扩展双精度浮点并行计算:MPI方法

双精度浮点并行计算将不能满足高性能计算领域对计算精度的要求,但是目前还没有高性能的超双精度并行计算的解决方法。基于并行编程语言MPI,本文提出了扩展双精度浮点的并行计算实现方法,并且使用精度敏感的圆周率计算BBP算法验证了该方法的正确性和性能。     

并行程序设计模型和语言

并行计算技术的发展已有20多年的历史了.时至今日,高性能并行计算仍然缺乏有效的并行程序设计方法和工具,使得编写并行程序、理解并行程序的行为、调试和优化并行程序的性能都很困难.从分析并行程序设计困难的原因入手,指出了当前各种高性能并行机系统支持的并行程序设计方法存在的诸多问题,综述了并行程序设计模型和语言的研究现状,给出了并行程序设计模型的评价标准,并提出了这一研究领域所面临的挑战性问题,指出了一些未来可能的发展方向.     

CPU/GPU协同并行计算研究综述

CPU/GPU异构混合并行系统以其强劲计算能力、高性价比和低能耗等特点成为新型高性能计算平台,但其复杂体系结构为并行计算研究提出了巨大挑战。CPU/GPU协同并行计算属于新兴研究领域,是一个开放的课题。根据所用计算资源的规模将CPU/GPU协同并行计算研究划分为三类,尔后从立项依据、研究内容和研究方法等方面重点介绍了几个混合计算项目,并指出了可进一步研究的方向,以期为领域科学家进行协同并行计算研究提供一定参考。     

高性能并行仿真中程序与平台之间的适用性研究

开发高性能仿真程序的前提是选择合适的并行计算平台以及明确程序的并行优化方向。为此,研究了并行计算平台和高性能仿真程序之间的适用性。重点提炼出仿真程序特性集合、并行计算平台的性能指标体系和并行优化目标要素集合,从而使平台选择和程序优化技术有更完善的理论指导。基于这三项研究,提出了确定程序适用性和平台适用性的方法。实例分析表明,研究成果能够指导选择适合的并行计算平台,以及指导开发面向平台性能的并行优化技术。     

高性能计算机并行计算环境的构建及使用效能情况

介绍了对高性能计算机进行并行计算时所必需的基本环境构建情况,包括ssh配置、编译器f90安装及设置、并行mpi软件配置等,还进行了高性能并行计算环境下的应用试验,如对气象并行软件grpaes进行了编译,并在指定相关节点的情况下实现了高性能运行计算。最后通过对高性能计算机进行并行效率试验,找出同样计算规模的grapes模式进行并行计算时所应使用的最佳节点数。     

基于Cart3D的全机数值模拟及并行计算

利用CFD商用软件Cart3D对亚声速飞行飞机的三维绕流流场进行了数值模拟以及并行计算,得到了飞机附近的流场,实现了此软件在高性能并行计算机上的并行;通过对比不同商用软件的计算结果,验证了用Cart3D软件进行数值模拟的有效性,为大规模科学工程计算提供了技术参照。     

基于Fluent的全机数值模拟及并行计算

利用CFD商用软件Fluent对亚声速飞行飞机的三维绕流流场进行了数值模拟以及并行计算，得到了飞机附近的流场，实现了此软件在高性能并行计算机上的并行；并且通过对不同数量网格在不同结点数目机群上的计算结果进行分析比较，验证了此商用软件在并行平台上应用的有效性，也为进行大规模科学工程计算提供了技术参照。     

基于网格的并行FFT计算研究

快速傅里叶变换（FFT）在科学和工程领域有着广泛的应用。在网格环境下进行并行FFT计算可以提高运算速度,促进FFT的应用。在介绍了网格计算发展状况的基础上,详细阐述了基于网格的分布式并行计算。实验以FFT算法为背景,在Globus Toolkit 4平台下实现了并行FFT计算,并对实验数据作了分析,说明了基于网格的并行FFT计算的可行性。最后指出网格资源调度对并行计算的重要性。     

高性能并行计算在航空航天CFD数值模拟中的应用

本文介绍了高性能并行计算在CFD数值模拟中的应用。CFD高性能并行计算可扩大求解规模,加快求解速度,是CFD实现高效计算的必然发展趋势。本文通过"数值风洞"的概念分析了CFD高性能计算的应用前景及对高性能计算的需求。通过某乘波飞行器前体并行算例对8～256CPU的CFD大规模并行效率和加速比进行了分析,并将CFD并行计算应用于高温热化学非平衡的返回舱数值计算中。     

基于网格的并行FFT计算研究

快速傅里叶变换(FFT)在科学和工程领域有着广泛的应用.在网格环境下进行并行FFT计算可以提高运算速度,促进FFT的应用.在介绍了网格计算发展状况的基础上,详细阐述了基于网格的分布式并行计算.实验以FFT算法为背景,在Globus Toolkit 4平台下实现了并行FFT计算,并对实验数据作了分析,说明了基于网格的并行FFT计算的可行性.最后指出网格资源调度对并行计算的重要性.     

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.     

High-level abstractions for message-passing parallel programming

Large-scale scientific and engineering computation problems are usually complex and consequently the development of parallel programs for solving these problems is a difficult task. In this paper, we describe the graph-oriented programming (GOP) model and environment for building and evaluating parallel applications. The GOP model provides higher level abstractions for message-passing parallel programming and the software environment offers tools which can ease programmers for parallelizing, writing, and deploying scientific and engineering computing applications. We discuss the motivations and various issues in developing the model and the software environment, present the design of the system architecture and the components, and describe the evaluation of the environment implemented on top of MPI with a sample parallel scientific application program. With the support of the high-level abstractions provided by the proposed GOP environment, programming of parallel applications on various parallel architectures can be greatly simplified.     

商业软件的并行网格计算平台模型及实现

以ANSYS和FLUENT为例,分析了商业软件在工作站机群并行运行的优势.将并行运行与网格计算相结合,提出了两者结合的软件结构和硬件结构,实现了并行计算资源的Web发布,从而提高商业软件和高性能计算资源的利用率,为大规模科学工程计算提供了良好的运算平台.同时平台实现用户认证,过载保护和实时监控功能.     

A general purpose real-world structural design optimization computing platform

Structural optimization has matured from a narrow academic discipline, where researchers focused on optimum design of small idealized structural components and systems, to become the basis in modern design of complex structural systems. Some software applications in recent years have made these tools accessible to professional engineers, decision-makers and students outside the structural optimization research community. These software applications, mainly focused on aerospace, aeronautical, mechanical and naval structural systems, have incorporated the optimization component as an additional feature of the finite element software package. On the other hand though there is not a holistic optimization approach in terms of final design stage for real-world civil engineering structures such as buildings, bridges or more complex civil engineering structures. The optimization computing platform presented in this study is a generic real-world optimum design computing platform for civil structural systems and it is implemented within an innovative computing framework, founded on the current state of the art in topics like metaheuristic optimization, structural analysis and parallel computing. For demonstration purposes the application of the optimization computing platform in five real-world design projects is presented.     

工作站网络环境下的并行计算

当前工作站网络环境（ＮＯＷｓ）下高性能科学与工程计算是并行计算的一个热门话题，本文借助于ＬｏｇＰ并行计算模型，提出了一套新的效率评价准则，用于优化并行算法效率以达到最佳实现效果，揭示了影响算法并行效率发挥的关键因素，并从算法和程序设计角度提出了相应措施，探讨了急需解决的几个关键性问题，三个典型应用问题的数值实验结果文中给出。     

SGI Origin2000上的并行计算的初步探讨——MPI方法

高性能计算机技术是现代科学技术研究、工程技术开发和大规模数据处理的基础。利用高性能计算机可以解决一些仅仅依靠理论及实验方法无法解决的问题。分析处理靠传统技术无法应付的海量数据。其中,并行计算技术是实现高性能计算的重要技术途径。本文主要讨论在SGIOrigin2000上使用MPI方法进行并行计算,并以Jacobi迭代程序为例,说明如何半将串行程序转换成并行程序。     

基于多类网络模型的AI芯片测评方法研究

随着AI芯片制程不断升级以及结构设计不断优化,AI芯片在并行计算能力和泛化能力等方面展现出明显的优势,这些优势使得AI芯片在宇航领域得到越来越多的关注和应用。与传统的质量保证方法不同,AI芯片测评作为一项新的重要环节,对于AI芯片的选型和使用具有重要意义。本文针对面向宇航应用的AI芯片,研究了一种宇航用AI芯片的测评方法,该方法可以测评出AI芯片的精度、算力、功耗和量化支持能力,并基于该方法对AI芯片的性能和功能性指标进行了详细的分析和评价,最后针对宇航用AI芯片测评方法的进一步研究方向提出了相关建议。