分布存储并行计算机优化数据安放一种方法

本文分析了面向分布存储ＳＩＭＤ／ＭＩＭＤ并行机的并行程序的优化数据安放问题，在ＦＯＲＡＬＬ程序模型和ＭＥＳＨ通信模型上，研究了数据分解过程中减少通信代价的优化要求，我们使用编好图描述并行数组之间的对准需求，通过消除维偏好图中的冲突，可得到维对准对准图，一个维对准图就对应一个数据安放方案，维对准图的总代价越大，对应的通信代价就越小，文中给出了最大代价维对准图的一个近似算法。     

面向SIMD机器的全局自动数据分割

提出了一种面向ＳＩＭＤ机器的全局数据自动分割算法,该算法能处理多个非紧嵌折循环嵌套,并且数组下标存取为循环变量的线性式,首先通过数据与迭代映射抽象了计算中的通信方式,然事提出识别规则模式通信模式的形式比条件,接着建立包含对准信息和相应通信开销的数据迭代图,并在数据迭代图的基础上提出了一个启发式算法来计算较优的数据分布和迭代分布,以优化处理单元之间的通信开销,通过发析多个循环嵌套所涉及的多个数组映和     

一个数据并行语言的设计及其实现

数据并行模型应用到ＭＩＭＤ机器上，实现ＳＰＭＤ模式的松散同步的方式越来越受到人们的重视。文中提出了一个以屏构并行系统为环境的数据并行语言Ｍｕｌｔｉ－ｃ的设计和实现。正在实现的Ｍｕｌｉｔｉ－ｃ编译器，以预编译的方式接受ＳＩＭＤ形式的程序说明，放宽同步要求，产生能以ＳＰＭＫ方式在并行系统上运行的Ｃ程序。     

基于MC68360的ISDN路由器设计

探讨了基于Ｍｏｔｏｒｏｉａ集成通信控制器ＭＣ６８３６０的ＩＳＤＮ路由器设计与实现。在介绍了ＩＳＤＮ及ＩＳＤＮ路由器的基本概念，并分析了ＭＣ６８３６０的关键性能的基础上，提出了适合于ＳＯＨＯ（小办公室和家庭办公室）环境的ＢＲＩ界面的ＩＳＤＮ路由器系统设计方案。并进一步探讨了几个有关ＩＳＤＮ数据通信的特殊问题：信道优化，安全和呼叫监控。     

C＊数据并行语言

Ｃ＊语言是通过对ＡＮＳＩＣ语言进行语法和语义的扩展得到的支持ＳＩＭＤ模式的数据并行语言。它允许用户基于一个ＳＩＭＤ虚拟机描述数据在各个虚处理机上的分布以及对这些数据的并行计算操作，提供了一种简单，有效并与任何特定的机器无关的数据并行编程模型。     

采用标准数据接口SDAI的CAD／CAM系统集成

如何将ＳＴＥＰ的方法和规范应用于系统开发是解决计算机集成制造系统（ＣＩＭＳ）开发的关键问题之一。集成化ＣＡＤ／ＣＡＭ系统是ＣＩＭＳ的核心，实现将ＣＡＤ的工程设计功能和ＣＡＭ的制造功能的结合。本文讨论通过ＳＴＥＰ的标准数据接口ＳＤＡＩ实现系统集成的集成方法，采用ＳＴＥＰ的数据交换、建模思想，实现了一个产品模型为核心的ＣＡＤ、ＣＡＭ集成系统－ＧＨＣＡＤ（高化ＣＡＤ）。     

浅析Windows95的自举与卸载

本文剖析了Ｗｉｎｄｏｗｓ９５的自举过程，指出Ｗｉｎｄｏｗｓ９５自举时不依于ＤＯＳ的实模式内核文件：ＭＳ－ＤＯＳ扣的ＩＯ．ＳＹＳ和 ＭＳＤＯＳ．ＳＹＳ，或者ＩＢＭＤＯＳ的ＩＢＭＢＩＯ．ＣＯＭ和ＩＢＭＤＯＳ．ＣＯＭ和ＩＢＭＤＯＳ．ＣＯＭ。     

分布存储媒体传输的同步算法

分布多媒体数据库（ＤＭＤＢ）和分布多媒体信息系统（ＤＭＩＳ）的一个重要需求是多媒体同步传输．文中先分析了在ＤＭＤＢ和ＤＩＭＳ中多媒体同步传输的特点和要求，然后提出了一个能满足这些要求的同步传输方案．在这个方案中，多媒体同步关系是用动态同步Ｐｅｔｒｉ网（ＤＳＰＮ）来显式描述的；通过文中给出的同步传输算式和同步发送算法，可以在ＤＳＰＮ模型的基础上产生同步传输调度方案；同时接收端能根据实际通信状况和多媒体的同步要求，对来自多个服务器的多媒体对象进行动态同步控制．     

美国对地观测系统(EOS)中分辨率成像光谱仪(MODIS)遥感数据的特点与应用

自１９９９年起美国开始了第二阶段对地观测系统计划,中分辨率成像光谱仪（ＭＯＤＩＳ）是该计划中最有特色的仪器之一。通过ＭＯＤＩＳ采集的数据具有３６个波段和２５０ｍ￣１０００ｍ地表分辨率,加上数据以每天上、下午的频率采集和免费接收的数据获取政策,使得ＭＯＤＩＳ数据成为我国地学研究和生态环境监测不可多得的数据资源。本在对比了ＭＯＤＩＳ与ＡＶＨＲＲ在数据接收、数据格式、数据处理、数据应用等方面的相同与不     

C^＊数据并行语言及其应用

Ｃ＊语言是通过对ＡＮＳＩＣ语言进行进行语法和语义的扩展得的支持ＳＩＭＤ模式的数据并行语言。它允许用户基于一个ＳＩＭＤ虚机描述数据在各个虚处理机上的分布以及对这些数据的并行计算操作，提供了一处简单，有效并与任何特定的机器无关的数据并行编程模型。介绍了Ｃ＊语言在超级计算机领域中的应用和Ｃ＊并行扩成分，并给出了典型的编程实例。     

分布存储并行机上的自动数据布局优化模型

在分布式并行机上,数据布局的质量极大的影响着应用程序的执行性能,以往的研究一般将自动数据布局优化问题近似分解为数据对准优化和数据分布优化两步来解决,且对两者的结合只研究了一维的情况,在相关研究工作的基础上,在多维情况下将数据对准优化和数据分布优化结合在一个模型当中,提出了一个数据对准优化与数据分布优化统一的多维静态数据布局模型,避免了采用启发式策略,从而更加精确地描述了自动数据布局优化问题,同时给     

The combining DAG: a technique for parallel data flow analysis

As the number of available multiprocessors increases, so does the importance of providing software support for these systems, including parallel compilers. Data flow analysis, an important component of software tools, may be computed many times during the compilation of a program, especially when compiling for a multiprocessor. Although converting a sequential data flow algorithm to a parallel algorithm can present some opportunities for computing data flow in parallel, more parallelism can be exposed by the development of new parallel data flow algorithms. We present a technique that computes rapid data flow problems in parallel and thus is applicable for commonly used classical data flow problems, including reaching definitions, reachable uses, available expressions, and very busy expressions. Unlike previous techniques, our technique exploits the inherent parallelism in the data flow computation that occurs across independent paths, within linear paths, and in paths through loops of a control flow graph. The technique first changes cyclic structures in a control flow graph to acyclic structures and then builds a combining directed acyclic graph (DAG) that represents the paths through the control flow graph needed to compute data flow. Data flow is then computed using two passes over the DAG by computing the data flow for the nodes on each level of the DAG in parallel. We also present experimental results comparing the performance of our algorithm with a sequential algorithm and a parallelized sequential algorithm     

Dynamic scheduling of a batch of parallel task jobs on heterogeneous clusters

This paper addresses the problem of minimizing the scheduling length (make-span) of a batch of jobs with different arrival times. A job is described by a direct acyclic graph (DAG) of parallel tasks. The paper proposes a dynamic scheduling method that adapts the schedule when new jobs are submitted and that may change the processors assigned to a job during its execution. The scheduling method is divided into a scheduling strategy and a scheduling algorithm. We also propose an adaptation of the Heterogeneous Earliest-Finish-Time (HEFT) algorithm, called here P-HEFT, to handle parallel tasks in heterogeneous clusters with good efficiency without compromising the makespan. The results of a comparison of this algorithm with another DAG scheduler using a simulation of several machine configurations and job types shows that P-HEFT gives a shorter makespan for a single DAG but scores worse for multiple DAGs. Finally, the results of the dynamic scheduling of a batch of jobs using the proposed scheduler method showed significant improvements for more heavily loaded machines when compared to the alternative resource reservation approach.     

并行数据库数据分布策略研究

数据分布是并行数据库系统实现的基础,其方法的优劣,直接影响到并行数据库的运行效率。通过对一维、多维几种数据分布方法的分析、对比,阐述并行数据库数据分布策略及方向。     

On the granularity and clustering of directed acyclic task graphs

The authors consider the impact of the granularity on scheduling task graphs. Scheduling consists of two parts, the processors assignment of tasks, also called clustering, and the ordering of tasks for execution in each processor. The authors introduce two types of clusterings: nonlinear and linear clusterings. A clustering is nonlinear if two parallel tasks are mapped in the same cluster otherwise it is linear. Linear clustering fully exploits the natural parallelism of a given directed acyclic task graph (DAG) while nonlinear clustering sequentializes independent tasks to reduce parallelism. The authors also introduce a new quantification of the granularity of a DAG and define a coarse grain DAG as the one whose granularity is greater than one. It is proved that every nonlinear clustering of a coarse grain DAG can be transformed into a linear clustering that has less or equal parallel time than the nonlinear one. This result is used to prove the optimality of some important linear clusterings used in parallel numerical computing     

A generic parallel processing model for facilitating data mining and integration

To facilitate data mining and integration (DMI) processes in a generic way, we investigate a parallel pipeline streaming model. We model a DMI task as a streaming data-flow graph: a directed acyclic graph (DAG) of Processing Elements (PEs). The composition mechanism links PEs via data streams, which may be in memory, buffered via disks or inter-computer data-flows. This makes it possible to build arbitrary DAGs with pipelining and both data and task parallelisms, which provide room for performance enhancement. We have applied this approach to a real DMI case in the life sciences and implemented a prototype. To demonstrate feasibility of the modelled DMI task and assess the efficiency of the prototype, we have also built a performance evaluation model. The experimental evaluation results show that a linear speedup has been achieved with the increase of the number of distributed computing nodes in this case study.     

面向并行应用程序的DAG模式复用技术

在并行应用程序设计中可以用有向无环图(DAG)表示子任务之间的依赖关系,从而实现子任务的调度。为此,针对DAG数据驱动模型中的DAG模式复用问题,提出插件式DAG模式图库。将DAG模式图模块和运行时系统模块分离,增强模块的复用性和扩展性。在Easy PDP系统中实现并扩展该模式图库。以棋盘问题为例,证明该技术可降低扩展系统所需的代价。     

成本约束的网格工作流时间优化方法

针对成本约束有向无环图DAG(directed acyclic graph)表示的网格工作流完工时间最小化问题,提出两个基于优先级规则的迭代启发算法.算法利用并行活动特征定义正向分层和逆向分层两个概念,将其分别引入最大收益规则MP(maximum profit),得到正分层最大收益规则MPTL(maximum profit with top level)和逆分层最大收益规则MPBL(maximum profit with bottom level).两规则每次迭代尽量以完工时间的最小增加换取总费用的最大降低,逐步将分层初始解构造为满足成本约束的可行解.模拟结果表明,两规则在获得较少迭代次数和运行时间的同时,能显著改进MP规则的平均性能,且MPBL优于MPTL.     

基于DAG图的自适应代码划分优化算法

并行编译的两大工作是程序代码划分和调度。对于调度问题，目前已有大量的解决方案，但是针对代码划分提取并行性的研究工作却非常少。该文提出了通过合并结点来划分DAG图的新的划分算法。实例分析证明，该算法是一种有效的、低复杂度的自适应代码划分解决方案，并且适用于异构计算的任务图划分。     

基于LFT和DAG方式的IPv6路由查找算法

随着网络的不断发展,路由表的信息量也在不断增加,这势必会影响路由转发的效率,影响网络速度.在分析了衡量路由算法优劣的标准后,又通过对现有IPv4和IPv6各种路由算法的分析,尤其是LFT和DAG结构的说明,综合了二者以及LC Trie的优点,提出了算法改进的思想,给出了算法的主要数据结构以及算法执行的流程图,此算法提高了路由查找效率.