面向对象有限元并行计算框架PANDA的多物理场耦合服务

针对结构分析软件面向多物理场的应用,分析讨论面向对象有限元并行计算框架PANDA的多物理场耦合服务设计,即多物理场分析类型的扩充能力、不同物理场间的数据传递和多物理场耦合分析的求解策略.在PANDA提供的多物理场耦合服务的基础上,开展热-力耦合分析功能的程序开发,实现热弹性分析功能.热弹性分析算例计算结果与ANSYS的...     

多物理场耦合软件GTEA开发及应用

围绕多物理场耦合问题,基于连续介质假设,采用非结构化网格和有限体积方法开发多物理场耦合并行计算软件GTEA。该软件包括计算流体力学、结构应力波传播、流 声耦合和声 固耦合等4个功能模块。介绍GTEA前处理网格读取、网格格式转换、求解器开发等关键技术。通过柴油机缸内工作过程模拟、船舶水动力计算、自然对流与辐射传热耦合作用、流场动力噪声计算和结构 声耦合计算等5个典型应用展示该软件的应用能力和适用范围。     

遍览ANSYS 8.0新功能与新产品

在新推出的ANSYS8.0中,不但增加了高端的CFD模块,增强了多物理场耦合技术,并且在多柔体动力学、非线性能力、计算流体动力学、电磁、优化、数据接口、并行计算、协同设计仿真以及智力资源整合与管理等个方面也有出色的表现,为各行各业的分析设计人员提供了更加全面、强大、完善的产品功能和最丰富的解决方案。     

多体问题在GPU上实现的讨论

多体问题(N-body)是力学的基本问题之一,研究N个质点互相作用的运动规律。结合分子动力学计算模拟软件LAMMPS和天体多体物理模拟软件Gadget-2这两个有广泛应用的多体并行计算软件,分析其基本算法和实现,讨论这两个有代表性的并行计算软件在GPU等加速部件上移植的基本思路。     

采用耦合器组件的区域冰—洋耦合模式的实现

采用耦合器组件形式的耦合技术现已成为数值模拟中不同模式物理过程间实现复杂相互作用的主流方法。以美国阿尔贡国家实验室（Argonne National Laboratory）开发的模式耦合工具包（MCT）为基础构建了耦合器组件,并利用其实现了海冰模式CSIM5与区域海洋环流模式ROMS3在北极地区的耦合。耦合模式以多任务多数据（MPMD）并行方式运行,在采用Linux系统和pgi编译器的高性能微机及银河集群计算机系统下已实现利用其开展冰—洋相互作用数值模拟研究的功能。     

基于网格的分布并行计算策略

网格计算为用户处理很多复杂问题提供了新方法,用网格实现大规模分布并行计算是必然的趋势。文章给出了基于网格中间件Globus Toolkit来实现分布并行计算的两种策略：紧密耦合并行程序和松散耦台并行服务,并给出实现这两种策略的实现方法,为实现分布并行计算提供了新方法。最后根据所提出的并行计算策略,在网格计算环境下实现了一个分布并行计算实例,并给出了相应的试验结果。     

多物理并行数值模拟中的两层紧耦合联接算法

复杂物理现象通常由多类复杂的物理过程紧耦合构成,其数值模拟也通常由适用不同物理过程的多类并行应用程序紧耦合完成．如何设计这些物理过程之间的联接算法,既要保证程序之间数据传递的高效,又要保证程序各自运行和总体模拟的高效,还要保证程序各自开发的独立,是一个值得研究的课题．该文基于广泛应用于高温高压多物理研究中的辐射流体力学和中子输运多物理并行数值模拟,在非结构网格上,提出了两种联接算法：完全松散联接算法和两层紧耦合联接算法,前者侧重于实现程序各自运行的高效和开发的独立,后者在前者的基础上,还权衡了数据传递和总体模拟的高效．在两台并行机的数百个处理机上,通信复杂度分析和数值实验结果表明两个算法均是有效的,可推广适用于辐射或中子输运与其他流体力学的多物理并行数值模拟应用中．特别地,两层紧耦合联接算法是高效可扩展的,取得了近似最优的并行性能．     

多物理数值模拟中一种有效的并行耦合方法

在实现多物理并行数值耦合模拟中,需要处理多个物理过程之间网格、并行区域分解的差异.针对该同题,该文基于三维流体力学与激光传播耦合的并行数值模拟,提出了一种实用的并行耦合方法:引入辅助状态将本地插值与通信相分离;构建并行耦合图并定义主导属性,以确定过程间传输的最小数据集合;提供并行数据重分配算法来完成通信.并行数值结果表明:该方法是有效的,在64台处理机上使整体程序获得50.07的加速比.     

基于NUMECA FINE/Turbo的并行计算测试

为具体了解CFD软件NUMECA FINE/Turbo的并行计算性能,良好把握后续的科研工作进度,分别研究在激活超线程情况下单节点计算与多节点并行计算以及CPU在激活超线程前、后计算速度的差异.结果表明:在多节点并行计算时,计算速度与实际参加并行计算的CPU物理核心数量成正比;在激活超线程的情况下,并行计算节点数在超过实际物理核心数后明显降低计算速度的提升.     

基于多核多线程的并行计算组件设计

随着四核微机走向市场和八十核处理器在实验室研制成功,多核正引领软件研发发生基础性变化。开发人员需要在代码中添加线程来利用系统所提供的多个内核,从而提升PC应用软件的功能和性能。本文探讨在多核微机上进行并行计算的实现技术,介绍基于基本线程类的多线程类的设计,包括属性、方法和事件的设计,着重探讨多个线程的同步核互斥问题。在基于多线程类的基础上,简要探讨VCL控件和ActiveX控件的实现方法。最后,展望了高性能并行计算软构件库的开发前景。     

Local and global models of physics and computation

Classical computation is essentially local in time, yet some formulations of physics are global in time. Here, I examine these differences and suggest that certain forms of unconventional computation are needed to model physical processes and complex systems. These include certain forms of analogue computing, massively parallel field computing and self-modifying computations.     

Using multiple levels of parallelism to enhance the performance of domain decomposition solvers

Large-scale scientific simulations are nowadays fully integrated in many scientific and industrial applications. Many of these simulations rely on modelisations based on PDEs that lead to the solution of huge linear or nonlinear systems of equations involving millions of unknowns. In that context, the use of large high performance computers in conjunction with advanced fully parallel and scalable numerical techniques is mandatory to efficiently tackle these problems.In this paper, we consider a parallel linear solver based on a domain decomposition approach. Its implementation naturally exploits two levels of parallelism, that offers the flexibility to combine the numerical and the parallel implementation scalabilities. The combination of the two levels of parallelism enables an optimal usage of the computing resource while preserving attractive numerical performance. Consequently, such a numerical technique appears as a promising candidate for intensive simulations on massively parallel platforms.The robustness and parallel numerical performance of the solver is investigated on large challenging linear systems arising from the finite element discretization in structural mechanics applications.     

YH-ACT：热工流体力学并行应用程序

商业CFD程序已广泛应用于反应堆的热工水力模拟,但不能完全满足反应堆的应用需求;开源CFD程序有部分应用,但与商业CFD程序相比,在物理模型全面性、计算精度、计算效率及易用性等方面仍存在差距。为更好地满足局部精细热工水力分析的需求,需要更全面的物理模型、较高的计算精度和较好的并行计算效率,因此有必要开发自主热工CFD程序。详细描述了热工流体力学并行应用程序YH-ACT的设计、实现方案以及测试结果。选取3个典型案例,通过与典型商业软件Fluent计算结果进行对比验证软件正确性, 程序并行计算规模达到400个结点共9 600个进程,稳态计算加速比为111.7,并行效率为27.9%,瞬态计算加速比为37.2,并行效率为9.3%。     

XpressSpace: a programming framework for coupling partitioned global address space simulation codes

Complex coupled multiphysics simulations are playing increasingly important roles in scientific and engineering applications such as fusion, combustion, and climate modeling. At the same time, extreme scales, increased levels of concurrency, and the advent of multicores are making programming of high‐end parallel computing systems on which these simulations run challenging. Although partitioned global address space (PGAS) languages attempt to address the problem by providing a shared memory abstraction for parallel processes within a single program, the PGAS model does not easily support data coupling across multiple heterogeneous programs, which is necessary for coupled multiphysics simulations. This paper explores how multiphysics‐coupled simulations can be supported by the PGAS programming model. Specifically, in this paper, we present the design and implementation of the XpressSpace programming system, which extends existing PGAS data sharing and data access models with a semantically specialized shared data space abstraction to enable data coupling across multiple independent PGAS executables. XpressSpace supports a global‐view style programming interface that is consistent with the PGAS memory model, and provides an efficient runtime system that can dynamically capture the data decomposition of global‐view data‐structures such as arrays, and enable fast exchange of these distributed data‐structures between coupled applications. In this paper, we also evaluate the performance and scalability of a prototype implementation of XpressSpace by using different coupling patterns extracted from real world multiphysics simulation scenarios, on the Jaguar Cray XT5 system at Oak Ridge National Laboratory. Copyright © 2013 John Wiley & Sons, Ltd.     

Practical aspects and experiences Scalable massively parallel algorithms for computational nanoelectronics

There is at present a worldwide effort to overcome the technological barriers to nanoelectronics. Microscopic simulation can significantly enhance our understanding of the physics of nanoscale structures, and constitutes a valuable tool for designing nanoelectronic functional devices. In nanodevices, novel physics effects are used to attain logic functionality which conventional technology can not achieve. Therefore it is necessary to develop quantum-transport simulation methods which include novel physical effects. Moreover, simulation of realistic nanodevices require enormous computing resource, necessitating parallel supercomputing. In this paper, we present massively parallel algorithms for simulating large-scale nanoelectronic networks based on the single-electron tunneling effect, which is arguably the quantum effect of greatest significance to nanoelectronic technology. A MIMD implementation of our simulation algorithm is carried out on a 64-processor nCUBE 2, and a SIMD implementation is carried out on a 16,384-processor MasPar MP-1. By exploiting massive parallelism, both parallel implementations achieve very high parallel efficiency and nearly linear scalability. The result of this work is that we are able to simulate large-scale nanoelectronic network, within a reasonable time period, which would be impractical on conventional workstations.     

有限差分离散模型分布并行计算支持库技术

本文研究实现了一个面向有限差分离散模型的分布并行计算支持库YHLIB。YHLIB库基于MPI消息传递接口设计实现,通过提供有限差分离散模型并行计算接口支持计算区域分解、域间通信、域内通信、循环下标转换、分布式I/O、动态负载平衡等功能,封装了并行计算实现细节,提高了并行程序开发效率。抽象模型实现和实际应用测试表明,YHLIB具有较高的并行效率。     

计算生物学中的高性能计算（Ⅰ）-分子动力学

分子动力学是高性能计算应用的重要领域,大量的高性能计算资源或机时被用于分子动力学模拟。描述了分子动力学的计算方法和特点,包括常用并行算法、性能改进方式等,介绍了常用的分子动力学大规模并行计算软件及其功能特性,最后展望了分子动力学模拟的发展与挑战。     

Accelerating geoscience and engineering system simulations on graphics hardware

Many complex natural systems studied in the geosciences are characterized by simple local-scale interactions that result in complex emergent behavior. Simulations of these systems, often implemented in parallel using standard central processing unit (CPU) clusters, may be better suited to parallel processing environments with large numbers of simple processors. Such an environment is found in graphics processing units (GPUs) on graphics cards.This paper discusses GPU implementations of three example applications from computational fluid dynamics, seismic wave propagation, and rock magnetism. These candidate applications involve important numerical modeling techniques, widely employed in physical system simulations, that are themselves examples of distinct computing classes identified as fundamental to scientific and engineering computing. The presented numerical methods (and respective computing classes they belong to) are: (1) a lattice-Boltzmann code for geofluid dynamics (structured grid class); (2) a spectral-finite-element code for seismic wave propagation simulations (sparse linear algebra class); and (3) a least-squares minimization code for interpreting magnetic force microscopy data (dense linear algebra class). Significant performance increases (between 10× and 30× in most cases) are seen in all three applications, demonstrating the power of GPU implementations for these types of simulations and, more generally, their associated computing classes.