engine

There are substantial benefits to be gained from building computing systems from a number of processors working in parallel. One of the frequently-stated advantages of parallel and distributed systems is that they may be scaled to the needs of the user. This paper discusses some of the problems associated with designing a general-purpose operating system for a scalable parallel computing engine and then describes the solutions adopted in our experimental parallel operating system. We explain why a parallel computing engine composed of a collection of processors communicating through point-to-point links provides a suitable vehicle in which to realize the advantages of scaling. We then introduce a parallel-processing abstraction which can be used as the basis of an operating system for such a computing engine. We consider how this abstraction can be implemented and retain the ability to scale. As a concrete example of the ideas presented here we describe our own experimental scalable parallel operating-system project, concentrating on the Wisdom nucleus and the Sage file system. Finally, after introducing related work, we describe some of the lessons learnt from our own project.     

Constant time BSR solutions to parenthesis matching, tree decoding,and tree reconstruction from its traversals

Recently Akl et al. introduced a new model of parallel computation, called BSR (broadcasting with selective reduction) and showed that it is more powerful than any CRCW PRAM and yet requires no more resources for implementation than even EREW PRAM. The model allows constant time solutions to sorting, parallel prefix and other problems. In this paper, we describe constant time solutions to the parenthesis matching, decoding binary trees in bitstring representation, generating next tree shape in B-order, and the reconstruction of binary trees from their traversals, using the BSR model. They are the first constant time solutions to mentioned problems on any model of computation. The number of processors used is equal to the input size, for each problem. A new algorithm for sorting integers is also presented     

基于面向服务对象体系结构的交通噪声地图分布式计算方法

针对目前城市交通噪声地图绘制工具和方法不能适应大规模项目分布式计算需要的现状,提出一种基于松耦合服务的噪声地图分布式计算方法,阐述了面向服务对象体系结构(SOOA)运作机制,给出了噪声地图计算服务的建立方法并介绍了其部署方式和管理模式。最后通过某示范区噪声地图求解实例验证了该算法在有效提高计算效率的同时能够给系统提供充分的灵活性。实验结果表明,并行子任务的不均衡会影响并行效率,一般状况下并行效率能够达到85%以上。