基于簇的层次敏感的可重构系统任务划分算法

对于可重构计算中面积约束条件下的任务划分问题,提出一种基于簇的、层次敏感的划分LSCBP算法.该算法按照依赖优先、最早最先和碎片利用三原则构造了新的启发函数AS_Level,能够跟踪节点分配过程并进行动态调整;它克服了CBP算法机械选取节点进行划分的缺点,同时算法复杂度也增大到O{｜ V｜^2＋｜ E｜}.对随机生成的任务图（节点数小于250）的划分实验表明：对于相同的DAG,LSCBP算法能够比CBP算法获得更少的任务簇（可重构资源需求量）和簇间有向边（通信代价）.     

动态可重构系统的时域划分及其行为级算法的定量分析

对近20年来可重构系统的时域划分算法进行了分析,把它们分为网表级和行为级算法两大类.网表级时域划分算法主要采用网络流方法,使电路的面积、割网的个数等最小化,并使电路获得较小的时延和通信代价.我们对层划分、簇划分、增强静态列表调度、多目标时域划分等四种行为级时域划分算法进行了定量分析和比较,评价指标体系包括划分后的模块数、跨模块的输入/输出边数、划分后所有模块的执行总延迟.实验结果表明,层划分是四个算法划分后所有模块执行总延迟最小的;簇划分算法获得较少的跨模块的输入/输出边数;增强的静态列表调度和多目标时域划分两个算法在三个指标之间获得了一个好的折中.然而,这四个算法均没有考虑划分后的模块形状及模块的跨层映射成本.     

Parallel Algorithms for Partitioning Sorted Sets and Related Problems

We consider the following partition problem: Given a set S of n elements that is organized as k sorted subsets of size n/k each and given a parameter h with 1/k ≤ h ≤ n/k , partition S into g = O(n/(hk)) subsets D ₁ , D ₂ , . . . , D _g of size Θ(hk) each, such that, for any two indices i and j with 1 ≤ i < j ≤ g , no element in D _i is bigger than any element in D _j . Note that with various combinations of the values of parameters h and k , several fundamental problems, such as merging, sorting, and finding an approximate median, can be formulated as or be reduced to this partition problem. The partition problem also finds many applications in solving problems of parallel computing and computational geometry. In this paper we present efficient parallel algorithms for solving the partition problem and a number of its applications. Our parallel partition algorithm runs in O( log n) time using processors in the EREW PRAM model. The complexity bounds of our parallel partition algorithm on the respective special cases match those of the optimal EREW PRAM algorithms for merging, sorting, and finding an approximate median. Using our parallel partition algorithm, we are also able to obtain better complexity bounds (even possibly on a weaker parallel model) than the previously best known parallel algorithms for several important problems, including parallel multiselection, parallel multiranking, and parallel sorting of k sorted subsets. Received May 5, 1996; revised July 30, 1998.     

基于遗传算法的软硬件划分方法

针对SOC软硬件协同设计中的软硬件划分问题,首先构建了软硬件划分的系统模型,讨论了影响SOC性能的价格、执行时间、功耗、面积等因素及其相互关系。在此基础上,提出了一个旨在实现最优性价比的目标函数,并结合软硬件划分问题自身的特点对传统遗传算法的遗传操作进行了改进,在Matlab中进行了软硬件划分方法的仿真,仿真实验获得的结果有力地证明了算法的稳定性和有效性。同时,该算法在MPEG-2视频解码芯片设计中得到了实际应用,芯片设计的结果良好地反映了设计目标,证明了算法的实用性。     

Smoothed Analysis of Partitioning Algorithms for Euclidean Functionals

Euclidean optimization problems such as TSP and minimum-length matching admit fast partitioning algorithms that compute near-optimal solutions on typical instances. In order to explain this performance, we develop a general framework for the application of smoothed analysis to partitioning algorithms for Euclidean optimization problems. Our framework can be used to analyze both the running-time and the approximation ratio of such algorithms. We apply our framework to obtain smoothed analyses of Dyer and Frieze’s partitioning algorithm for Euclidean matching, Karp’s partitioning scheme for the TSP, a heuristic for Steiner trees, and a heuristic for degree-bounded minimum-length spanning trees.     

Algorithms and Support for Horizontal Class Partitioning in Object-Oriented Databases

Horizontal partitioning is a logical database design technique which facilitates efficient execution of queries by reducing the irrelevant objects accessed. Given a set of most frequently executed queries on a class, the horizontal partitioning generates horizontal class fragments (each of which is a subset of object instances of the class), that meet the queries requirements. There are two types of horizontal class partitioning, namely, primary and derived. Primary horizontal partitioning of a class is performed using predicates of queries accessing the class. Derived horizontal partitioning of a class is the partitioning of a class based on the horizontal partitioning of another class. We present algorithms for both primary and derived horizontal partitioning and discuss some issues in derived horizontal partitioning and present their solutions. There are two important aspects for supporting database operations on a partitioned database, namely, fragment localization for queries and object migration for updates. Fragment localization deals with identifying the horizontal fragments that contribute to the result of the query, and object migration deals with migrating objects from one class fragment to another due to updates. We provide novel solutions to these two problems, and finally we show the utility of horizontal partitioning for query processing.     

Selection Algorithms for Parallel Disk Systems

With the widening gap between processor speeds and disk access speeds, the I/O bottleneck has become critical. Parallel disk systems have been introduced to alleviate this bottleneck. In this paper we present deterministic and randomized selection algorithms for parallel disk systems. The algorithms to be presented, in addition to being asymptotically optimal, have small underlying constants in their time bounds and hence have the potential of being practical.     

Server Allocation Algorithms for Tiered Systems

Many web-based systems have a tiered application architecture, in which a request needs to transverse all the tiers before finishing its processing. One of the most important QoS metrics for these applications is the expected response time for the user. Since the expected response time in any tier depends upon the number of servers allocated to this tier, and a request's total response time is the sum of the response times over all the tiers, many different configurations (number of servers allocated to each tier) can satisfy the expected response-time requirement. Naturally, one would like to find the configuration that minimizes the total system cost while satisfying the total response-time requirement. This is modeled as a non-linear optimization problem using an open-queuing network model of response time, which we call the server allocation problem for tiered systems (SAPTS). In this paper we study the computational complexity of SAPTS and design efficient algorithms to solve it. For a variable number of tiers, we show that the decision version of SAPTS is NP-complete. Then we design a simple two-approximation algorithm and a fully polynomial-time approximation scheme (FPTAS). If the number of tiers is a constant, we show that SAPTS is polynomial-time solvable. Furthermore, we design a fast polynomial-time exact algorithm to solve the important two-tier case. Most of our results extend to the general case in which each tier has an arbitrary response-time function.     

一种Jave遗留系统服务化切分和封装方法

SOA是一种新型企业应用架构,为复用存在于Internet上的软件资源提供了一个最佳实践.面对目前可用的服务资源匮乏,同时大量企业信息系统需要借助服务计算技术重组优化的现状,从遗留系统中切分并封装成可复用的服务是实现SOA的关键.目前以人工方式的遗留系统服务化切分和封装过程效率较低且难以保证质量,亟需一种自动化手段辅助开发人员实施这一过程.文中针对Java语言的遗留系统,研究自动化的遗留系统服务化切分和封装技术.在综合静态类结构模型和动态对象调用模型的基础上,提出了一个遗留系统的对象依赖频度图表示模型,并基于面向服务的切分目标设计了一种服务模块自动识别和切分的有效方法,并利用Java语言的执行码重写技术实现了自动化的服务封装工具,最终通过实际的应用案例验证了文中工作的有效性.     

基于遗传算法的VLSI电路划分方法

电路划分是降低超大规模集成电路设计复杂性有效方法,提出了一种基于遗传算法的电路划分算法,该算法不仅适用于电路的二划分和K划分问题,而且可以满足划分对子集的大小和面积等多约束的要求。     

Submodular fractional programming for balanced clustering

We address the balanced clustering problem where cluster sizes are regularized with submodular functions. The objective function for balanced clustering is a submodular fractional function, i.e., the ratio of two submodular functions, and thus includes the well-known ratio cuts as special cases. In this paper, we present a novel algorithm for minimizing this objective function (submodular fractional programming) using recent submodular optimization techniques. The main idea is to utilize an algorithm to minimize the difference of two submodular functions, combined with the discrete Newton method. Thus, it can be applied to the objective function involving any submodular functions in both the numerator and the denominator, which enables us to design flexible clustering setups. We also give theoretical analysis on the algorithm, and evaluate the performance through comparative experiments with conventional algorithms by artificial and real datasets.     

Partitioning a Square into Rectangles: NP-Completeness and Approximation Algorithms

   Abstract. In this paper we deal with two geometric problems arising from heterogeneous parallel computing: how to partition the unit square into p rectangles of given area s ₁ , s ₂ , . . . ,s _p (such that Σ _i=1 ^p s _i = 1 ), so as to minimize either (i) the sum of the p perimeters of the rectangles or (ii) the largest perimeter of the p rectangles? For both problems, we prove NP-completeness and we introduce a 7/4 -approximation algorithm for (i) and a

Partitioning Planar Graphs with Vertex Costs: Algorithms and Applications

We prove separator theorems in which the size of the separator is minimized with respect to non-negative vertex costs. We show that for any planar graph G there exists a vertex separator of total sum of vertex costs at most and that this bound is optimal to within a constant factor. Moreover, such a separator can be found in linear time. This theorem implies a variety of other separation results. We describe applications of our separator theorems to graph embedding problems, to graph pebbling, and to multicommodity flow problems. Received June 1997; revised February 1999.     

Partitioning a Square into Rectangles: NP-Completeness and Approximation Algorithms

In this paper we deal with two geometric problems arising from heterogeneous parallel computing: how to partition the unit square into p rectangles of given area s ₁ , s ₂ , . . . ,s _p (such that Σ _i=1 ^p s _i = 1 ), so as to minimize either (i) the sum of the p perimeters of the rectangles or (ii) the largest perimeter of the p rectangles? For both problems, we prove NP-completeness and we introduce a 7/4 -approximation algorithm for (i) and a $(2/\sqrt{3})$ -approximation algorithm for (ii).     

A Latency-Aware Partitioning Method for Distributed Virtual Environment Systems

Distributed virtual environment (DVE) systems allow multiple users working on different client computer's interconnected through different networks to interact in a shared virtual world. In these systems, latency is crucial for providing an acceptable quality of service (QoS), since it determines how fast client computers are reported about changes in the shared virtual scene produced by other client computers. This paper presents in a unified manner a partitioning approach for providing a latency below a threshold to the maximum number of users as possible in DVE systems. This partitioning approach searches the assignment of avatars, which represents the best trade-off among system latency, system throughput, and partitioning efficiency when solving the partitioning problem. Evaluation results show that the proposed approach not only maximizes system throughput, but also allows the system to satisfy, if possible, any specific latency requirement needed for providing QoS. This improvement is achieved without decreasing either image resolution or quality of animation, and it can be used together with other techniques already proposed. Therefore, it can contribute to provide QoS in DVEs.     

Simple Efficient Load-Balancing Algorithms for Peer-to-Peer Systems

Load balancing is a critical issue for the efficient operation of peer-to-peer (P2P) networks. We give two new load-balancing protocols whose provable performance guarantees are within a constant factor of optimal. Our protocols refine the consistent hashing data structure that underlies the Chord (and Koorde) P2P network. Both preserve Chord's logarithmic query time and near-optimal data migration cost. Consistent hashing is an instance of the distributed hash table (DHT) paradigm for assigning items to nodes in a P2P system: items and nodes are mapped to a common address space, and nodes have to store all items residing closeby in the address space. Our first protocol balances the distribution of the key address space to nodes, which yields a load-balanced system when the DHT maps items "randomly" into the address space. To our knowledge, this yields the first P2P scheme simultaneously achieving O(log n) degree, O(log n) look-up cost, and constant-factor load balance (previous schemes settled for any two of the three). Our second protocol aims to balance directly the distribution of items among the nodes. This is useful when the distribution of items in the address space cannot be randomized. We give a simple protocol that balances load by moving nodes to arbitrary locations "where they are needed." As an application, we use the last protocol to give an optimal implementation of a distributed data structure for range searches on ordered data.     

分布存储系统中优化通信的冗余计算分割

针对并行循环套序列,提出一种冗余计算分割的通信优化方法,根据数据流分析,文中给出用以确定每个循环套的冗余计算量的一般方法,并在此基础上提出冗余计算分割的实现和判定,针对规则依赖的程序,该文还提出了一个高效的冗余计算分割的实现方法,该技术已经在一个并行编译器中实现,试验结果表明,它比传统的通信优化技术有明显的优越性。