一种并行结构路由器保序自适应负载平衡结构

论文提出了一种通用的并行结构路由器具有IP包保序功能的自适应负载平衡结构APOKLB(AdaptivePacket-Order-KeepingLoadBalancer)和一种有效的基于流分类的信元调度算法FCS(FlowClassification-basedScheduling)。分析了FCS的算法复杂度、APOKLB所需内存数量、带宽及其平均排队延迟,并给出了APOKLB与几种保序结构进行了比较。     

一种并行BP神经网络的动态负载平衡方案

为了加快在大规模神经网络训练下并行技术的训练速度问题,从BP算法的内部结构分析了BP神经网络算法的大规模行划分方法,提出了一种动态负载平衡方案。通过在PC集群环境下对并行算法的试验结果表明,这种并行划分提高了加速比,具有现实意义。     

一种并行BP神经网络的动态负载平衡方案

为了加快在大规模神经网络训练下并行技术的训练速度问题，从BP算法的内部结构分析了BP神经网络算法的大规模行划分方法，提出了一种动态负载平衡方案。通过在PC集群环境下对并行算法的试验结果表明．这种并行划分提高了加速比，具有现实意义。     

Euler方程非结构网格分布式并行计算

在二维非结构网格情形下,针对PC集群并行系统提出一种新的并行算法,在前景网格与背景网格之间建立起逻辑映射关系来交换边界计算数据并提高并行效率,该算法在应用中能有效地保持并行系统的负载平衡和边界计算数据的正确交换,多个数值算例的结果表明了该算法的有效性。     

改进的分布式动态自适应负载平衡算法探讨

为了使分布式网络保持高效的运作,在多种常用的负载平衡算法中选择了动态自适应负载平衡算法,根据结点负载情况,区分轻载结点和重载结点。     

并行微观交通动态负载平衡预测方法仿真

研究交通负载平衡优化预测问题,因交通负载量增多,导致车流的突变性呈现无规则瞬时增大.由于车辆分布不平衡,造成难以准确进行观测.传统的串行负载平衡方法面对忽然增加的调度任务,在很多情况下计算消耗时间将会超过实际运营时间,导致负载调度效果不佳.提出一种并行微观交通动态负载平衡预测方法,算法将仿真车辆作为各节点机负载平衡指标,当一台节点机上的负载需要向另一台节点机迁移时,从离子网中心节点最远的节点开始,保证负载迁移后每台节点机上的子网仍然是互连的,保证了速度.以TPSS并行仿真平台进行并行加速比性能和扩展性能测试分析.仿真结果表明,改进算法适用于较大规模的交通网络微观预测,能够获得较好的并行速度效果及预测准确性.     

多处理机系统的自适应动态负载平衡算法研究

通过对多处理机系统中自适应动态负载平衡算法的分析研究,针对现有算法未考虑任务之间通信量及节点机可能出现故障等问题,对现有算法进行了改进,并给出了算法的主体思想。     

一种有效的并行数据库动态负载平衡连接算法

在基于Shared-nothing结构的并行数据库中,负载平衡一直是影响查询处理性能的重要因素。在数据库中频繁使用的连接操作会因为各种因素导致的负载倾斜和额外的通讯开销而降低数据库的整体性能。提出了一种基于RCMD分布方法的动态负载平衡连接算法,能够在连接操作的执行过程中动态调整各个结点的负载。理论分析和实验结果证明提出的算法能够有效地平衡负载,提高并行数据库的执行效率。     

基于非结构滑移网格技术的旋翼型无人机空气动力学并行数值模拟方法

在现代飞行器设计中,数值模拟方法以低成本、高效率和高灵活性等优点成为研究飞行器空气动力学的重要方法.在旋翼型无人机流场模拟中,由于旋翼与机身存在相互作用,为获得精确模拟结果需要对整个无人机的流场进行模拟,因此,有效地模拟旋翼与机身的相对运动是实现成功模拟的关键步骤,这使得此类模拟问题极具挑战性.文章设计了一套求解旋翼型无人机空气动力学数值模拟问题的基于非结构滑移网格技术的高可扩展并行计算方法.该方法对控制方程的离散,在空间方向采用非结构移动网格有限元方法,时间推进采用全隐式二阶向后差分格式,最后采用一种并行Newton-Krylov-Schwarz方法求解离散后的非线性方程组.作为应用,文章对一个真实旋翼型无人机模型在悬停状态下的外流场进行了数值模拟,获得了一些非常详细的流场信息.数值结果显示,算法在天河2号上使用4 096个处理器核时仍具有接近线性的并行加速比,这为下一步开展旋翼型无人机的高保真度快速模拟奠定了良好的基础.     

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.     

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。     

A novel dynamic load balancing scheme for parallel systems

Adaptive mesh refinement (AMR) is a type of multiscale algorithm that achieves high resolution in localized regions of dynamic, multidimensional numerical simulations. One of the key issues related to AMR is dynamic load balancing (DLB), which allows large-scale adaptive applications to run efficiently on parallel systems. In this paper, we present an efficient DLB scheme for structured AMR (SAMR) applications. This scheme interleaves a grid-splitting technique with direct grid movements (e.g., direct movement from an overloaded processor to an underloaded processor), for which the objective is to efficiently redistribute workload among all the processors so as to reduce the parallel execution time. The potential benefits of our DLB scheme are examined by incorporating our techniques into a SAMR cosmology application, the ENZO code. Experiments show that by using our scheme, the parallel execution time can be reduced by up to 57% and the quality of load balancing can be improved by a factor of six, as compared to the original DLB scheme used in ENZO.     

Dynamic load balancing with adaptive factoring methods in scientific applications

To improve the performance of scientific applications with parallel loops, dynamic loop scheduling methods have been proposed. Such methods address performance degradations due to load imbalance caused by predictable phenomena like nonuniform data distribution or algorithmic variance, and unpredictable phenomena such as data access latency or operating system interference. In particular, methods such as factoring, weighted factoring, adaptive weighted factoring, and adaptive factoring have been developed based on a probabilistic analysis of parallel loop iterates with variable running times. These methods have been successfully implemented in a number of applications such as: N-Body and Monte Carlo simulations, computational fluid dynamics, and radar signal processing. The focus of this paper is on adaptive weighted factoring (AWF), a method that was designed for scheduling parallel loops in time-stepping scientific applications. The main contribution of the paper is to relax the time-stepping requirement, a modification that allows the AWF to be used in any application with a parallel loop. The modification further allows the AWF to adapt to load imbalance that may occur during loop execution. Results of experiments to compare the performance of the modified AWF with the performance of the other loop scheduling methods in the context of three nontrivial applications reveal that the performance of the modified method is comparable to, and in some cases, superior to the performance of the most recently introduced adaptive factoring method.

Partitioning of unstructured meshes for load balancing

Many large-scale engineering and scientific calculations involve repeated updating of variables on an unstructured mesh. To do these types of computations on distributed memory parallel computers, it is necessary to partition the mesh among the processors so that the load balance is maximized and interprocessor communication time is minimized. This can be approximated by the problem of partitioning a graph so as to obtain a minimum cut, a well-studied combinatorial optimization problem. Graph partitioning is NP complete, so for real world applications one resorts to heuristics, i.e. algorithms that give good but not necessarily optimum solutions. These algorithms include recursive spectral bisection, local search methods such as Kernighan-Lin, and more general purpose methods such as simulated annealing. We show that a general procedure enables us to combine simulating annealing with Kernighan-Lin. The resulting algorithm is both very fast and extremely effective.     

基于网格计算的混合负载均衡策略

根据分布式系统的静态和动态负载均衡策略的优缺点,提出了在网格计算环境下的混合负载均衡策略.为了让网络中节点在网格计算环境中有效地执行需要大量计算的复杂任务,提出了用来评估节点效率的函数,并结合模拟实验证实了在此函数下算法的优越性.     

网络计算机集群负载均衡机制的研究

目前使用单台网络计算机应用服务器难以满足大量用户的并发访问需求,在网络计算机系统中引入集群/负载均衡技术是解决这一问题的理想途径.研究网络计算机集群的负载均衡机制.设计和实现了适合于网络计算机应用模式的负载评估方法及负载状态更新机制,并在此基础上提出和实现了一种基于分布式协商的动态负载均衡算法.     

A dynamic and adaptive load balancing strategy for parallel file system with large-scale I/O servers

Many solutions have been proposed to tackle the load imbalance issue of parallel file systems. However, all these solutions either adopt centralized algorithms, or lack considerations for both the network transmission and the tradeoff between benefits and side-effects of each dynamic file migration. Therefore, existing solutions will be prohibitively inefficient in large-scale parallel file systems. To address this problem, this paper presents SALB, a dynamic and adaptive load balancing algorithm which is totally based on a distributed architecture. To be also aware of the network transmission, SALB on the one hand adopts an adaptively adjusted load collection threshold in order to reduce the message exchanges for load collection, and on the other hand it employs an on-line load prediction model with a view to reducing the decision delay caused by the network transmission latency. Moreover, SALB employs an optimization model for selecting the migration candidates so as to balance the benefits and the side-effects of each dynamic file migration. Extensive experiments are conducted to prove the effectiveness of SALB. The results show that SALB achieves an optimal performance not only on the mean response time but also on the resource utilization among the schemes for comparison. The simulation results also indicate that SALB is able to deliver high scalability.     

Flexible and extensible load balancing

This paper presents the design philosophy and implementation of the BALANCE system. BALANCE is a flexible, network independent and computer architecture independent load balancing system which allows the building of reusable parallel and distributed applications. By implementing related services as bi generic servers with their connection endpoints registered in BALANCE, the clients can easily access the servers by server system calls. To demonstrate the flexibility of BALANCE, several widely different applications have been implemented and evaluated, including system servers, parallel and distributed applications and a scheduling testbed. The use of generic servers to improve system modularity and code reuse is also discussed. © 1997 John Wiley & Sons, Ltd.     

动态负载均衡算法在校园网格中的应用

校园网格能有效消除信息孤岛,实现我国高校的计算资源和信息资源的有效共享。一个亟待解决的问题是在校园网格环境下,服务器节点响应能力低下。目前已提出多种技术与方案以解决并提高校园网格的服务器节点的响应能力,负载均衡技术就是一种全新的技术。本文根据校园网格的特点和影响负载均衡的因素,对基于校园网格的负载均衡技术进行了分析和探讨,并提出一种动态负载均衡算法。     

工件多目标设计中的一种动态负载均衡算法

在分析了工件多目标设计的集群设计中流程结构特点的基础上,提出了一种反馈控制信息、双负载确认等方式实现的适合于双队列缓存计算模型的动态负载均衡算法,并对算法中的任务调度、适载控制、负载计量、分配策略等的实现进行了详细阐述,最后对该算法的实际应用效果做了具体分析。