A new hybrid solver with two‐level parallel computing for large‐scale structural analysis

With the advancement of new processor and memory architectures, supercomputers of multicore and multinode architectures have become general tools for large‐scale engineering and scientific simulations. However, the nonuniform latencies between intranode and internode communications on these machines introduce new challenges that need to be addressed in order to achieve optimal performance. In this paper, a novel hybrid solver that is especially designed for supercomputers of multicore and multinode architectures is proposed. The new hybrid solver is characterized by its two‐level parallel computing approach on the basis of the strategies of two‐level partitioning and two‐level condensation. It distinguishes intranode and internode communications to minimize the communication overheads. Moreover, it further reduces the size of interface equation system to improve its convergence rate. Three numerical experiments of structural linear static analysis were conducted on DAWNING‐5000A supercomputer to demonstrate the validity and efficiency of the proposed method. Test results show that the proposed approach was superior in performance compared with the conventional Schur complement method. Copyright © 2014 John Wiley & Sons, Ltd.     

HSWAP:适用于高性能计算环境的数值模拟工作流管理平台

针对高性能计算（HPC）环境中的"建模、计算、分析、优化"一体化应用构建的问题，设计了支持数值模拟软件封装和数值模拟工作流交互设计的数值模拟工作流管理平台——HSWAP。首先，基于对数值模拟活动的运行特征共性建模构建组件模型；然后，利用工作流表达数值模拟活动间的控制、数据依赖关系，建立形式化的数值模拟工作流模型，所形成的工作流模型可在平台中自动解析并适配高性能计算资源，从而实现批量关联数值模拟任务的自动生成与调度，为领域用户屏蔽高性能计算资源的使用细节。平台提供Web Portal服务，支持图形数值模拟程序的交互界面推送。目前该平台已在超算中心实际生产环境得到部署应用，可在2人月内完成包含10个以下数值模拟软件、20个以内计算任务节点的数值模拟工作流的集成。     

基于并行计算的大规模群体行为建模与仿真方法研究

为解决当前群体行为模型因规模扩大而导致计算量剧增的问题,采用并行离散事件方法构建了大规模群体行为模型,利用YH-SUPE仿真引擎实现了群体行为模型的并行计算。重点介绍了模型中仿真对象和仿真对象信息交互的设计方法,并对该模型在不同数量的节点和仿真实体的环境下进行了测试。实验结果表明,将并行计算引入群体行为建模之中,可以显著提高仿真个体的数量,更加有效地支持了群体模型的实时运行。     

大规模3D并行分层可扩展矩阵乘法的递阶优化方法

为进一步提高大规模平台上可扩展矩阵乘法的并行计算效率,提出一种并行分层可扩展矩阵乘法的递阶优化方法。首先,在可扩展矩阵乘法算法(SMM)算法枢轴行和枢轴列通信研究基础上,利用分层方式在更高等级上对网格进行矩形群划分,实现矩阵乘法的二维计算向三维计算转变,并设计对应的集群内通信和集群间通信过程,实现SMM乘法的递阶并行优化(HSMM);其次,对所提HSMM算法进行理论分析,分情况对其通信成本进行分析和预测,推导出最佳计算成本的集群数选取方式;最后,通过在Grid5000和BlueGene/P测试平台实验,验证了所提算法有效性和理论分析的正确性。     

海洋物质输运模拟中并行计算的应用比较研究

为了找到一种更高效的并行计算方法以提高海洋物质输运模拟速度,将适用于分布式存储环境的消息传递接口(message passing interface,MPI)与适用于共享存储环境的开放式多处理(open multiple processing,OpenMP)两种海洋数值模拟领域常用的并行计算技术分别应用于模拟海洋物质输运过程,并在多核心(chip muti-processors)集群系统上进行了对比实验研究.实验结果表明,与串行模拟方法相比MPI和OpenMP分别可以使计算速度提高6倍和4.2倍,在海洋物质输运模拟并行计算中MPI的加速效果明显优于OpenMP.     

A stable time advancing scheme for solving fluid-structure interaction problem at small structural displacements

A semi-implicit time advancing scheme for transient fluid-structure interaction problem is presented. At every time step, a least squares problem is solved by partitioned procedures, such that the continuity of the velocity as well as the continuity of the stress hold at the interface. During the iterative method for solving the optimization problem, the fluid mesh does not move, which reduces the computational effort. The stability of the algorithm is derived. The numerical results presented in this paper show that the computed solution is similar to the one obtained by the implicit algorithm, but the computational time is reduced.     

大规模流场模拟中壁面距离的并行计算方法研究

采用MPI多进程和Open MP多线程两级并行相结合的方式,实现了循环盒子法的并行计算,并对其预处理算法进行了改进。在国家超算广州中心的"天河-2"系统上,完成了对亿级网格量的超燃冲压发动机燃烧室算例的测试。结果分析表明,进程盒子法和边界盒子法不存在盒子切割数的选择问题,边界盒子法较其他算法具有更好的加速比,可显著提高壁面距离的计算效率。     

CPU-GPU协同计算的遥感仿真图像MTF退化并行算法

在遥感图像仿真中,为了定量模拟并分析平台抖动、探测器电子特性、大气衰减等因素对遥感成像质量的影响,需要有效计算遥感系统的调制传递函数MTF,并将其快速作用到仿真图像上。然而,由于遥感仿真图像的大数据量特性以及MTF退化包含多个计算密集型算法,使得计算效率成为一个瓶颈问题。为此,根据已有研究提出的MTF计算模型,分析了遥感仿真图像MTF退化的一般流程及主要环节的算法复杂度。在此基础上,提出了一种CPU-GPU协同计算的遥感仿真图像MTF退化并行算法。实验结果表明,该并行算法有效地发挥了GPU并行计算能力,并明显提高了MTF退化处理效率。     

A novel approach to generate a large scale of supervised data for short text sentiment analysis

Multimedia Tools and Applications - As for the complexity of language structure, the semantic structure, and the relative scarcity of labeled data and context information, sentiment analysis has...     

A geometric process repair model for a two-component system with shock damage interaction

In this article, the repair-replacement problem for a two-component system with shock damage interaction and one repairman is studied. Assume that component 1 will be replaced as soon as it fails, and each failure of component 1 will induce a random shock to component 2. The shock damages may be accumulative, and whenever the total shock damage equals or exceeds a given threshold Δ, component 2 fails and the system breaks down. Component 2 is repairable, and it follows a geometric process repair. Under these assumptions, we consider a replacement policy N based on the number of failures of component 2. Our problem is to determine an optimal replacement policy N* such that the average cost rate (i.e. the long-run average cost per unit time) is minimised. The explicit expression of the average cost rate is derived by the renewal reward theorem, and the optimal replacement policy can be determined analytically or numerically. The existence and uniqueness of the optimal replacement policy N* is also proved under some mild conditions. Finally, two appropriate numerical examples are provided to show the effectiveness and applicability of the theoretic results in this article.     

A coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing

Refined models and nonlinear time-history analysis have been important developments in the field of urban regional seismic damage simulation. However, the application of refined models has been limited because of their high computational cost if they are implemented on traditional central processing unit (CPU) platforms. In recent years, graphics processing unit (GPU) technology has been developed and applied rapidly because of its powerful parallel computing capability and low cost. Hence, a coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing is proposed. The buildings are modeled using a multi-story concentrated-mass shear (MCS) model, and their seismic responses are simulated using nonlinear time-history analysis. The benchmark cases demonstrate the performance-to-price ratio of the proposed approach can be 39 times as great as that of a traditional CPU approach. Finally, a seismic damage simulation of a medium-sized urban area is implemented to demonstrate the capacity and advantages of the proposed method.