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Congress on Evolutionary Computation

作者： Zhijian Wu Lishan Kang State Key Laboratory of Sofware Engineering Wuhan University of China Wuhan Hubei China

We present a parallel elite-subspace evolutionary algorithm for solving systems of nonlinear equations. On the basis of numerical experiments, we find that our algorithm has an outstanding universal characteristics an... 详细信息

ISBN: (纸本)0780378040

关键词： Evolutionary computation Nonlinear equations Laboratories Convergence of numerical methods Iterative methods Newton method Gradient methods parallel algorithms parallel processing Concurrent computing

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Three-dimensional digital filtering algorithm for parallel DSP implementation

Three-dimensional digital filtering algorithm for parallel D...

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IEEE International Conference on Image Processing

作者： M. Aziz S. Boussakta D.C. McLernon School of flectronic and Electrical Lngincering Unitersity of Leeds Thc Institute of lntegmtcd Information Systems Leeds UK The Institute of Integrated Information Systems School of Electronic and Electrical Engineering University of Leeds Leeds UK University of Leeds Leeds West Yorkshire GB Inst. of Integrated Inf. Syst. Leeds Univ. UK

In this paper we present a 3-D parallel filtering algorithm. This algorithm is highly parallel and efficient as it eliminates the overhead associated with the overlapping segments in the block-filtering approach. It also lifts the restrictions on the input size for high efficiency in the block-filtering algorithm, as both the 3-D input data and impulse response of the system are decimated into eight subsections each. These subsections can be simultaneously and independently processed. The results of the implementation of the 3-D parallel filtering algorithm on multiDSP platform is presented and discussed showing a high performance reflected by the highly parallel architecture and good memory distribution of the 3-D parallel algorithm.

关键词： Filtering algorithms Digital signal processing Signal processing algorithms Digital filters parallel algorithms parallel processing Concurrent computing Information systems parallel architectures Computer applications

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Impact of data distribution, level of parallelism, and communication frequency on parallel data cube construction

Impact of data distribution, level of parallelism, and commu...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Ge Yang Ruoming Jin G. Agrawal Department of Computer and Information Sciences Ohio State Uinversity Columbus OH USA

Data cube construction is a commonly used operation in data warehouses. Because of the volume of data that is stored and analyzed in a data warehouse and the amount of computation involved in data cube construction, it is natural to consider parallel machines for this operation. We have developed a set of parallel algorithms for data cube construction using a new data structure called aggregation tree. Our experience has shown that a number of performance trade-offs arise in developing a parallel data cube implementation. We focus on three important issues, which are: (1) data distribution, i.e., how the original array is distributed among the processors; (2) level of parallelism, i.e., what parts of the computation are parallelized and sequentialized; and (3) frequency of communication, i.e., does the implementation require frequent interprocessor communication (and less memory) or less frequent communication (and more memory). We present a detailed experimental study evaluating the above trade-offs. We consider parallel data cube construction with different cube sizes and sparsity levels. Our experimental results show the following: (1) In all cases, reducing the frequency of communication and using higher memory gave better performance, though the difference was relatively small. (2) Choosing data distribution to minimize communication volume made a substantial difference in the performance in most of the cases. (3) Finally, using parallelism at all levels gave better performance, even though it increases the total communication volume.

关键词： Frequency Concurrent computing parallel processing Data warehouses parallel algorithms Data analysis Distributed computing Companies Performance analysis Aggregates

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parallel algorithms for maximum matching in complements of interval graphs and related problems

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ALGORITHMICA 2000年第2期26卷 263-289页

作者： Andrews, MG Atallah, MJ Chen, DZ Lee, DT AT&T Bell Labs Naperville IL 60566 USA Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA Acad Sinica Inst Informat Sci Nankang 11529 Taiwan

Given a set of n intervals representing an interval graph, the problem of finding a maximum matching between pairs of disjoint (nonintersecting) intervals has been considered in the sequential model. In this paper we present parallel algorithms for computing maximum cardinality matchings among pairs of disjoint intervals in interval graphs in the EREW PRAM and hypercube models. For the general case of the problem, our algorithms compute a maximum matching in O (log(3) n) time using O (nl log(2) n) processors on the EREW PRAM and using n processors on the hypercubes. For the case of proper interval graphs, our algorithm runs in O (log n) time using O (n) processors if the input intervals are not given already sorted and using O (n/log n) processors otherwise, on the EREW PRAM. On n-processor hypercubes, our algorithm for the proper interval case takes O (log n log log n) time for unsorted input and O (log n) time for sorted input. Our parallel results also lead to optimal sequential algorithms for computing maximum matchings among disjoint intervals. In addition, we present an improved parallel algorithm for maximum matching between overlapping intervals in proper interval graphs.

关键词： parallel algorithms maximum matching problems interval graphs complement graphs EREW PRAM hypercubes

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A parallel iterative decoding algorithm for zero-tail and tail-biting convolutional codes

A parallel iterative decoding algorithm for zero-tail and ta...

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IEEE International Symposium on Information Theory

作者： T. Matsushima T.K. Matsushima S. Hirasawa Waseda University Shinjuku Tokyo Japan Polytechnic University Sagamihara Japan

This paper discusses the parallel propagation algorithm applied to the decoding of convolutional codes. The parallel algorithm surpasses the BCJR algorithm in parallel computational complexity and performance when it is applied to tail-biting codes. The complexity of iterative decoding algorithms depends on the calculation of posterior probability and bit error probability by using clique and number of iterations. The computational complexity of the parallel algorithm for tail-biting codes is almost the same as that for zero-tail convolutional codes.

关键词： Iterative decoding Iterative algorithms Convolutional codes parallel algorithms Algorithm design and analysis Error probability Performance analysis Concurrent computing Random variables Analytical models

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A simple, fast parallel implementation of Quicksort and its performance evaluation on SUN Enterprise 10000

A simple, fast parallel implementation of Quicksort and its ...

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Euromicro Conference on parallel, Distributed and Network-Based Processing

作者： P. Tsigas Yi Zhang Department of Computing Science Chalmers University of Technology Gothenburg Sweden

We have implemented sample sort and a parallel version of Quicksort on a cache-coherent shared address space multiprocessor: the SUN ENTERPRISE 10000. Our computational experiments show that parallel Quicksort outperforms sample sort. Sample sort has been long thought to be the best, general parallel sorting algorithm, especially for larger data sets. On 32 processors of the ENTERPRISE 10000 the speedup of parallel Quicksort is more than six units higher than the speedup of sample sort, resulting in execution times that were more than 50% faster than sample sort. On one processor, parallel quicksort achieved 15% percent faster execution times than sample sorting. Moreover, because of its low memory requirements, parallel Quicksort could sort data sets at twice the size that sample sort could under the same system memory restrictions.

关键词： Sun Sorting Concurrent computing parallel algorithms Space technology Computer aided manufacturing Clustering algorithms Multiprocessing systems parallel processing Computer networks

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Research-on parallel computing model of BSP in the NOWS adapt environment

Research-on parallel computing model of BSP in the NOWS adap...

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International Conference on Neural Networks and Signal Processing

作者： Anjun Song Qinke Peng Baoshen Hu Institute of System Engineering Xi'an Jiaotong University Xi'an Shaanxi China

ISBN: (纸本)0780377028

In this paper, the characteristic of parallel computing model of BSP and NOWS was analyzed. The research indicates that based from some algorithm that designed the rationalization parallel computing, the parallel computing model is fit with the environment. With the improvement of parallel computing algorithm based on NOWS of linear programming normal, the simplex method has obtained the best result to validate the conclusion.

关键词： parallel processing Concurrent computing Military computing parallel programming Costs Algorithm design and analysis Acceleration parallel algorithms Investments Predictive models

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Benchmarking the parallel MAGIC software on small clusters

Benchmarking the parallel MAGIC software on small clusters

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International Conference on Vacuum Electronics

作者： D. Smithe L. Ludeking T. Gray R. Steele G. Scheitrum G. Caryotakis Mission Research Corporation Newington VA USA Stanford Linear Accelerator Center Menlo Park CA

In this paper, we report on 2-D and 3-D versions of parallelization, and efforts to simplify reconstruction of data during post processing. The parallelization scheme uses single-coordinate domain decomposition with 1-cell overlap, and asynchronous time-stepping. We have performed a series of calibration on sheet beam klystron cavity with long drift tube using MAGIC software.

关键词： Delay Read-write memory Time measurement Linear accelerators Collaborative tools Collaborative software Acceleration Software tools parallel algorithms Software standards

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parallel breadth-first search LTL model-checking 03

Parallel breadth-first search LTL model-checking

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IEEE International Conference on Automated Software Engineering (ASE)

作者： J. Barnat L. Brim J. Chaloupka Faculty of Informatics Masaryk University Brno Brno Czech Republic

ISBN: (纸本)9780769520353

We propose a practical parallel on-the-fly algorithm for enumerative LTL (linear temporal logic) model checking. The algorithm is designed for a cluster of workstations communicating via MPI (message passing interface). The detection of cycles (faulty runs) effectively employs the so called back-level edges. In particular, a parallel level-synchronized breadth-first search of the graph is performed to discover back-level edges. For each level, the back-level edges are checked in parallel by a nested depth-first search to confirm or refute the presence of a cycle. Several optimizations of the basic algorithm are presented and advantages and drawbacks of their application to distributed LTL model-checking are discussed. Experimental implementation of the algorithm shows promising results.

关键词： State-space methods Workstations Concurrent computing Clustering algorithms Software engineering Explosions Computer networks Logic parallel algorithms Reachability analysis

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parallel computation of the 3-D Euclidean distance transform on the SlMD hypercube computer

Parallel computation of the 3-D Euclidean distance transform...

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IEEE International Conference on parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Y.-H. Lee S.-J. Horng Department of Computer Science and Information Engineering Ching Yun Instutute of Technology Jung-Li Taiwan

The processing of three-dimensional (3-D) objects from 3-D digital image data is an important task in the image processing and the computer vision fields. The distance transform (DT) is extensively applied in the image processing and computer vision areas as a key operation. In a two or three-dimensional image array, the computation of distance transform (DT) is an important task. With the increasing application of 3-D voxel images, it is useful to consider the distance transform of a 3-D digital image array. In order to provide the efficient transform computations, parallelism is employed. We develop parallel algorithms for the three-dimensional Euclidean distance transform (3D-EDT) on the SIMD hypercube computer. The time complexity of our parallel algorithm is O(log/sup 2/N) for an N/spl times/N/spl times/N image array using N/sup 3/ processors. A generalized parallel algorithm for the 3D-EDT is also proposed and it runs O((N/p)/sup 3/log(N)+(N/p)/sup 2/log/sup 2/p) time for an N/spl times/N/spl times/N binary image array on the SIMD hypercube computer using p/sup 3/ PE's, where 1/spl les/p/spl les/N.

关键词： Concurrent computing Euclidean distance Hypercubes Digital images parallel algorithms Computer vision Biomedical imaging Application software Computer science Image processing

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