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15th International Euro-Par conference on parallel Computing

作者： Schlauch, Tobias Eifer, Anastasia Soddemann, Thomas Schreiber, Andreas German Aerosp Ctr Simulat & Software Technol D-51147 Cologne Germany Fraunhofer Inst Algorithms & Sci Comp SCAI St Augustin Germany

ISBN: (纸本)9783642141218

Data produced in scientific and industrial applications is growing exponentially but most resource middleware systems lack of appropriate support for data and metadata management. In particular easy and intuitive retrieval of data for later use is a serious problem. In this context the paper proposes a pragmatic approach for data management of distributed data with focus on appropriate means for data organization improving data retrieval. The paper presents the key concepts and architecture of a dedicated data management system for sharing data located on heterogeneous storage resources. The different specifics of storage systems such as data object names, data locations, and data access methods are abstracted to allow transparent data access. Moreover, the system provides means for data structuring and organization by supporting custom data models and annotation of individual metadata on data objects. Current development status of the system is illustrated by presenting an integration with the UNICORE Rich Client which has been validated in the context of the AeroGrid project.

关键词： UNICORE DataFinder distributed Data Management

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The research of image segmentation based on improved neural network algorithm

The research of image segmentation based on improved neural ...

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6th International conference on Semantics, Knowledge and Grid, SKG 2010

作者： Zhang, Lijun Deng, Xiuchun Computer Science and Information Technology College Zhejiang Wanli University Qianhu South Road 8 NingBo China

ISBN: (纸本)9780769541891

image segmentation is critical to image processing and pattern recognition, An image segmentation system is proposed for the segmentation of color image based on neural networks. First, we introduce BP Neural network, it has the capacity of parallel computing, distributed saving, self-studying, fault-to-learnt and nonlinear function approximating. So it widely used in image segmentation, but it also has some unavoidable defects. Based on this, a new method of image segmentation based on both Wavelet Decomposition and self-organizing map neural network (short for SOM-NN) is proposed. It has a greater ability on resisting noise, improving the convergence and so on. Color prototypes provide a good estimate for object colors. The image pixels are classified by the matching of color prototypes. The experimental results show that the system has the desired ability for the segmentation of color image in a variety of vision tasks. © 2010 IEEE.

关键词： Self organizing maps

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Comparative Study of parallel Algorithms for Asynchronous Cellular Automata Simulation on Different Computer Architectures

Comparative Study of Parallel Algorithms for Asynchronous Ce...

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9th International conference on Cellular Automata for Research and Industry

作者： Kalgin, Konstantin RAS SB Inst Computat Math & Math Geophys Moscow Russia

ISBN: (纸本)9783642159787

Overview and experimental comparative study of parallel algorithms of asynchronous cellular at simulation is presented. The algorithms are tested for the model of physicochemical process of surface CO + O-2 reaction over the supported Pd nanoparticles on different parallel computers. For testing we use shared memory computers, distributed memory computers (i.e. clusters), and graphical processing unit. Characterization of these algorithms in respect of methods of parallelism maintenance is given.

关键词： parallel algorithms

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Scalable combined H.264/distributed video coding

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COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2010年第2期29卷 388-404页

作者： Lv, Rui Qing, Linbo Yu, Yanmei He, Xiaohai Zeng, Qiangyu Sichuan Univ Image Informat Inst Sch Elect & Informat Engn Chengdu 610064 Peoples R China

Purpose - The first purpose of this paper is to propose a scalable video coding scheme providing flexibility in video transmission, especially under wireless environment. The second purpose is to analyze the problem of lengthening the key frame interval in distributed video coding (DVC), and propose an approach to improve the rate-distortion (RD) performance of DVC for long group-of-frames (GOF) size. Design/methodology/approach - In the proposed scheme, a base layer is first obtained from an H.264 coder. When a DVC coder is then used to code the enhancement layer, information in processing the base layer is extracted and analyzed to make multiple side-information available and reduce error accumulation for DVC coding, thus further improving the performance of the DVC coder. Findings - By dividing video into base and enhancement layers, the combined video coding architecture enables a flexible video transmission. In addition, several methods are used to improve the RD performance in DVC coding. Simulation shows that the proposed scheme outperforms non-scalable DVC for long GOF size. Originality/value - Prediction from the decoding loop in base layer encoder largely reduces enhancement layer spatial redundancy. Multiple side-information provides better estimation for DVC reconstruction. Long prediction loop is more reliable because error accumulation is effectively compensated.

关键词： Video Codes Wireless Data compression Transmission Control Protocol/Internet Protocol

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Non-intrusive performance analysis of parallel hardware accelerated applications on hybrid architectures

Non-intrusive performance analysis of parallel hardware acce...

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International Workshop on Scheduling and Resource Management for parallel and distributed Systems

作者： Dietrich, Robert Ilsche, Thomas Juckeland, Guido Technische Universität Dresden Dresden Germany

ISBN: (纸本)9780769541570

New high performance computing (HPC) applications recently have to face scalability over an increasing number of nodes and the programming of special accelerator hardware. Hybrid composition of large computing systems leads to a new dimension in complexity of software development. This paper presents a novel approach to gain insight into accelerator interaction and utilization without any changes to the application. It leverages well established methods for performance analysis to accelerator hardware, allowing a holistic view on performance bottlenecks of hybrid applications. A general strategy is presented to get dynamic runtime information about hybrid program execution with minimal impact on the program flow. The achievable level of detail is exemplarily studied for the CUDA environment and the OpenCL framework. Combined with existing performance analysis techniques this facilitates obtaining the full potential of hybrid computing power. © 2010 IEEE.

关键词： Computing power

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A connectionist knowledge based system using coarse-coded distributed representations 10

A connectionist knowledge based system using coarse-coded di...

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International conference and Workshop on Emerging Trends in Technology 2010, ICWET 2010

作者： Sanjeevi, S.G. Bhattacharyya, P. Dept. of Comp. Science and Engineering N.I.T. Warangal Warangal India Dept. of Comp. Science and Engineering IIT Bombay Mumbai-400076 India

ISBN: (纸本)9781605588124

Traditionally reasoning systems have been implemented using symbolic methods of artificial intelligence. Connectionist methods of implementing reasoning systems form an alternative paradigm. Among the connectionist reasoning systems two types of representational methods can be used. They are i) localist and ii) distributed representational methods. In the literature, some localist methods for reasoning were used in connectionist systems. Since those systems used localist representations, advantages of distributed representations are not obtainable by them. In this paper, we describe the design and implementation of a connectionist knowledge based system which integrates a connectionist predicate logic reasoning system and a connectionist semantic network. The system uses distributed coarse-coded representations. The connectionist predicate logic system supports both simple rules as well as a complex rule having multiple conjunctions. distributed representations have advantages of increased fault tolerance, graceful degradation of performance;neural plausibility, cognitive modeling and parallel distributed processing. The system besides showing above features allows the communication between these two connectionist systems and makes it possible to access the information of attributes and corresponding values from the connectionist semantic network for the entities used in the connectionist predicate logic system. Copyright 2010 ACM.

关键词： Fault tolerance

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Regularization parameter estimation for large-scale Tikhonov regularization using a priori information

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2010年第12期54卷 3430-3445页

作者： Renaut, Rosemary A. Hnetynkova, Iveta Mead, Jodi Arizona State Univ Dept Math & Stat Tempe AZ 85287 USA

Solutions of numerically ill-posed least squares problems Ax approximate to b for A is an element of R-mxn by Tikhonov regularization are considered. For D is an element of R-pxn, the Tikhonov regularized least squares functional is given by J(sigma) = parallel to Ax - b parallel to(2)(W) + 1/sigma(2) parallel to D(x - x(0))parallel to(2)(2) where matrix W is a weighting matrix and x(0) is given. Given a priori estimates on the covariance structure of errors in the measurement data b, the weighting matrix may be taken as W = W-b which is the inverse covariance matrix of the mean 0 normally distributed measurement errors e in b. If in addition x(0) is an estimate of the mean value of x, and sigma is a suitable statistically-chosen value, J evaluated at its minimizer x(sigma) approximately follows a chi(2) distribution with (m) over tilde = m + p - n degrees of freedom. Using the generalized singular value decomposition of the matrix pair [W(b)(1/2)AD], sigma can then be found such that the resulting J follows this chi(2) distribution. But the use of an algorithm which explicitly relies on the direct solution of the problem obtained using the generalized singular value decomposition is not practical for large-scale problems. Instead an approach using the Golub-Kahan iterative bidiagonalization of the regularized problem is presented. The original algorithm is extended for cases in which x(0) is not available, but instead a set of measurement data provides an estimate of the mean value of b. The sensitivity of the Newton algorithm to the number of steps used in the Golub-Kahan iterative bidiagonalization, and the relation between the size of the projected subproblem and sigma are discussed. Experiments presented contrast the efficiency and robustness with other standard methods for finding the regularization parameter for a set of test problems and for the restoration of a relatively large real seismic signal. An application for image deblurring also validates the appr

关键词： PARAMETER estimation INFORMATION processing LEAST squares FUNCTIONAL analysis STATISTICS DATA analysis

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Scalability in privacy-preserving data aggregation for wireless sensor networks

Scalability in privacy-preserving data aggregation for wirel...

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IEEE International Symposium on parallel and distributed processing With Applications

作者： Bista, Rabindra Shin, Young-Sung Chang, Jae-Woo Dept. of Computer Engineering Center for Advanced Image and Information Technology Chonbuk National University Chonju Chonbuk 561-756 Korea Republic of

ISBN: (纸本)9780769541907

In this paper, we propose a new privacy preserving data aggregation scheme for WSNs. Our scheme applies additive property of complex numbers in order to combine sensor data and preserve data privacy during transmission to the sink node. In addition, for supporting scalability, we propose a novel mechanism in which a special set of real numbers are assigned to sensor nodes as their IDs so that a single bit is sufficient to hold ID of a sensor node during transmission of aggregated data to the sink node. For this, we, first, generate fixed size signatures for the IDs of all sensor nodes and then superimpose the signatures during data aggregation phase. By analytical evaluations, we show that our scheme is more scalable and energy efficient than the existing methods to achieve data privacy and transmit IDs of sensor nodes along with the aggregated data to the sink node. © 2010 IEEE.

关键词： Sensor nodes

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parallel Adaptive Finite Element Package with Dynamic Load Balancing for 3D Thermo-Mechanical Problems

Parallel Adaptive Finite Element Package with Dynamic Load B...

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8th International conference on parallel processing and Applied Mathematics

作者： Olas, Tomasz Lesniak, Robert Wyrzykowski, Roman Gepner, Pawel Czestochowa Tech Univ Dabrowskiego 73 PL-42201 Czestochowa Poland Intel Corp Santa Clara CA USA

ISBN: (纸本)9783642143892

Numerical modeling of 3D thermomechanical problems is a complex and time-consuming issue. Adaptive techniques are powerful tools to perform efficiently such modeling using the FEM analysis. During the adaptation computational workloads change unpredictably at the runtime, therefore dynamic load balancing is required. This paper presents new developments in the parallel FIFA package NuscaS;they allow for extending its functionality and increasing performance. In particular, by including dynamic load balancing capabilities, this package allows us to solve efficiently adaptive FEM problems with 3D unstructured meshes on distributed-memory parallel computers such as PC-clusters. For solving sparse systems of equations, NuscaS uses the message-passing paradigm to implement the PCG iterative method with geometric multigrid as a preconditioner. The implementation of load balancing is based on the proposed performance model.

关键词： Iterative methods

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Dynamic load balancing in parallel KD-Tree k-Means

Dynamic load balancing in parallel KD-Tree k-Means

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10th IEEE International conference on Computer and Information Technology, CIT-2010, 7th IEEE International conference on Embedded Software and Systems, ICESS-2010, 10th IEEE Int. Conf. Scalable Computing and Communications, ScalCom-2010

作者： Di Fatta, Giuseppe Pettinger, David School of Systems Engineering University of Reading Whiteknights Reading Berkshire RG6 6AY United Kingdom

ISBN: (纸本)9780769541082

One among the most influential and popular data mining methods is the k-Means algorithm for cluster analysis. Techniques for improving the efficiency of k-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting geometrical constraints and an efficient data structure, notably a multi-dimensional binary search tree (KD-Tree). These techniques allow to reduce the number of distance computations the algorithm performs at each iteration. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient k-Means variants in parallel computing environments. In this work, we provide a parallel formulation of the KD-Tree based k-Means algorithm for distributed memory systems and address its load balancing issue. Three solutions have been developed and tested. Two approaches are based on a static partitioning of the data set and a third solution incorporates a dynamic load balancing policy. © 2010 IEEE.

关键词： Cluster analysis

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