EPIC微体系结构的存储级并行执行模型的研究

描述了一种可以有效提高存储级并行(Memory Level Parallelism,MIP)的指令优化锁步执行模型--OLSM(Optimized Lock-Step execution Model)执行模型,并建立了一种能体现OLSM模型思想的层次存储结构.OLSM允许显示并行指令计算(Explicit Parallel Instruction Computmg,EPIC)微处理器实现一定程度的乱序执行,解决了传统超长指令字(Very Long Instruction Word,VLIW)锁步执行的缺陷,可以充分利用结构中的大量计算和存储资源,最大化隐藏存储延迟、提高MLP.     

Exploiting Linked Data to Build Web Applications

Semantic Web technologies have been around for a while. However, such technologies have had little impact on the development of real-world Web applications to date. With linked data, this situation has changed dramatically in the past few months. This article shows how linked data sets can be exploited to build rich Web applications with little effort.     

Exploiting Distributed-Memory and Shared-Memory Parallelism on Clusters of SMPs with Data Parallel Programs

Clusters of SMPs are hybrid-parallel architectures that combine the main concepts of distributed-memory and shared-memory parallel machines. Although SMP clusters are widely used in the high performance computing community, there exists no single programming paradigm that allows exploiting the hierarchical structure of these machines. Most parallel applications deployed on SMP clusters are based on MPI, the standard API for distributed-memory parallel programming, and thus may miss a number of optimization opportunities offered by the shared memory available within SMP nodes. In this paper we present extensions to the data parallel programming language HPF and associated compilation techniques for optimizing HPF programs on clusters of SMPs. The proposed extensions enable programmers to control key aspects of distributed-memory and shared-memory parallelization at a high-level of abstraction. Based on these language extensions, a compiler can adopt a hybrid parallelization strategy which closely reflects the hierarchical structure of SMP clusters by automatically exploiting shared-memory parallelism based on OpenMP within cluster nodes and distributed-memory parallelism utilizing MPI across nodes. We describe the implementation of these features in the VFC compiler and present experimental results which show the effectiveness of these techniques.     

海量数据处理中的网格技术应用

网格是继Internet和Web之后第三次信息技术革命,最终将改变分布式资源的共享和服务方式。该文主要讨论了海量数据的产生、存储、处理,以及其对数据网格技术的需求,分析了欧洲数据网格和LHC计算网格的功能,并探讨了网格技术研究的最新情况。     

Metadata for Managing Grid Resources in Data Mining Applications

The Grid is an infrastructure for resource sharing and coordinated use of those resources in dynamic heterogeneous distributed environments. The effective use of a Grid requires the definition of metadata for managing the heterogeneity of involved resources that include computers, data, network facilities, and software tools provided by different organizations. Metadata management becomes a key issue when complex applications, such as data-intensive simulations and data mining applications, are executed on a Grid. This paper discusses metadata models for heterogeneous resource management in Grid-based data mining applications. In particular, it discusses how resources are represented and managed in the Knowledge Grid, a framework for Grid-enabled distributed data mining. The paper illustrates how XML-based metadata is used to describe data mining tools, data sources, mining models, and execution plans, and how metadata is used for the design and execution of distributed knowledge discovery applications on Grids.     

Exploiting Workload Parallelism for Performance and Power Optimization in Blue Gene

Optimizing future supercomputing applications will depend on delivering the best performance for a given power budget. To determine the effect on efficiency of application-scaling parameters, this article analyzes system power and performance measurement results for real-world applications exploiting thread- and data-level parallelism on the Blue Gene/L system     

数据并行语言中的任务并行

数据并行虽然已经获得了广泛的应用,但是,仍然有一些应用程序不适于数据并行语言的并行模式,如树结构算法。数据并行与任务并行的结合可以很好地解决这些问题。该文主要讨论了在数据并行中引入任务并行时,遇到的共享变量、代码生成和处理器分配等问题,比较和分析了基于编译、基于语言和基于协作库的方法。     

数据并行应用的基于伪机群的网格资源选择

为给数据并行应用选择适合的网格资源,文章给出一个伪机群的想法。非专用机群中的主机可根据资源性能偏差率构造出若干伪机群,使同一个伪机群中的资源性能彼此相近。专用机群也可被视为伪机群,故对于任何类型的应用,伪机群思想使网格资源彼此有了可比性。实验表明,拥有最高整体性能的伪机群将使应用取得最短的运行时间。     

User Interaction and Data Management for Large Scale Grid Applications

In this paper we present a model that combines the X3DMMS application with the G3CPie execution framework, that enables the user to perform large scale computations on distributed computing environments. Such an approach facilitates the management and the preparation of the data required to define the input files for DL_POLY, a popular Molecular Dynamics (MD) package used for the study of molecular systems. The researcher can define in a intuitive way the initial configuration of the molecular system, making use of the X3DMMS virtual reality environment, and prepares the related MD package oriented input files. After having defined the initial conditions of the system, the researcher can carry out the required computations by using the G3CPie workflow environment, which controls the execution of the calculation on a distributed computing infrastructure. To test the validity of the developed model, implemented in the EGI infrastructure, we present the results carried out for a propane bulk system, where the solvation process of propane inside the bulk has been investigated. The presented approach provides a reusable example for other laboratories or groups interested both in acting through virtual representation of the molecular systems and porting their applications to distributed computing infrastructures.     

Workflow-Based Data Parallel Applications on the EGEE Production Grid Infrastructure

Setting up and deploying complex applications on a Grid infrastructure is still challenging and the programming models are rapidly evolving. Efficiently exploiting Grid parallelism is often not straight forward. In this paper, we report on the techniques used for deploying applications on the EGEE production Grid through four experiments coming from completely different scientific areas: nuclear fusion, astrophysics and medical imaging. These applications have in common the need for manipulating huge amounts of data and all are computationally intensive. All the cases studied show that the deployment of data intensive applications require the development of more or less elaborated application-level workload management systems on top of the gLite middleware to efficiently exploit the EGEE Grid resources. In particular, the adoption of high level workflow management systems eases the integration of large scale applications while exploiting Grid parallelism transparently. Different approaches for scientific workflow management are discussed. The MOTEUR workflow manager strategy to efficiently deal with complex data flows is more particularly detailed. Without requiring specific application development, it leads to very significant speed-ups.     

基于XML的非结构化文本数据转换研究与实现

采用XML作为存储数据的中间过程,通过两次调用Java程序,使非结构化的数据结构化因为XML作为一种半结构化的语言,适合数据存储与数据转换 而Java程序可以让基于XML的非结构化数据转换成结构化的数据,使其完全的结构化.使用该Java程序,可以完成类似的非结构化数据的转换工作.     

The Cell Broadband Engine: Exploiting Multiple Levels of Parallelism in a Chip Multiprocessor

As CMOS feature sizes continue to shrink and traditional microarchitectural methods for delivering high performance (e.g., deep pipelining) become too expensive and power-hungry, chip multiprocessors (CMPs) become an exciting new direction by which system designers can deliver increased performance. Exploiting parallelism in such designs is the key to high performance, and we find that parallelism must be exploited at multiple levels of the system: the thread-level parallelism that has become popular in many designs fails to exploit all the levels of available parallelism in many workloads for CMP systems. We describe the Cell Broadband Engine and the multiple levels at which its architecture exploits parallelism: data-level, instruction-level, thread-level, memory-level, and compute-transfer parallelism. By taking advantage of opportunities at all levels of the system, this CMP revolutionizes parallel architectures to deliver previously unattained levels of single chip performance. We describe how the heterogeneous cores allow to achieve this performance by parallelizing and offloading computation intensive application code onto the Synergistic Processor Element (SPE) cores using a heterogeneous thread model with SPEs. We also give an example of scheduling code to be memory latency tolerant using software pipelining techniques in the SPE. This paper is based in part on “Chip multiprocessing and the Cell Broadband Engine”, ACM Computing Frontiers 2006.     

一种数据并行中的群通信优化策略

群通信是影响大规模数据并行系统效率的关键因素,其主要发生在程序不同阶段间的数组重分布与循环划分后的数组重映射这两种情况.在一次通信中显著影响群通信效率常被忽视的因素是消息冲突和消息长度的不一致.因为它们会导致进程间大量的空闲等待时间.然而以前的研究要么不能完全避免消息冲突,要么针对某些特殊情况.对此,提出了在数组分布为Block_Cyclic(k)情况下的一种更具有普遍适用性的通信调度策略CSS.通过证明表明该策略能使一个通信步内的消息互不冲突且消息长度尽量相等.从而最小化通信调度生成时间和实际通信时间.最后的测试结果也表明,与传统的通信优化算法和MPI_Alltoallv实现相比,CSS策略使得通信效率得以明显提高.     

Application of Multiblock Grid and Dual-Level Parallelism in Coastal Ocean Circulation Modeling

Numerical grid generation techniques play an important role in the numerical solution of partial differential equations on arbitrarily shaped regions. For coastal ocean modeling, in particular, a one-block grid covering the region under study is commonly used. Most bodies of water of interest have complicated coastlines; e.g., the Persian Gulf and Mediterranean Sea. Since such one-block grids are not boundary conforming, the number of unused grid points can be a relatively large portion of the entire domain space. Other disadvantages of using a one block grid include large memory requirements and long computer processing time. Multiblock grid generation and dual-level parallel techniques are used to overcome these problems. Message Passing Interface (MPI) is used to parallelize the Multiblock Grid Princeton Ocean Model (MGPOM) such that each grid block is assigned to a unique processor. Since not all grid blocks are of the same size, the workload varies between MPI processes. To alleviate this, OpenMP dynamic threading is used to improve load balance. Performance results from the MGPOM model on a one-block grid, a twenty block grid, and a forty-two block grid after a 90-day simulation for the Persian Gulf demonstrate the efficacy of the dual-level parallel code version.     

Exploiting Temporal Relations in Mining Hepatitis Data

Various data mining methods have been developed last few years for hepatitis study using a large temporal and relational database given to the research community. In this work we introduce a novel temporal abstraction method to this study by detecting and exploiting temporal patterns and relations between events in viral hepatitis such as “event A slightly happened before event B and B simultaneously ended with event C”. We developed algorithms to first detect significant temporal patterns in temporal sequences and then to identify temporal relations between these temporal patterns. Many findings by data mining methods applied to transactions/graphs of temporal relations shown to be significant by physician evaluation and matching with published in Medline.     

Secure Data Objects Replication in Data Grid

Secret sharing and erasure coding-based approaches have been used in distributed storage systems to ensure the confidentiality, integrity, and availability of critical information. To achieve performance goals in data accesses, these data fragmentation approaches can be combined with dynamic replication. In this paper, we consider data partitioning (both secret sharing and erasure coding) and dynamic replication in data grids, in which security and data access performance are critical issues. More specifically, we investigate the problem of optimal allocation of sensitive data objects that are partitioned by using secret sharing scheme or erasure coding scheme and/or replicated. The grid topology we consider consists of two layers. In the upper layer, multiple clusters form a network topology that can be represented by a general graph. The topology within each cluster is represented by a tree graph. We decompose the share replica allocation problem into two subproblems: the Optimal Intercluster Resident Set Problem (OIRSP) that determines which clusters need share replicas and the Optimal Intracluster Share Allocation Problem (OISAP) that determines the number of share replicas needed in a cluster and their placements. We develop two heuristic algorithms for the two subproblems. Experimental studies show that the heuristic algorithms achieve good performance in reducing communication cost and are close to optimal solutions.     

网格环境下的数据存储

数据存储可以使利用不同存储环境的用户有效地访问数据。本文对网格环境下的主要存储技术进行了介绍。讨论了在本地和远程存储数据时,存储方法要考虑的问题;数据存储的基本传输和存储单元及存储模式。     

网格环境下的数据存储

数据存储可以使利用不同存储环境的用户有效地访问数据。本文对网格环境下的主要存储技术进行了介绍。讨论了在本地和远程存储数据时，存储方法要考虑的问题；数据存储的基本传输和存储单元及存储模式。     

数据网格中数据交互处理模式研究

作为业界的研究新热点——网格技术,随着其应用领域的拓展,其具体的应用网格也由单纯的计算网格发展到数据网格、拾遗网格、信息服务网格等应用重点不同的具体应用网格。该文简单探讨了数据网格的体系结构及应用场景,并着重对在数据网格中所出现的不同数据交互处理模式进行了探讨。针对其应用条件和场合的不同,将数据网格中的数据交互处理模式分为三大类六个不同的处理模式,对每种模式的具体工作机制进行了探讨,并给出了一定的应用描述。