MPI＋OpenMP混合编程模型在大规模三对角线性方程组求解中的应用

分布式共享存储系统的特点是每个节点内是共享存储的,而节点间是分布式存储.为了更好地利用这种多级体系结构,讨论了MPI＋OpenMP混合编程模型的性能及实现方法,建立了大规模三对角线性方程组的MPI＋OpenMP混合并行算法,并在上海大学高性能计算集群上与单纯MPI算法进行了性能方面的比较.结果表明,MPI＋OpenMP混合并行算法具有更好的加速比和扩展性.     

基于Moldflow/MPI的UPS电源壳体注塑成型分析

运用Moldflow/MPI模块对UPS电源壳体注塑成型过程进行了数值模拟分析,预测了熔体充模过程中的型腔压力分布、温度分布、锁模力大小、体积收缩率及翘曲变形;根据分析结果,提出了工艺优化方案,从而缩短模具设计制造周期。     

通过西门子step7软件配置手持单元与NCU的通讯

西门子840D系统配置手持单元HHU时，通常的做法是采用西门子提供的标准软件包，解压之后，把源文件导入step7的源文件区，再编译下载即可，但是遇到某些特殊应用时，必须自己编程去建立手持单元和840D的通讯。本文介绍的方法，经证实有效。     

Integrated evolutionary neural network approach with distributed computing for congestion management

Electric supply industry is facing deregulation all over the world. Under deregulated power supply scenario, power transmission congestion has become more intensified and recurrent, as compared to conventional regulated power system. Congestion may lead to violation of voltage or transmission capacity limits, thus threatens the power system security and reliability. Also the growing congestion may lead to unanticipated divergent electricity pricing. Owing to these facts congestion management has become a crucial issue in the deregulated power system scenario.Fast and precise prediction of nodal congestion prices in real time deregulated/spot power market may enable market participants and system operators to keep pace with the congestion by taking preventive measures like transaction rescheduling, bids (both for supplying and consuming electricity) modification, regulated dispatch of electric power, etc. This paper proposes an integrated evolutionary neural network (ENN) approach to predict nodal congestion prices (NCPs) for congestion management in spot power market. Distributed computing is employed to tackle the heterogeneity of the data in the prediction of NCP values. Developed ENNs have been trained and tested under distributed computing environment, using a message passing paradigm. Proposed hybrid approach for NCP prediction is demonstrated on a 6-bus test power system with and without distributed computing. The proposed approach not only demonstrated the computing efficiency of the developed ENN model over the conventional optimal power flow method but also shows the time saving aspect of distributed computing.     

Performing BMMC Permutations Efficiently on Distributed-Memory Multiprocessors with MPI

This paper presents an architecture-independent method for performing BMMC permutations on multiprocessors with distributed memory. All interprocessor communication uses the MPI function MPI_Sendrecv_replace(). The number of elements and number of processors must be powers of 2, with at least one element per processor, and there is no inherent upper bound on the ratio of elements per processor. Our method transmits only data without transmitting any source or target indices, which conserves network bandwidth. When data is transmitted, the source and target processors implicitly agree on each other's identity and the indices of the elements being transmitted. A C-callable implementation of our method is available from Netlib. The implementation allows preprocessing (which incurs a modest cost) to be factored out for multiple runs of the same permutation, even if on different data. Data may be laid out in any one of several ways: processor-major, processor-minor, or anything in between. Experimental results indicate that our method works well compared with several other candidate methods on three different platforms. In particular, the slower the interconnection network, the greater the relative advantage of our method. Received June 1, 1997; revised March 10, 1998.     

Flood simulation using parallel genetic algorithm integrated wavelet neural networks

The conventional means of flood simulation and prediction using conceptual hydrological model or artificial neural network (ANN) has provided promising results in recent years. However, it is usually difficult to obtain ideal flood reproducing due to the structure of hydrological model. Back propagation (BP) algorithm of ANN may also reach local optimum when training nodal weights. To improve the mapping capability of neural networks, wavelet function was adopted (WANN) to strengthen the non-linear simulation accuracy and generality. In addition, genetic algorithm is integrated with WANN (GAWANN) to avoid reaching local optimum. Meanwhile, Message Passing Interface (MPI) subroutines are introduced for distributed implement considering the time consumption during nodal weights training. The GAWANN was applied in the flood simulation and prediction in arid area. The test results of 4 independent cases were compared to reveal the relations between historical rainfall and runoff under different time lags. The simulation was also carried out with Xinanjiang model to demonstrate the capability of GAWANN. The numerical experiments in this paper indicated that the parallel GAWANN has strong capability of rain-runoff mapping as well as computational efficiency and is suitable for applications of flood simulation in arid areas.     

超磁致伸缩作动器的率相关Hammerstein模型与H∞鲁棒跟踪控制

利用Hammerstein模型对超磁致伸缩作动器（Giant magnetostrictive actuators,GMA）的率相关迟滞非线性进行建模,分别以改进的 Prandtl-Ishlinskii（Modified Prandtl-Ishlinskii）模型和外因输入自回归模型（Autoregressive model with exogenous input,ARX）代表Hammerstein模型中的静态非线性部分和线性动态部分,并给出了模型的辨识方法. 此模型能在1～100Hz频率范围内较好地描述GMA的率相关迟滞非线性. 提出了带有逆补偿器和H∞鲁棒控制器的二自由度跟踪控制策略,实时跟踪控制实验结果证明了所提策略的有效性.     

基于气体穿透效果数值模拟的气体辅助注射成型工艺优化

对气体辅助注射成型工艺进行分析，阐述了气体辅助注射成型的关键技术要求在分析熔料流动、气体穿透物理模型的基础上，探讨了气体辅助注射成型数值分析的实现原理运用MPI／Gas模块对一T型支架进行了气体辅助注射成型CAE分析，模拟不同工艺条件下的气体穿透效果，确定了合理的工艺参数。     

A uniform approach for programming distributed heterogeneous computing systems

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging.In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal.We assess libWater’s performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.     

Moldflow冷却分析在注塑模中的应用

基于Moldflow的MPI/Cool模块,介绍了MPI/Cool模块的主要功能和作用,并结合其在实际生产中的应用,通过比较不同的冷却方案,优化出冷却系统,从而说明在注塑模设计时使用MPI/Cool模块优化冷却系统的强大作用,这对提高制品质量和生产率具有重大的实际指导意义.