Cilk: An Efficient Multithreaded Runtime System

Cilk (pronounced “silk”) is a C-based runtime system for multithreaded parallel programming. In this paper, we document the efficiency of the Cilk work-stealing scheduler, both empirically and analytically. We show that on real and synthetic applications, the “work” and “critical-path length” of a Cilk computation can be used to model performance accurately. Consequently, a Cilk programmer can focus on reducing the computation's work and critical-path length, insulated from load balancing and other runtime scheduling issues. We also prove that for the class of “fully strict” (well-structured) programs, the Cilk scheduler achieves space, time, and communication bounds all within a constant factor of optimal. The Cilk runtime system currently runs on the Connection Machine CM5 MPP, the Intel Paragon MPP, the Sun Sparcstation SMP, and the Cilk-NOW network of workstations. Applications written in Cilk include protein folding, graphic rendering, backtrack search, and the Socrates chess program, which won second prize in the 1995 ICCA World Computer Chess Championship.     

An Efficient Data Dissemination Scheme for Spatial Query Processing

Due to the personal portable devices and advances in wireless communication technologies, Location Dependent Information Services （LDISs） have received a lot of attention from both the industrial and academic communities. In LDISs, it is important to reduce the query response time, since a late query response may contain out-of-date information. In this paper, we study the issue of LDISs using a Voronoi Diagram. We introduce a new NN search method, called the Exponential Sequence Scheme （ESS）, to support NN query processing in periodic broadcast environment. This paper aims to provide research directions towards minimizing both the access latency and energy consumption for the NN-query processing.     

An Efficient and Scalable Image Filtering Framework Using VIPS Fusion

Edge‐preserving image filtering is a valuable tool for a variety of applications in image processing and computer vision. Motivated by a new simple but effective local Laplacian filter, we propose a scalable and efficient image filtering framework to extend this edge‐preserving image filter and construct an uniform implementation in O (N) time. The proposed framework is built upon a practical global‐to‐local strategy. The input image is first remapped globally by a series of tentative remapping functions to generate a virtual candidate image sequence (Virtual Image Pyramid Sequence, VIPS). This sequence is then recombined locally to a single output image by a flexible edge‐aware pixel‐level fusion rule. To avoid halo artifacts, both the output image and the virtual candidate image sequence are transformed into multi‐resolution pyramid representations. Four examples, single image dehazing, multi‐exposure fusion, fast edge‐preserving filtering and tone‐mapping, are presented as the concrete applications of the proposed framework. Experiments on filtering effect and computational efficiency indicate that the proposed framework is able to build a wide range of fast image filtering that yields visually compelling results.     

网格数据检索中结果集的合并算法

随着网格从科学计算转到企业级应用,要求数据库提供多种服务支持以实现更强更丰富的资源共享和应用。网格上的数据库只能通过网格服务进行访问,而数据库中的数据也只能通过网格服务接口来存取。因此如何在网格环境下直接对分布在各地的数据库进行高效的检索就是迫切要解决的问题。本文首先提出了一个网格环境下数据检索的体系结构,然后针对该结构下的数值型数据的Top-k查询问题给出了GrangM算法,它有效解决了来自不同数据源查询结果的合并问题。对该算法的模拟实现表明,它可以快速、高效地合并网格中多结点检索出的结果,减少连接中间结果的大小,降低发送查询请求的通信量。     

一种异构集群中能量高效的大数据处理算法

集群的能量消耗已经超过了其本身的硬件购置费用,而大数据处理需要大规模的集群耗费大量时间,因此如何进行能量高效的大数据处理是数据拥有者和使用者亟待解决的问题,也是对能源和环境的一个巨大挑战.现有的研究一般通过关闭部分节点以减少能量消耗,或者设计新的数据存储策略以便实施能量高效的数据处理.通过分析发现即便使用最少的节点也存在很大的能源浪费,而新的数据存储策略对于已经部署好的集群会造成大规模的数据迁移,消耗额外的能量.针对异构集群下I/O密集型的大数据处理任务,提出一种新的能量高效算法MinBalance,将问题分为节点选择和负载均衡两个步骤.在节点选择阶段采用4种不同的贪心策略,充分考虑到节点的异构性,尽量选择最合适的节点进行任务处理;在负载均衡阶段对选择的节点进行负载均衡,以减少各个节点因为等待而造成的能量浪费.该方法具有通用性,不受数据存储策略的影响.实验表明MinBalance方法在数据集较大的情况下相对于传统关闭部分节点的方法可以减少超过60%的能量消耗.     

一种高效可扩展的传感器网络系统状态监测协议

具备一种底层基础设施来指示网络运行时的失效节点、资源消耗以及系统综合性能,对于传感器网络这样的分布式系统相当重要.研究了用于系统状态监测的数据分发与收集网络协议,提出了基于最大连通度的分簇模型,并通过仿真对其有效性进行了验证,在该模型基础上设计与实现了用于系统状态监测的层次型数据分发与收集网络协议,仿真证明该协议与现有数据分发与收集协议相比具有更好的可扩展性与能量有效性.     

存储容量可扩展区块链系统的高效查询模型

区块链技术是目前计算机领域的研究热点,其实现了去中心化,并且能够安全地存储数字信息,有效降低现实经济的信任成本.提出一种区块链存储容量可扩展模型的高效查询方法——ElasticQM.此查询模型由用户层、查询层、存储层和数据层这4个模块组成.在用户层,模型将查询结果缓存,加快再次查询相同数据时的查询速度;在查询层,模型采用容量可扩展区块链模型的全局查询优化算法,增加了查询超级节点、查询验证节点和查询叶子节点这3种节点角色,提高了查询效率;在存储层,模型改进了区块链的容量可扩展模型ElasticChain的数据存储过程,实现了存储的可扩展性,并减少了占用的存储空间;在数据层,提出一种基于B-M树的区块链存储结构,并给出了B-M树的建立算法和基于B-M树的查找算法,基于B-M树的存储结构,区块链会在进行块内局部查找时提高区块链的查询速度.最后,通过在多节点不同数据量的区块链中查询的实验结果表明,ElasticQM查询方法具有高效的查询效率.     

可以动态修改的数据库系统

本文介绍了利用ＰｏｗｅｒＢｕｉｌｄｅｒ６．０的动态（Ｄｙｎａｍｉｃ）数据窗口（ＤａｔａＷｉｎｄｏｗ）技术修改数据库的列属性名称,并且保存所做修改的办法。     

Using Data Flow Information to Obtain Efficient Check Sets for Algorithm-Based Fault Tolerance

Algorithm-Based Fault Tolerance (ABFT) is a well known technique for achieving fault and error detection in multiprocessor systems. We examine several issues concerning ABFT systems when the data flow information for the underlying multiprocessor computation is available. Our results show that this finergrained information can be exploited to obtain test schemes involving fewer checks, in some cases, dramatically fewer checks. We address both the analysis and design of ABFT systems when the data flow information is available. The analysis problem for a given ABFT system is to determine the fault detectability and the fault locatability (maximum number of detectable and locatable faulty processors) of the system. We show that the analysis problem can be solved efficiently when the number of faults is fixed. We also address the computational difficulty of this problem when the number of faults is not fixed. The design problem is concerned with the construction of a minimal collection of checks which can detect or locate a specified number of faults for a given multiprocessor computation. We examine some special classes of data flow graphs and establish upper and lower bounds on the number of checks needed to detect or locate a given number of faults. We also address the computational difficulty of this design problem for several cases.     

一种高效体数据压缩算法及其在地震数据处理中的应用

采用可编程图形硬件对大规模体数据进行直接体绘制时常常受到图形卡容量的限制,导致数据在内存与显存之间频繁交换,从而成为绘制的瓶颈.为此,提出一种大规模体数据矢量量化压缩算法.首先对体数据分块,并依据块内数据平均梯度值是否为0对该块进行分类;然后用3层结构表示梯度值非0的块,对其中次高层和最高层采用基于主分量分析分裂法产生初始码书,用LBG算法进行码书优化和量化,而对最低层以及梯度值为0的块采用定比特量化.实验结果表明,在保证较好图像重构质量的前提下,该算法可获得50倍以上的压缩比和更快的解压速度.     

X—射线粉末衍射数据信息处理系统

本文介绍了X-射线粉末衍射数据信息处理系统的总体结构、库文件结构及谱图识别的策略.核心是三强峰预检、元素信息的匹配,以及用"链式递推法"和元素信息控制组合膨胀以得到混合物样品的组成.为适应不同需要,本系统把总库分为无机、有机、NBS、金属及合金、地质、常用等八个分库,用户也可自建库.通过PDF号、分子式、矿物名称等可方便快速地检索标准数据.系统用Fortran 77实现于IBM PC/XT(AT)及其兼容机上,要求20M硬盘,640K内存.     

构建一种高效的Web网站访问数据获取系统

提出了一种基于客户端的访问数据获取机制，它有效地克服了现存的不足，同时给出了构建实现系统的结构。     

Scalable and Efficient Video Coding Using 3-D Modeling

In this paper, we present a three-dimensional (3D) model-based video coding scheme for streaming static scene video in a compact way but also enabling time and spatial scalability according to network or terminal capability and providing 3D functionalities. The proposed format is based on encoding the sequence of reconstructed models using second-generation wavelets, and efficiently multiplexing the resulting geometric, topological, texture, and camera motion binary representations. The wavelets decomposition can be adaptive in order to fit to images and scene contents. To ensure time scalability, this representation is based on a common connectivity for all 3D models, which also allows straightforward morphing between successive models ensuring visual continuity at no additional cost. The method proves to be better than previous methods for video encoding of static scenes, even better than state-of-the-art video coders such as H264 (also known as MPEG AVC). Another application of our approach are smoothing camera path for suppression of jitter from hand-held acquisition and the fast transmission and real-time visualization of virtual environments obtained by video capture, for virtual or augmented reality and interactive walk-through in photo-realistic 3D environments around the original camera path     

应用RFID的便携式数据采集与处理系统的研究

本文介绍了一种应用RFID技术的便携式数据采集与处理系统,给出了其工作原理及硬件组成,详细阐述了其软件设计中的两大关键技术,预测了其应用前景.     

一种高效的多路数据采集与处理系统模型

分析了现有数据采集与处理系统模型在高数据率、大数据量应用中存在的弊端,提出了一种新的高效的系统模型,基于该模型建立的多路视频数据采集系统取得了良好的运行效果,充分证明了这种模型的实时性和高效性。     

TKEP:海量数据上一种有效的Top-K查询处理算法

在许多应用领域中,top-k查询是一种十分重要的操作,它根据给定的评分函数在潜在的巨大的数据空间中返回k个最重要的对象.不同于传统的TA算法,NRA算法只需要顺序读就可以处理top-k查询,从而适合于随机读受限或不可能的场合.文中详细地分析了NRA算法的执行行为,确定了增长阶段和收缩阶段中每个文件需要扫描的元组个数.文中发现在海量数据环境中,NRA在增长阶段需要维护大量的候选元组,严重影响了算法的执行效率.所以,文中提出一种新的海量数据上的top-k查询算法TKEP,该算法在查询的增长阶段就执行早剪切,从而大大减少增长阶段需要维护的候选元组.文中给出了早剪切操作的数学分析,确定了早剪切操作的理论和实际剪切效果.据作者所知,该文是第一篇提出在top-k查询的增长阶段执行早剪切的文章.实验结果表明,和传统的NRA相比,TKEP在增长阶段维护的元组数量减少3个数量级,需要的内存量减少1个数量级,TKEP算法获得1个数量级的加速比.     

一种处理Skyline查询的有效方法

skyline查询是近年来数据库领域的一个研究重点和热点.当系统中存在多个不同维空间上的skyline查询时,现有的工作均直接从底层关系表中获取这些skyline查询的结果集.显然,当底层关系表的基数较大且skyline查询的个数较多时,现有方法的处理效率极其低下.基于此,提出一种使用预存储的n个skyline集合{PR\\-1,…,PR\\-n}来回答用户提交的m个不同维空间上的skyline查询{SQ\\-1,…,SQ\\-m}的有效方法EAPSQ(efficient algorithm for processing skyline queries).算法充分考虑预存储的skyline集合的编码机制,采用经济学中边际贡献(contribution margin)的概念,使得m个用户提交的skyline查询在n个预存储的skyline集合间的分配达到最佳状态,从而显著提高了处理用户m个skyline查询的效率.实验评估表明,EAPSQ算法具有有效性和实用性.     

一种利用并发提高数据处理吞吐率的模型

针对分布式组网终端集中式数据采集与处理系统实时性高、数据吞吐量大、周期性强等特点,引入了一种利用并发机制的大吞吐量实时数据处理模型,在讨论模型基本结构和原理的基础上,深入研究了决定模型数据吞吐效率和时效性能的并发缓存机制和算法设计。利用该模型实现的数据采集处理系统在基于GPRS组网的1500个自动气象站数据采集与处理业务应用中,性能稳定可靠,能够满足对周期性大批量实时＂浪涌＂数据进行实时快速处理的要求,大大提高了数据处理的吞吐效率。     

示温漆温度自动判读与数据处理系统

本文介绍了基于微型计算机和高分辩率面阵ＣＣＤ的示温漆采集与数据处理系统。该系统在研究示温漆颜色温度特性的基础上,依据色度学理论、综合运用图像处理与数据库技术实现了示温漆温度判读与数据处理的自动化。实测数据表明,该系统显著提高了显温漆温度判读的准确性。     

基于值-剖面的OpenMP运行时优化系统

本文设计并实现了一个基于值一剖面的OpenMP运行时优化系统CCRG OpenMP。它能够根据常见的值的组合优化并行区域，并且在运行时只有并行区代码需要重编译和管理。CCRG OpenMP基于动态重编译技术，避免了目前静态多版本技术的不足。同时，值-剖面的收集和分析由独立的动态优化器线程完成，降低了动态重编译引入的开销。SPEC OMP2001基准测试表明，我们基于值一剖面的Open MP优化系统能够较大地提高程序性能。