一种支持分布式进程迁移的动态负载平衡征募算法的研究

负载平衡是分布式系统必须考虑的问题,本文介绍的征募算法独立于网络拓扑结构,其思想可以应用到分布式系统中,征募算法的设计思想向传统负载平衡算法提出了挑战,它不但克服了投标算法的缺点,而且在减小通讯开销和提高处理机利用率两方面作了很多努力,使其成为一种高效的分布式进程迁移和动态负载平衡策略。我们在分布式ＵＮＩＸ系统上实现并验证了征募算法的高效性。     

一个有效的动态负载平衡方法

动态负载平衡问题是影响工作站网络并行计算性能的重要因素.首先分析出在负载平衡中产生额外开销的根本原因是负载的移动,进而定性地给出了每次移动负载的粒度公式.引入益处估计的方法,仅在有益的情况下进行负载平衡.另外还提出了一个动态负载平衡算法.最后,通过实验,将该算法的运行结果与其他人的负载平衡结果以及不作负载平衡的情况进行了对比.此负载平衡方法在工作站为空载以及不同的负载和应用问题的数据规模的情况下,都优于Siegell等人提出的方法.     

分布式容错系统的任务分配算法

文章提出了分布式容错系统的任务分配算法,该算法考虑了系统任务的周期性、冗余性特点,以处理机负载平衡为目标,通过三步静态分配实现了任务在处理机中的冗余分布,在系统执行过程中的处理机故障,通过冗余任务动态唤醒实现系统重构。     

异构系统中负载平衡扩散算法的加速方法

目前,很多单位与组织都有连接着数百台工作站和微机的局域网,并将它们作为一个机群系统使用.在这样的异构系统上动态负载平衡是提高性能的一个重要方法.扩散方法是同构系统的动态负载平衡算法.将散算法扩展到异构系统中,对异构系统中速度不同的处理机的位置与扩散收敛速度的关系进行了研究,提出了加速扩散算法的收敛速度的优化方法.初步实验证明,该方法能通过合理安排处理机,加快扩散算法的速度.     

动态负载调度算法在分布式系统中的应用

本文探讨了一种新的负载平衡调度算法,达到高效、合理地进行任务调度和处理机分配。     

实时集群中一种基于任务分配表的动态负载平衡算法

动态负载平衡问题是影响实时集群性能的重要因素。文章在分析实时集群负载平衡特点的基础上,提出了一种基于任务分配表的动态负载平衡算法,并对算法的设计思想和具体实现进行了详细阐述。算法在某指控实时集群系统中的应用证明了它的可行性。     

面向同构型多处理机系统的动态负载平衡算法

为了解决同构型多处理机系统中的负载不平衡问题,提出一种分布式控制、发送者驱动的动态平衡算法,该算法利用CPU队列长度衡量处理机负载状态、利用进程执行时间选取适合被迁移的负载、利用较完备的消息机制传播处理机负载状态和负载平衡要求,适用于计算密集型任务.实验结果验证了该算法的有效性.     

一种实时集群计算机系统动态负载平衡算法的研究

负载平衡是集群计算机并行计算的核心问题。该文在研究了多种非实时并行系统负载平衡算法后,根据实时集群系统的特点,提出了一种基于动态任务分配表的负载平衡算法,并对算法的设计思想和实现作了阐述。     

并行计算稀疏矩阵乘以向量的负载平衡算法

稀疏矩阵乘以一个向量（SpM×V）的问题是许多大型应用问题的核心计算问题，文中提出了一种在并行计算机上并行计算SpMXV的负载平衡算法，计算复杂性为O（N）（N为稀疏矩阵的阶），而目前计算此类问题的最优负载平衡算法的计算复杂性为O（N·P）（P为处理机台数）。文章最后给出了并行数值实验。     

并行计算中的负载均衡问题研究

在多处理机系统中,任务的静态分配和进程的动态调度都要求做到负载平衡。一个负载平衡的多处理机系统,将具有较高的系统性能,使并行程序总的执行时间最短。本文介绍了并行计算中的负载均衡问题,着重对动态负载平衡算法的组成以及几种典型的动态负载平衡算法进行了讨论与分析。     

Optimal Load Balancing in a Multiple Processor System with Many Job Classes

A loosely coupled multiprocessor system contains multiple processors which have their own local memories. To balance the load among multiple processors is of fundamental importance in enhancing the performance of such a multiple processor system. Probabilistic load balancing in a heterogeneous multiple processor system with many job classes is considered in this study. The load balancing scheme is formulated as a nonlinear programming problem with linear constraints. An optimal probabilistic load balancing algorithm is proposed to solve this nonlinear programming problem. The proposed load balancing method is proven globally optimum in the sense that it results in a minimum overall average job response time on a probabilistic basis.     

XML数据查询的并行算法

目前已经提出了多种查询XML数据的方法,然而这些传统的方法不能充分利用多处理器和多核心处理器的优势。本文提出了一种XML查询的并行算法,大幅提高了共享存储器多处理器、多核心处理器系统中XML数据的查询效率。     

基于快速分配机制的动态负载平衡算法

针对同构型多处理机系统中的动态负载平衡问题，制定了若干规则，对搜索轻载节点的过程进行约束，提出一种能快速分配多余负载的、分布式控制、发送者驱动的动态负载平衡算法，实验证明该算法在处理计算密集型任务时，具有较好的有效性。     

基于MPI高性能计算的方法研究

并行处理在计算能力方面与单处理器的串行处理相比有着无可比拟的优势。个人计算机和网络成本的下降使得使用分布式系统进行并行处理的现象越来越普遍,而分布式网络系统中多采用MPI作为并行编程标准。为了减少程序运行时间,改善MPI计算的性能,负载均衡方法尤为重要,本文提出一种在MPI并行处理中负载均衡的方法,可以按照节点的计算能力和负载情况,在节点之间分配和迁移任务。实验表明,本文提出的方法可有效提高MPI并行处理的性能。     

基于反馈机制的动态负载平衡算法研究*

动态负载平衡是提高多处理器系统资源利用率和并行计算性能的重要途径。为了解决变化负载系统中子任务可并行计算的双重循环(PTM-NL)问题,提出一种基于反馈机制的动态负载平衡算法。该算法以处理器作业速度为负载指标,在循环计算中根据反馈的负载指标分配计算任务,动态适应负载变化。实验结果表明,该算法在变化负载的系统中能有效提高PTM-NL问题并行效率。     

A load balancing mechanism for large scale multiprocessor systems and its implementation

In large scale multiprocessor systems, the distance between processors should be taken into account by software to reduce the network traffic and the communication overhead. A load balancing method based on P³ (Processing Power Plane) model is proposed to enable programmers to specify distributing computational load, keeping the locality of the computation. In this method, a process is allocated to a rectangle on a hypothetical processing power plane. The size of the rectangle represents the processing power given to the process, and the distance between rectangles represents the communication cost between them. This plane is divided to processors, and the region of the processor may be dynamically reshaped to alleviate imbalance on P³. Mechanism for realization of the method has been implemented on the Multi-PSI/version, 2, which is a parallel processing system with 64 processing elements connected to form a 2-dimensional mesh network. A packet transmission mechanism of the Multi-PSI/version 2 is described, which realizes the process distribution along with the balancing method.     

Load balancing strategies for a parallel ray-tracing system based on constant subdivision

Static and dynamic load balancing strategies for a multiprocessor system for a ray tracing algorithm based on constant subdivision are presented. An object space is divided into regular cubes (subspaces), whose boundary planes are perpendicular to the coordinate axes, and these are allocated to the processors in the system. Here, load balancing among the processors is the most important problem. Firstly, in a category of static load balancing, strategies for mapping the subspaces into the processors are evaluated by simulation. Moreover, we propose a hierarchical multiprocessor system in order to realize dynamic load balancing with the static one. Its architecture can overcome the limitation of the static load balancing in a large scale multiprocessor system.     

Load Management in Loosely Coupled Multiprocessor Systems

Scheduling is a typical technique used to distribute the load in multiprocessor systems. Usually, the manager(dispatcher or operating system)schedule the tasks so that the average finish time is minimized. Constraints related to the characteristics of the load such as precedence relation, deadline time, etc. must be taken into consideration. With ever increasing applications of a new paradigm of divisible tasks in image processing and parallel processing, one must concentrate on the characteristics of the system such as processor speed, link speed, and processor interconnection topology when distributing the load. By exploiting queuing theory, we managed to find different bounds on the arrival rate(load) as a function of link speed, processor speed and the size of tasks. A flow control mechanism for different multiprocessor systems with different topologies is embedded in our analysis. Moreover, our model indicates to the design engineers, depending on the traffic intensity, which element(s)of a parallel system has to be upgraded or replaced to meet the new load. This, of course, has to be justified by cost consideration.     

Parallel branch and bound on fine-grained hypercube multiprocessors

In this paper, we study parallel branch and bound on fine grained hypercube multiprocessors. Each processor in a fine grained system has only a very small amount of memory available. Therefore, current parallel branch and bound methods for coarse grained systems ( 1000 nodes) cannot be applied, since all these methods assume that every processor stores the path from the node it is currently processing back to the node where the process was created (the back-up path). Furthermore, the much larger number of processors available in a fine grained system makes it imperative that global information (e.g. the current best solution) is continuously available at every processor; otherwise the amount of unnecessary search would become intolerable. We describe an efficient branch-and-bound algorithm for fine grained hypercube multiprocessors. Our method uses a global scheme where all processors collectively store all back-up paths such that each processor needs to store only a constant amount of information. At each iteration of the algorithm, all current nodes may decide whether they need to create new children, be pruned, or remain unchanged. We describe an algorithm that, based on these decisions, updates the current back-up paths and distributes global information in O(log m) steps, where m is the current number of nodes. This method also includes dynamic allocation of search processes to processors and provides optimal load balancing. Even if very drastic changes in the set of current nodes occur, our load balancing mechanism does not suffer any slow down.