基于MPI并行程序的容错系统设计

为了确保并行程序能够在并行环境下准确地运行,须提高系统的可靠性,将容错技术应用到并行计算中。该文针对MPI并行程序提出一种容错系统的设计方法,采用检查点/卷回恢复技术、并添加故障检测功能,能够有效地处理节点失效故障和进程失效故障,在一定范围内实现容错,为MPI环境下进行大规模计算提供一个可使用的应用模型。     

Petri网共享合成及其在并行系统中的应用

为了使Petri网技术能够应用于MPI并行程序的正确性和性能的验证,提出了Petri网共享合成运算构建MPI并行程序Petri网的算法。对分布式并行处理系统MPI并行程序的结构与消息传递过程进行分析,给出并行程序基本语句与传递函数的Petri网,将Petri网共享合成运算从两个Petri网的共享合成运算推广到并行程序的多个Petri网的共享合成运算,给出了推广定理和证明。提出了共享合成构建MPI并行程序Petri网的算法,并在消息传递并行系统中给出构建MPI并行程序Petri网的应用示例。实验结果表明,共享合成运算是构建MPI并行程序Petri网模型的一种有效方法。     

MPI程序设计简介

一、MPI简介 MPI是国际上通用的一种基于消息传递的并行程序设计运行环境。与PVM不同，MPI不是由少数厂商控制的私有程序，而是由国际组织MPI论坛（MPI Forum）维护的一种国际标准。像C语言一样，有许多厂商为其提供实现版本，比较著名的有LAM-MPI和MPICH等。MPI的实现版本往往包括两部分：程序库和运行环境。MPI并不是语言而是程序库，它可以和常见的程序设计语言如C，Fortran相结合而构成并行程序设计语言；运行环境可以看作是一个介于操作系统和MPI并行程序之间的中间件，为MPI程序运行提供支持。     

大规模结构有限元分析程序在多核集群计算环境中的性能分析和优化

通过对基于MPI编程模型实现的开源有限元计算分析软件在多核集群计算平台中的程序性能的分析,找出程序瓶颈及其原因,实现了基于MPI编程模型的并行程序在多核计算环境中的性能优化。根据程序性能瓶颈的分析,提出了基于MPI/OpenMP混合并行编程模型的大规模线性/非线性方程组求解和多线程多进程同时进行消息通信的两种程序性能优化方案。不同计算规模的实验结果表明,在多核集群计算平台中,MPI/OpenMP混合编程模型实现的大规模非线性方程组求解器相对于单纯基于MPI编程模型实现的并行程序,其性能有2倍到3倍的提升;多线程多进程同时消息传递的优化方案虽然对程序能够起到性能优化作用,但是对解决程序消息通信瓶颈的问题不是最好的方法。两个方案总体性能分析结果表明,基于MPI/OpenMP混合编程模型实现的并行程序,在多核集群计算平台中能够更好地发挥硬件系统的计算能力。     

基于MPI的Warshall算法实现及其优化

MPI并行编程方法是目前编程人员广泛使用的方法之一,但此方法将并行性开发的任务完全交给编程人员,程序的质量与效率往往与编程人员水平及风格不同而显示出不同的差异.本文基于MPI环境下把传统串行程序转变为并行程序从而提高其性能.此外通过MPI所提供的函数来进一步优化并行程序以便提高其性能.     

Windows环境下基于Eclipse的MPI编程环境配置

对当前并行程序开发工具存在的问题进行了分析。结合并行开发环境的迫切需求,给出了一种windows环境下,以开源项目Eclipse作为开发平台,以MinGW作为GUN的C/C＋＋编译器的MPI并行程序开发平台的搭建方法。并给出了该环境下的开发实例和测试。     

Windows环境下基于Eclipse的MPI编程环境配置

对当前并行程序开发工具存在的问题进行了分析.结合并行开发环境的迫切需求,给出了一种windows环境下,以开源项目Eclipse作为开发平台,以MinGW作为GUN的C/C 编译器的MPI并行程序开发平台的搭建方法.并给出了该环境下的开发实例和测试.     

XVM虚拟环境下并行程序的性能评测

该文引入speedup作为并行程序的性能评测指标,分析了并行程序在不同类型和不同数量的客户虚拟机中运行的性能差异,实验表明,MPI并行程序在xVM虚拟化环境中的运行性能接近非虚拟化本地主机的性能,在半虚拟化环境中的并行程序性能超过全虚拟化环境中的并行程序性能。     

基于Linux的MPI并行环境的配置

并行处理是一项重要的技术,简要介绍MPI的定义,详尽描述了在Linux环境下如何安装和配置MPI,搭建并行程序实现的软件平台,以达到多机并行计算,或者单机多进程模拟多机并行计算.     

COUPL+:并行PDE求解函数库

COUPL＋是一种基于消息传递模型的并行库,它将并行程序巾需要处理的数据划分、消息传递函数的调用等都封装在其函数中。COUPL＋可以简化在分布式存储结构并行机上编写基于网格的应用程序的任务。该文简要介绍了COUPL＋的基本原理,以及它与MPI、OpenMP和HPF的特性对比;并且使用COUPL＋实现了共轭梯度法和结构化网格计算两种并行计算中常用的任务,也对比了使用MPI和HPF的性能差异。     

基于代理的网格计算中间件

WADE系统是基于代理技术实现的一个可屏蔽异构和分布性的动态自适应的校园计算网格，提出了基于代理技术在校园网络内实现并行计算的方法，详细论述了基于代理的网格计算中间件的体系结构和主要模块功能，阐述了利用代理实现异构编译、协同计算的过程，给出了代理的Java实现方法，利用软件代理实现网格计算中间件，可以解决异构计算平台下多种并行编程环境的协同计算问题，为用户提供统一的服务接口，这将大大增强系统的可用性。     

Near real-time parallel processing and advanced data management of SAR images in grid environments

In this paper, we describe the process of parallelizing an existing, production level, sequential Synthetic Aperture Radar (SAR) processor based on the Range-Doppler algorithmic approach. We show how, taking into account the constraints imposed by the software architecture and related software engineering costs, it is still possible with a moderate programming effort to parallelize the software and present an message-passing interface (MPI) implementation whose speedup is about 8 on 9 processors, achieving near real-time processing of raw SAR data even on a moderately aged parallel platform. Moreover, we discuss a hybrid two-level parallelization approach that involves the use of both MPI and OpenMP. We also present GridStore, a novel data grid service to manage raw, focused and post-processed SAR data in a grid environment. Indeed, another aim of this work is to show how the processed data can be made available in a grid environment to a wide scientific community, through the adoption of a data grid service providing both metadata and data management functionalities. In this way, along with near real-time processing of SAR images, we provide a data grid-oriented system for data storing, publishing, management, etc.

Application execution management on the InteGrade opportunistic grid middleware

The InteGrade project is a multi-university effort to build a novel grid computing middleware based on the opportunistic use of resources belonging to user workstations. The InteGrade middleware currently enables the execution of sequential, bag-of-tasks, and parallel applications that follow the BSP or the MPI programming models.     

基于二维结构化网格的可压缩流体并行算法研究

基于二维/轴对称高精度可压缩多相流计算流体力学方法 MuSiC-CCASSIM的结构化网格部分,设计了区域并行分解方法;针对各处理器边界数据的通信,设计了阻塞式通信与非阻塞式通信并行算法;为了减少通信开销,设计了MPI/OpenMP混合并行优化算法。在天河二号超级计算机上进行了测试,每个核固定网格规模为625*250,最多调用8 192核。测试数据表明,采用MPI/OpenMP混合并行算法、纯MPI非阻塞式通信并行算法和纯MPI阻塞式通信并行算法的程序的平均并行效率分别达到86%、83%和77%,三种算法都具有良好的可扩展性。     

The design and implementation of Visuel performance monitoring and analysis toolkit for cluster and grid environments

The computing power provided by high performance and low-cost PC-based clusters with Grid platforms are attractive and they are equal or superior to supercomputers and mainframes. In this paper, we present implementation and design rationale of Visuel toolkit for MPI parallel program performance measurement and analysis in cluster and grid environments. Most of performance visualization tools available today for high-performance platforms show solely system performance data (e.g., CPU load, memory usage, network bandwidth, server average load), and thus, being suitable for computing system activity visualization. The Visuel (Visuel (in French language) = to visualize) toolkit is web-based interface designed to show performance activities of all computing nodes of a distributed environment involved in the execution of MPI parallel program, such as CPU load level and memory usage of each computing node. In addition, this toolkit is able to display comparative performance data charts of MPI parallel applications and multiple executions under investigation. The usage of this toolkit shows that it outperforms in easing the process of investigation of parallel applications.

OilCL:一个面向油藏数值模拟并行计算的通信库

ＯｉｌＣＬ是一个用于油藏数值模拟计算的可移植的通信库,虽然目前存在很多的通信库,如ＭＰＩ,ＰＶＭ等,但由于它们的通用性,而且其界面较低级而不适合油藏模拟数值计算,ＯｉｌＣＬ为油藏数值模拟计算程序员提供一个方便、自然的界面,它支持动态地建立和释放通信上下文／逻辑进程网格;支持基于源的消息选择;逻辑拓扑作为群通信子程序的参数并提供开发和运行模式,这些机制便于油藏数值模拟计算程序的设计,使程序可读性更强     

基于国产众核处理器三维地震声波正演模拟

三维地震声波理论与计算方法是地质勘探研究的基础,通过分析不同介质中声波的传播特性,完成三维地震声波正演模拟。针对三维地震声波有限差分交错网格方程正演过程中存在数值计算大、内存消耗大等实际问题,提出了基于神威·太湖之光超级计算机系统中国产异构众核处理器(申威26010)的三维地震声波正演模拟编程模型,完成了基于处理器间的进程级并行基于计算核心间的线程级并行优化策略。研究了DMA(直接内存读取)通信方式,提出2.5D流水线任务划分、通信与计算的相互掩盖的多角度优化策略。实验结果表明,该策略有效缓解了带宽瓶颈,发挥了处理器强大的计算能力,解决了程序在申威26010异构众核处理器处理有限差分问题时,并行效率过低的问题。在大规模测试下,使用266240个计算核心,程序仍能够保持稳定的计算性能,达到5.5 GFlops的场值更新。     

Gauss: A Framework for Verifying Scientific Computing Software

High performance scientific computing software is of critical international importance as it supports scientific explorations and engineering. Software development in this area is highly challenging owing to the use of parallel/distributed programming methods and complex communication and synchronization libraries. There is very little use of formal methods to debug software in this area, given that the scientific computing community and the formal methods community have not traditionally worked together. The Utah Gauss project combines expertise from scientific computing and formal methods in addressing this problem. We currently focus on MPI programs which are the kind that run on over 60% of world's supercomputers. These are programs written in C / C++ / FORTRAN employing message passing concurrency supported by the Message Passing Interface (MPI) library. Large-scale MPI programs also employ shared memory threads to manage concurrency within smaller task sub-groups, capitalizing on the recent availability of small-scale (e.g. single-chip) shared memory multiprocessors; such mixed programming styles can result in additional bugs. MPI libraries themselves can be buggy as they strive to implement complex requirements employing aggressive techniques such as multi-threading. We have built a model extractor that extracts from MPI C programs a formal model consisting of communicating processes represented in Microsoft's Zing modeling language. MPI library functions are also being modeled in Zing. This allows us to run formal analysis on the models to detect bugs in the MPI programs being analyzed. Our preliminary results and future plans are described; in addition, our contribution is to expose the special needs of this area and suggest specific avenues for problem- driven advances in software model-checking applied to scientific computing software development and verification.     

A framework for adaptive collective communications for heterogeneous hierarchical computing systems

Collective communication operations are widely used in MPI applications and play an important role in their performance. However, the network heterogeneity inherent to grid environments represent a great challenge to develop efficient high performance computing applications. In this work we propose a generic framework based on communication models and adaptive techniques for dealing with collective communication patterns on grid platforms. Toward this goal, we address the hierarchical organization of the grid, selecting the most efficient communication algorithms at each network level. Our framework is also adaptive to grid load dynamics since it considers transient network characteristics for dividing the nodes into clusters. Our experiments with the broadcast operation on a real-grid setup indicate that an adaptive framework allows significant performance improvements on MPI collective communications.     

海洋模式FVCOM2.6并行计算性能TAU分析

本文利用并行程序分析软件Tuning and Analysis Utilities(TAU),对基于Message Passing Interface(MPI)的海洋环流模式Finite-Volume Coastal Ocean Model(FVCOM)2.6版本进行并行性能分析。在Linux集群(Intel Xeon CPU E5450,10GInfiniBand)上,使用不同进程数分别对低分辨率(网格节点数为2108和10378)、高分辨率(网格节点数为15347和26033)的深沪湾潮汐算例进行测试。结果表明,模式单进程运行时,平流项子程序所占运行时间比例较大;模式多进程运行时,通过比较不同算例的加速比,发现算例分辨率对模式的并行性能有较大影响。在本次测试硬件条件下,算例存在某一最佳进程数,低分辨率为32,高分辨率为64,最佳进程数随分辨率增高而增高。到达最佳进程数后,随着进程数增加,模式运行时间反而增加。TAU分析表明,主要是由于MPI_Waitany程序时间比例增加以致阻塞时间占模式运算总时间的比例增大,从而为FVCOM并行性能进一步改善提供参考。