On computing signatures of coherent systems

It is difficult to compute the signature of a coherent system with a large number of components. This paper derives two basic formulas for computing the signature of a system which can be decomposed into two subsystems (modules). As an immediate application, we obtain the formula for computing the signature of systemwise redundancy in terms of the signatures of the original system and the backup one. The formula for computing the signature of a componentwise redundancy system is also derived. Some examples are given to illustrate the power of the main results.     

Rapid development of scalable scientific software using a process oriented approach

Scientific applications are often not written with multiprocessing, cluster computing or grid computing in mind. This paper suggests using Python and PyCSP to structure scientific software through Communicating Sequential Processes. Three scientific applications are used to demonstrate the features of PyCSP and how networks of processes may easily be mapped into a visual representation for better understanding of the process workflow. We show that for many sequential solutions, the difficulty in implementing a parallel application is removed. The use of standard multi-threading mechanisms such as locks, conditions and monitors is completely hidden in the PyCSP library. We show the three scientific applications: kNN, stochastic minimum search and McStas to scale well on multi-processing, cluster computing and grid computing platforms using PyCSP.     

A programming system for sensor-based scientific applications

Technical advances are leading to a pervasive computational ecosystem that integrates computing infrastructures with embedded sensors and actuators, and are giving rise to a new paradigm for monitoring, understanding, and managing natural and engineered systems – one that is information/data-driven. In this paper, we present a programming system that can support such end-to-end sensor-based dynamic data-driven applications. Specifically, the programming system enables these applications at two levels. First, it provides programming abstractions for integrating sensor systems with computational models for scientific and engineering processes and with other application components in an end-to-end experiment. Second, it provides programming abstractions and system software support for developing in-network data processing mechanisms. The former supports complex querying of the sensor system, while the latter enables development of in-network data processing mechanisms such as aggregation, adaptive interpolation and assimilation. Furthermore, for the latter, we also explore the use of temporal and spatial correlations of sensor measurements in the targeted application domains to tradeoff between the complexity of coordination among sensor clusters and the savings that result from having fewer sensors for in-network processing, while maintaining an acceptable error threshold. The research is evaluated using two application scenarios: the management and optimization of an instrumented oil field and the management and optimization of an instrumented data center. Experimental results show that the provided programming system reduces overheads while achieving near optimal and timely management and control in both application scenarios.     

一种基于大数据处理的异构私有云系统

云计算和大数据已成为IT领域的研究热点,如何将云计算在数据存储和数据处理方面的优势应用于大数据领域具有重要的实际应用价值.开源的云平台OpenStack可方便地从硬件管理方面构建私有云,其存储模块Swift能够支持PB级的大数据存储.开源的云平台Hadoop在数据处理方面具有很强的优势,但在支持超大数据存储方面存在不足.通过对OpenStack中的存储模块Swift和Hadoop中的文件处理模块HDFS的比较分析,提出了将Swift和Hadoop的MapReduce技术结合来构建企业处理大数据的私有云计算系统方案.分析结果显示该方案是可行的,这种异构的私有云系统可以整合不同云计算平台各自的优势进行高效的大数据处理.     

基于云计算的电子商务解决方案研究

云计算技术的出现,给电子商务的快速发展提供新的增长点.总结了云计算的概念和三种计算形式后,详细探讨了基于云计算环境的电子商务解决方案,主要有,从云计算关键技术实现、标准建立和安全策略三个方面给出了电子商务系统构建的技术应用方案;探讨了基于电子商务云服务的虚拟电子商务系统构建的管理策略.最后,简要探讨了基于云计算的电子商务应用中的的研究问题和思路.     

The ScopeShell graphic interface: Support for computational experiments and data visualization

We consider problems of the visualization and automation of routine tasks that arise in the process of a computational experiment. We describe ScopeShell, a state-of-the-art universal platform independent graphic interface for computational codes that includes data visualization and the monitoring of calculations on distributed computing systems. We describe the concept behind ScopeShell, along with the interface’s functionality and methods of application. The ScopeShell system is used to support computational experiments in the field of controlled thermonuclear fusion. The system considerably increases the efficiency of research requiring the application of voluminous computer codes.     

Modeling framework for membrane computing in biological systems: Evaluation with a case study

Membrane computing can represent the structures and behaviors of biological systems while considering their characteristics. This paper proposes a modeling framework for membrane computing in biological systems to provide guidelines when using and experimenting with membrane computing. The framework processes include the biological requirements and property specifications, membrane computing model, membrane computing simulation strategy, and model checking approach. A biological system that comprised the ligand–receptor networks of TGF-β protein was used as a case study to evaluate the framework. The evaluation of the framework demonstrated that membrane computing performed better than conventional ordinary differential equations when capturing the structure and behavior of biological systems.     

Facilitating analysis of Monte Carlo dense matrix inversion algorithm scaling behaviour through simulation

With the latest developments in the area of advanced computer architectures, we are already seeing large-scale machines at petascale level and are faced with the exascale computing challenge. All these require scalability at system, algorithmic and mathematical model levels. In particular, efficient scalable algorithms are required to bridge the performance gap. Being able to predict application demeanour, performance and scalability of currently used software on new supercomputers of different architectures, varying sizes, and utilising distinct ways of intercommunication, can be of great benefit for researchers as well as application developers. This paper is concerned with scaling characteristics of Monte Carlo based algorithms for matrix inversion. The algorithmic behaviour on both, a shared memory and a large-scale cluster system will be predicted with the help of an extreme-scale high-performance computing (HPC) simulator.     

Limitations of computing time savings in variational multirate integrations

For systems that contain slow and fast dynamics, variational multirate integration schemes are used. These schemes split the system into parts which are simulated using a time grid consisting of micro and macro nodes. This leads to computing time savings, however not unlimited, for a certain number of micro steps per macro step the computing time is minimal. To find a relation between this minimum computing time and the number of variables in the system, the computing time for the Fermi-Pasta-Ulam problem (FPU) is measured for different numbers of masses and different numbers of micro steps. In addition, the numerical convergence of the variational multirate integration is shown for the FPU. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A poroelastic spheroidal shell model for studying the problem of head injury

The present investigation is essentially devoted to a study of the cranial biomechanics by modelling the head as a poroelastic spheroidal shell filled with a viscoelastic fluid representing the brain material. Both the skull and the brain are considered as linear and isotropic materials. The problem is formulated in terms of prolate spheroidal coordinates and is treated mathematically by using the integral transform technique. The applicability of the analytical study is illustrated by computing the stress-field generated in the system due to the application of the load through the use of appropriate numerical procedures.     

云计算技术在输电线路状态监测系统中的应用

在分析输电线路状态监测系统特点的基础上,提出了在系统中引入云计算存储与并行处理技术的设计方案,将关系型数据库与开源的Hadoop云计算平台结合使用,解决了关系型数据库在系统使用中存储和访问效率等方面的问题.介绍了所开发的原型系统提供的服务及其主要功能,并针对系统中的典型应用进行了性能测试.测试结果表明所提方案可以满足输电线路状态监测系统对数据存储与读取、分析的性能要求.     

Residue integrals and Waring’s formulas for algebraic or even transcendental systems

The present article is focused on the study of a special class of systems of non-linear transcendental equations for which classical algebraic and symbolic methods are inapplicable. For the purpose of study of such systems we develop a method for computing residue integrals with integration over certain cycles. We describe conditions under which the mentioned residue integrals coincide with power sums of the inverses to the roots of a system of equations (i.e. multidimensional Waring’s formulas). Based on this, we develop an algorithm that computes such power sums without computing the roots. As an application of the suggested method, we consider a problem of finding sums of multi-variable number series.     

A formal framework to analyze cost and performance in Map-Reduce based applications

Satisfying the global throughput targets of scientific applications is an important challenge in high performance computing (HPC) systems. The main difficulty lies in the high number of parameters having an important impact on the overall system performance. These include the number of storage servers, features of communication links, and the number of CPU cores per node, among many others.In this paper we present a model that computes a performance/cost ratio using different hardware configurations and focusing on scientific computing. The main goal of this approach is to balance the trade-off between cost and performance using different combinations of components for building the entire system. The main advantage of our approach is that we simulate different configurations in a complex simulation platform. Therefore, it is not necessary to make an investment until the system computes the different alternatives and the best solutions are suggested. In order to achieve this goal, both the system's architecture and Map-Reduce applications are modeled. The proposed model has been evaluated by building complex systems in a simulated environment using the SIMCAN simulation platform.     

Ontological approach to development of computing with words based systems

Computing with words introduced by Zadeh becomes a very important concept in processing of knowledge represented in the form of propositions. Two aspects of this concept – approximation and personalization – are essential to the process of building intelligent systems for human-centric computing.For the last several years, Artificial Intelligence community has used ontology as a means for representing knowledge. Recently, the development of a new Internet paradigm – the Semantic Web – has led to introduction of another form of ontology. It allows for defining concepts, identifying relationships among these concepts, and representing concrete information. In other words, an ontology has become a very powerful way of representing not only information but also its semantics.The paper proposes an application of ontology, in the sense of the Semantic Web, for development of computing with words based systems capable of performing operations on propositions including their semantics. The ontology-based approach is very flexible and provides a rich environment for expressing different types of information including perceptions. It also provides a simple way of personalization of propositions. An architecture of computing with words based system is proposed. A prototype of such a system is described.     

Über eine spezielle lineare o-l-optimlermagsaufgabe

Starting with the empty container problem a special linear 0-1-programming problem is stated. The application of this problem allows the optimal use of the main storage of a computing system in a certain sense. An approximating algorithm for solving this task is given, and some numerical results are mentioned.     

Block-iterative methods for consistent and inconsistent linear equations

Summary We shall in this paper consider the problem of computing a generalized solution of a given linear system of equations. The matrix will be partitioned by blocks of rows or blocks of columns. The generalized inverses of the blocks are then used as data to Jacobi- and SOR-types of iterative schemes. It is shown that the methods based on partitioning by rows converge towards the minimum norm solution of a consistent linear system. The column methods converge towards a least squares solution of a given system. For the case with two blocks explicit expressions for the optimal values of the iteration parameters are obtained. Finally an application is given to the linear system that arises from reconstruction of a two-dimensional object by its one-dimensional projections.     

A modified accelerated monotone iterative method for finite difference reaction-diffusion-convection equations

This paper is concerned with monotone algorithms for the finite difference solutions of a class of nonlinear reaction-diffusion-convection equations with nonlinear boundary conditions. A modified accelerated monotone iterative method is presented to solve the finite difference systems for both the time-dependent problem and its corresponding steady-state problem. This method leads to a simple and yet efficient linear iterative algorithm. It yields two sequences of iterations that converge monotonically from above and below, respectively, to a unique solution of the system. The monotone property of the iterations gives concurrently improving upper and lower bounds for the solution. It is shown that the rate of convergence for the sum of the two sequences is quadratic. Under an additional requirement, quadratic convergence is attained for one of these two sequences. In contrast with the existing accelerated monotone iterative methods, our new method avoids computing local maxima in the construction of these sequences. An application using a model problem gives numerical results that illustrate the effectiveness of the proposed method.     

非线性自由表面波问题的差分解法

本文提出计算二维非定常位势流动的有限差分法,流动是因自由表面任意瞬间扰动所产生的.自由表面上同时满足动力和运动的非线性条件.本方法的基本特征是利用坐标变换将时间相关的物理计算域变换为固定域;建立迭代格式解Poisson方程以求速度势;通过快速富氏变换化为三对角型代数方程组计算未知量,因而大量节省计算机时.为解非定常自由表面波浪问题提供了一个有效的方法.引用了两个例题验证方法的可行性.     

状态反馈极点配置问题的一个新算法

§1.引言 极点配置问题是控制理论中的一个重要的问题,描述如下: 问题(P1).给定A∈R~(n×n),B∈R~(n×m),Λ={λ_1,λ_2,…,λ_n},Λ在复共轭下封闭.求F∈R~(m×n),使得