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8th International Symposium on parallel Architectures, Algorithms and Networks, I-SPAN 2005

作者： Li, Kuan-Ching Wang, Hsiao-Hsi Chen, Chiou-Nan Liu, Chun-Chieh Chang, Chia-Fu Hsu, Chia-Wen Hung, Sheng-Shiang Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Shalu Taichung 43301 Taiwan Laboratory of Bioinformatics and Computational Biology Department of Computer Science National Tsing Hua University Hsinchu 30013 Taiwan

ISBN: (纸本)0769525091

The low-cost and availability of network of workstations have made them attractive solution for high performance computing. Striking progress of network technology is enabling high-performance global computing, with the utilization of cluster and grid technologies, in which computational and data resources in a local or wide area network are transparently employed to solve large-scale problems. In this paper, we present implementation and design rationale of Visuel* toolkit for performance measurement and analysis of parallel applications in cluster and grid environments. Most of performance visualization tools available today for high-performance platforms show solely system performance data (e.g., CPU load, memory usage, network bandwidth, server average load), and thus, being suitable for visualization of computing platform system activities. The Visuel toolkit is web-based interface designed to show performance, activities of all computing nodes of a cluster or grid computing platform involved in the execution of a parallel application, such as CPU load level and memory usage of each computing node. In addition, this toolkit is able to display comparative performance data visualizations generated from a number of executions of an application under investigation, analyzing the performance of different implementations. Evaluations using this toolkit show that it outperforms in easing the process of investigation and implementation of parallel applications, in effective way. © 2005 IEEE.

关键词： computer workstations

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Performance evaluation of allgather algorithms on terascale Linux cluster with Fast Ethernet

Performance evaluation of allgather algorithms on terascale ...

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8th International Conference on High-Performance Computing in Asia-Pacific Region

作者： Chen, Jing Zhang, Linbo Zhang, Yunquan Yuan, Wei Department of Computer Science University of Science and Technology of China China Lab. of Parallel Computing Institute of Software CAS China State Key Laboratory of Computer Science China Academy of Mathematics and Systems Sciences CAS China

ISBN: (纸本)0769524869

We report our work on evaluating performance of several MPI Allgather algorithms on Fast Ethernet. These algorithms are ring, recursive doubling, Bruck, and neighbor exchange. The first three algorithms are widely used today. The neighbor exchange algorithm which was recently proposed by the authors incorporates pair-wise exchange, and is expected to perform better with certain configurations, mainly when using TCP/IP over Ethernet. We tested the four algorithms on terascale Linux clusters DeepComp 6800 and DAWNING 4000A using TCP/IP over Fast Ethernet. Results show that our neighbor exchange algorithm performs the best for long messages, the ring algorithm performs the best for medium-size messages and the recursive doubling algorithm performs the best for short messages.

关键词： computer networks

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Decision tree construction for data mining on grid computing environments

Decision tree construction for data mining on grid computing...

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19th International Conference on Advanced Information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Tsai, Shu-Tzu Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

In this paper, we present our Grid-based decision tree architecture, with the intention of applying it to both parallel and sequential algorithms. Also, we show that, based on the scope and model of data mining applied in the Grid environment as well as user equivalent perspective, Grid roles can be categorized into three types. It is our goal, through these definitions, to help software developers define clear system processes and differentiate the application scope for software applications. To, fulfill our architecture, we first apply an existing parallel decision tree algorithm (the SPRINT algorithm) to the Grid environment. The performance and differences in many other areas are compared using datasets of different sizes. The experimental results will be used for future reference and further development. © 2005 IEEE.

关键词： Data mining

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An enhanced parallel loop self-scheduling scheme for cluster environments

An enhanced parallel loop self-scheduling scheme for cluster...

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19th International Conference on Advanced Information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Cheng, Kuan-Wei Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

In this paper, a parallel loop self-scheduling scheme for heterogeneous PC cluster systems is proposed. Though the proposed scheme does allow users to choose parameters before the execution initialization phase, there are still weaknesses that motivate us to go further with new improvements in that scheme. For instance, a decision on a fixed and monotonous parameter can easily lead to invalid schedule by using previous input information. Thus, it is proposed in this paper a new scheme, where the scheduling parameter can be adjusted dynamically and fit into most widely available computer systems, in order to provide higher overall performance. © 2005 IEEE.

关键词： Scheduling

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A high-performance computational resource broker for Grid Computing environments

A high-performance computational resource broker for Grid Co...

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19th International Conference on Advanced Information Networking and Applications, AINA 2005

作者： Yang, Chao-Tung Shih, Po-Chi Li, Kuan-Ching High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung City 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung County 43301 Taiwan

ISBN: (纸本)0769522491

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. As Grid Computing is becoming a reality, there is a need for managing and monitoring the available resources worldwide, ax well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the user's needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using user's credentials. The resource broker runs on top of the Globus Toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the diverse systems available in the Grid. © 2005 IEEE.

关键词： computer systems

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Speeding up fractal image compression by genetic algorithms

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MULTIDIMENSIONAL systems AND SIGNAL PROCESSING 2005年第2期16卷 217-236页

作者： Mohamed, F Aoued, B Department of Computer Science Evolutionary Engineering and Distributed Information Systems Laboratory EEDIS University of Sidi Bel-Abbès Algeria Department of Electronics Communications Networks Architectures and Multimedia Laboratory University of Sidi Bel Abbès Algeria

The main problem with all fractal compression implementation is execution time. Algorithms can spend hours to compress a single image. Most of the major variants of the standard algorithm for speeding up computation time have led to a bad-quality or a lower compression ratio. For example, the Fisher's [ 7] proposed classification pattern greatly accelerated the algorithm, but image quality was poor due to the search-space reduction imposed by the classification, which eleminates a lot of good solutions. By using genetic algorithms to address the problem, we optimize the domain blocks search. We explore all domain blocks present in the image but not in exhaustive way ( like a standard algorithm) and without omitting any possible block (solution) as a classification pattern does. A genetic algorithm is the unique method for satisfying these constraints. And it is a way to do be a random search because the genetic one is directed by fitness selection, which produces optimal solutions. Our goal in this work is to use a genetic algorithm to solve the IFS inverse problem and to build a fractal compression algorithm based on the genetic optimization of a domain blocks search. we have also implemented standard Barnsley algorithm, the Y. Fisher based on classification, and the genetic compression algorithm with quadtree partitioning. A population of transformations was evolved for each range block, and the result is compared with the standard Barnsely algorithm and the Fisher algorithm = based classification. We deduced an optimal set of values for the best parameters combination, and we can also specify the best combination for each desired criteria: best compression ratio, best image quality, or quick compression process. By running many test images, we experimentally found the following set of optimal values of all the algorithm parameters that ensure compromise between execution time and solutions optimality: Population size = 100, Maximum generations = 20, Crossover rat

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A recursive-adjustment co-allocation scheme in data grid environments 1

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6th International Conference on Algorithms and Architectures for parallel Processing, ICA3PP

作者： Yang, Chao-Tung Yang, I.-Hsien Li, Kuan-Ching Hsu, Ching-Hsien High Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan

ISBN: (数字)9783540320715

ISBN: (纸本)3540292357

The co-allocation architecture was developed in order to enable parallel downloads of datasets from multiple servers. Several co-allocation strategies have been coupled and used to exploit rate differences among various client-server links and to address dynamic rate fluctuations by dividing files into multiple blocks of equal sizes. However, a major obstacle, the idle time of faster servers having to wait for the slowest server to deliver the final block, makes it important to reduce differences in finish time among replica servers. In this paper, we propose a dynamic co-allocation scheme, namely Recursive-Adjustment Co-Allocation scheme, to improve the performance of data transfer in Data Grids. Our approach reduces the idle time spent waiting for the slowest server and decreases data transfer completion time. © Springer-Verlag Berlin Heidelberg 2005.

关键词： parallel processing systems

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On utilization of the grid computing technology for video conversion and 3D rendering

On utilization of the grid computing technology for video co...

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3rd International Symposium on parallel and distributed Processing and Applications, ISPA 2005

作者： Yang, Chao-Tung Lai, Chuan-Lin Li, Kuan-Ching Hsu, Ching-Hsien Chu, William C. High Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan

ISBN: (纸本)3540297693

In this paper, we investigate the recent popular computing technique called Grid Computing, and use video conversion and 3D rendering applications to demonstrate this technology's effectiveness and high performance. We also report on developing a resource broker called Phantom that runs on our grid computing testbed and whose main function is querying nodes in grid computing environments and showing their system information to aid in selecting the best nodes for job assignments to have the jobs executed in the least amount of time. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Computability and decidability

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Performance analysis of applying replica selection technology for Data Grid environments

Performance analysis of applying replica selection technolog...

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8th International Conference on parallel Computing Technologies, PaCT 2005

作者： Yang, Chao-Tung Chen, Chun-Hsiang Li, Kuan-Ching Hsu, Ching-Hsien High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan

The Data Grid enables the sharing, selection, and connection of a wide variety of geographically distributed computational and storage resources for solving large-scale data intensive scientific applications. Such technology efficiently manage and transfer terabytes or even petabytes of data for data-intensive, high-performance computing applications in wide-area, distributed computing environments. Replica selection process allows an application to choose a replica from replica catalog, based on its performance and data access features. In this paper, we build a Grid environment based on three existing PC Cluster environments and perform performance analysis of data transfers using GridFTP protocol over these systems. In addition, based on experimental results, it is proposed a cost model to pick the best replica, in real and dynamic network situations. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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A chronological history-based execution time estimation model for embarrassingly parallel applications on grids

A chronological history-based execution time estimation mode...

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3rd International Symposium on parallel and distributed Processing and Applications, ISPA 2005

作者： Yang, Chao-Tung Shih, Po-Chi Lin, Cheng-Fang Hsu, Ching-Hsien Li, Kuan-Ching High Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan

ISBN: (纸本)3540297693

In order to identify and schedule jobs that are suitable for determined resources, an execution time estimation model is required. In this paper, it is described a Chronological history-based execution time estimation model to predict current execution time, according to the previous execution results. We built a heterogeneous computational Grid environment using Globus Toolkit, and our research is focused in Grid computing environments and to execute parallel jobs on multiple resources by measuring its accuracy. The experimental results shown that our model can accurately predict the execution time of embarrassingly parallel applications. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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