异构机群系统上双序列全局比对并行算法

对于处理机节点具有不同的计算速度、通信延迟和存储容量的异构机群系统,考虑通信启动开销,基于可分负载理论,提出一种双序列全局比对问题并行处理的最优分配策略,利用该策略确定出并行迭代次数和分配给各个从处理机的子序列长度。异构PC机群系统上的实验结果表明,提出的双序列全局比对并行算法优于基于平均分配策略的并行比对算法,获得良好的加速和可扩展性。     

存储受限异构机群系统的多目标串近似匹配并行算法

针对处理机节点具有不同的计算能力、通信延迟和存储容量的情形,考虑计算和通信启动开销,给定处理机分配顺序,基于可分负载理论,分别建立单层和两层树结构模型的存储受限异构机群系统的目标串最优分配线性规划模型,给出相应的目标串最优分配方法,并讨论了处理机最优分配顺序.实验结果表明,本文提出的基于最优分配方法的多目标串近似匹配并行算法优于平均分配算法,获得了较好的加速并具有良好的可扩展性.     

异构机群系统上近似串匹配并行算法

基于可分负载理论的最优原则,在假定正文串分配顺序固定的前提下,考虑处理机节点具有不同计算速度、不同通信能力的情况,提出一种异构机群计算环境下的最优正文串分配策略,给出最优正文串分配的闭合解。对于节点具有不同计算速度、通信能力、存储容量的异构机群系统,建立正文串最优分配的线性规划模型。针对几种特殊情况讨论正文串的最优分配顺序。实验结果表明,与平均分配正文串策略以及按照从处理机能力分配正文串策略相比,利用该策略进行近似串匹配并行处理所需时间分别缩短了10%~40%和5%~20%。     

异构机群系统上基于多轮分配方式的近似串匹配并行算法

在给定正文串分配轮数的前提下,考虑处理机节点具有不同计算速度、不同通信能力的情形,根据从处理机是否允许重叠执行计算和通信操作,提出异构机群计算环境下的最优正文串多轮分配策略;同时提出一种周期性的正文串多轮分配策略并给出了相应的正文串多轮分配的闭合解,此策略可以求出最优的分配轮数.实验结果表明,正文串多轮分配策略比正文串单轮分配策略大大缩短了近似串匹配并行处理的时间,并且在正文串多轮分配策略中,当近似串匹配应用的规模较小时,分配轮数比参与近似串匹配并行处理的从处理机数更能影响近似串匹配并行处理的完成时间,反之,从处理机数对近似串匹配并行处理的完成时间影响更大.     

异构机群上高效可扩展的Motif发现并行算法

在节点具有不同计算速度、不同通信能力的异构机群系统上,分别建立求解l≤16和l>16的Motif发现问题的最优序列分配模型,在此基础上设计实现融合投票和统一投影-邻居阈值思想的Motif发现并行算法。实验结果表明,给出的基于最优序列分配策略的Motif发现并行算法具有良好的加速和可扩展性,优于采用平均分配策略的Motif发现并行算法。     

具有通信序列的网络控制系统LQG控制器设计

研究了具有通信序列的网络控制系统控制器设计问题.通过在系统的输入输出端设计通信序列,分时占用网络,以降低带宽约束对系统的影响,进而构建了具有通信序列的网络控制系统模型;在此基础上,将网络控制器设计分为2个部分,首先,基于输出值设计Kalman滤波器,用于提供最优状态估计值;然后,在考虑通信序列的基础上利用LQG方法协同...     

序列捕获的序列核变换方法

在序列扩频、加扰通信系统中,通常采用连续接收信号并进行滑动相关运算的方法,通过搜索相关峰进行序列捕获,需要接收多个完整周期的序列。随着序列周期的加大,一方面需要花费大量的接收端存储资源,另一方面,相关运算的计算开销会呈指数增长,导致很难实时捕获长周期序列。为解决这一问题,提出了一种序列核变换方法,变换后的每个元素均包含有完整的序列信息,实现了序列信息压缩。然后,基于该变换方法将捕获过程分为序列检测和序列捕获两个阶段,只在检测到目标序列后才开始捕获,进一步降低了计算开销。理论分析和仿真验证表明,算法通过牺牲部分低信噪比环境下的捕获成功率换取了计算资源的大量减少,算法可在一个序列周期内快速捕获不同周期的m序列,并且所节省的计算资源随序列周期变大而增多。     

OFDM系统中基于训练序列的参数信道估计算法的改进

针对OFDM通信系统中基于训练序列的常规信道估计算法存在矩阵求逆过程,使算法计算量过大的现象,提出了一种基于最优训练序列的信道估计简化算法。该算法通过对训练序列的最优设计,避免了矩阵求逆,大大降低了算法的复杂度和运算量。通过仿真实验,表明优化后的信道估计算法具有更好的性能和实际应用价值。     

基于基本操作序列的编辑距离顺序验证

两字符串的编辑距离是从一个串转换到另一个串所需要的最少基本操作数。编辑距离广泛应用于字符串近似匹配、字符串相似连接等领域。动态规划法利用编辑距离矩阵来计算两个串的编辑距离,需要计算矩阵中的所有元素,时间效率低。改进的方法改变了矩阵中元素的计算次序,减少了需要比对的元素,但仍需要比对一半以上的元素,时间效率还有待提高。提出基于基本操作序列的编辑距离顺序验证方法。首先,分析了基本操作序列的可列性,给出了列举基本操作序列的方法。然后依次顺序验证基本操作数从小到大的基本操作序列直到某一序列通过验证,得到其编辑距离。在阈值为2的字符串近似搜索实验中发现,所提方法比动态规划类方法具有更高的效率。     

异构机群系统上带返回信息的可分负载多轮调度算法

针对处理机具有不同的计算速度、通信能力的异构机群计算环境,以及实际应用中许多问题的求解在处理完任务后向中心处理机节点返回处理结果信息的情形,通过允许计算和通信操作重叠执行,采取FIFO调度策略和多次并行分配计算任务的方法,提出一种带返回结果信息的调度轮数可变的可分负载多轮调度算法.实验结果表明,该算法对于处理具有返回结果信息的应用的调度性能优于UMR可分负载多轮调度算法,并且可以获得近似最优的调度轮数.     

Partitioning of Independent Tasks for Minimizing Completion Time and Total Waiting Time

Parallel processors provide fast computing environments for various users.But the real efficiencies of parallel processors intensively depend on the partitioning strategies of tasks over the processors.In this paper,the partitioning problems of independent tasks for homogeneous system of parallel processors are quantitatively studied.We adopt two criteria,minimizing the completion time and the total waiting time, to determine the optimal partitioning strategy.     

On balancing sorting on a linear array

A balanced parallel algorithm to sort a sequence of items on a linear array of processors is presented. The length of the sequence may be small to arbitrarily large. For a short sequence, the output of the sorted sequence begins at the step following the last input of the whole sequence. For an arbitrarily long sequence, the time complexity is optimal under realistic hardware conditions. A variation of the algorithm is also introduced. Both algorithms require far less local memory than that required by a different approach of balanced computation. Any number of balanced processors can be connected to deliver more computing power without increasing the memory size of each processor     

Handling biological sequence alignments on networked computing systems: A divide-and-conquer approach

In this paper, we address the biological sequence alignment problem, which is one of the most commonly used steps in several bioinformatics applications. We employ the Divisible Load Theory (DLT) paradigm that is suitable for handling large-scale processing on network-based systems to achieve a high degree of parallelism. Using the DLT paradigm, we propose a strategy in which we carefully partition the computation work load among the processors in the system so as to minimize the overall computation time of determining the maximum similarity between the DNA/protein sequences. We consider handling such a computational problem on networked computing platforms connected as a linear daisy chain. We derive the individual load quantum to be assigned to the processors according to computation and communication link speeds along the chain. We consider two cases of sequence alignment where post-processes, i.e., trace-back processes that are required to determine an optimal alignment, may or may not be done at individual processors in the system. We derive some critical conditions to determine if our strategies are able to yield an optimal processing time. We apply three different heuristic strategies proposed in the literature to generate sub-optimal solutions for processing time when the above conditions cannot be satisfied. To testify the proposed schemes, we use real-life DNA samples of house mouse mitochondrion and the DNA of human mitochondrion obtained from the public database GenBank [GenBank, http://www.ncbi.nlm.nih.gov] in our simulation experiments. By this study, we conclusively demonstrate the applicability and potential of the DLT paradigm to such biological sequence related computational problems.     

Efficient geometric algorithms on the EREW PRAM

We present a technique that can be used to obtain efficient parallel geometric algorithms in the EREW PRAM computational model. This technique enables us to solve optimally a number of geometric problems in O(log n) time using O(n/log n) EREW PRAM processors, where n is the input size of a problem. These problems include: computing the convex hull of a set of points in the plane that are given sorted, computing the convex hull of a simple polygon, computing the common intersection of half-planes whose slopes are given sorted, finding the kernel of a simple polygon, triangulating a set of points in the plane that are given sorted, triangulating monotone polygons and star-shaped polygons, and computing the all dominating neighbors of a sequence of values. PRAM algorithms for these problems were previously known to be optimal (i.e., in O(log n) time and using O(n/log n) processors) only on the CREW PRAM, which is a stronger model than the EREW PRAM     

Distributed Computation with Communication Delays: Asymptotic Performance Analysis

This paper analyzes the effect of communication delay on the optimal distribution of processing loads in distributed computing networks. The processing load is assumed to satisfy the property of arbitrary divisibility. The objective is to divide and distribute this processing load among various processors in the network in order to minimize the processing time. An asymptotic analysis of the performance of such networks is carried out to obtain a limit on the performance enhancement obtained by using additional processors. The architectures considered are linear and single-level tree configurations. The cases when the processors are equipped with and without front-ends are considered.