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parallel construction of independent spanning trees and an application in diagnosis on Mobius cubes

JOURNAL OF SUPERCOMPUTING 2013年第3期65卷 1279-1301页

作者： Cheng, Baolei Fan, Jianxi Jia, Xiaohua Jia, Juncheng Soochow Univ Sch Comp Sci & Technol Suzhou 215006 Peoples R China Soochow Univ Prov Key Lab Comp Informat Proc Technol Suzhou 215006 Peoples R China City Univ Hong Kong Dept Comp Sci Kowloon Hong Kong Peoples R China

Independent spanning trees (ISTs) on networks have applications to increase fault-tolerance, bandwidth, and security. Mobius cubes are a class of the important variants of hypercubes. A recursive algorithm to construct n ISTs on n-dimensional Mobius cube M (n) was proposed in the literature. However, there exists dependency relationship during the construction of ISTs and the time complexity of the algorithm is as high as O(NlogN), where N=2 (n) is the number of vertices in M (n) and na parts per thousand yen2. In this paper, we study the parallel construction and a diagnostic application of ISTs on Mobius cubes. First, based on a circular permutation n-1,n-2,aEuro broken vertical bar,0 and the definitions of dimension-backbone walk and dimension-backbone tree, we propose an O(N) parallel algorithm, called PMCIST, to construct n ISTs rooted at an arbitrary vertex on M (n) . Based on algorithm PMCIST, we further present an O(n) parallel algorithm. Then we provide a parallel diagnostic algorithm with high efficiency to diagnose all the vertices in M (n) by at most n+1 steps, provided the number of faulty vertices does not exceed n. Finally, we present simulation experiments of ISTs and an application of ISTs in diagnosis on 0-M (4).

关键词： Mobius cube Independent spanning tree parallel algorithm Nonnegative vector Diagnosis Circular permutation

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Clustering using Artificial Bee Colony on CUDA

Clustering using Artificial Bee Colony on CUDA

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Jan Janousek Jan Platos Vaclav Snasel Department of Computer Science FEECS IT4 Innovations VSB - Technical University of Ostrava

ISBN: (纸本)9781479938414

Artificial bee colony is a meta-heuristic optimization algorithm based on the behavior of honey bee swarm. These bees work largely independently of other bees, making the algorithm suitable for parallel implementation. Within this paper, we introduce the algorithm itself and its subsequent parallelization utilizing the CUDA platform. The runtime speedup is demonstrated on several commonly used test functions for optimization. The algorithm is subsequently applied to the problem of clustering real data.

关键词： parallel algorithm Artificial bee colony CUDA Clustering

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parallel algorithms for Approximate String Matching with k Mismatches on CUDA

Parallel Algorithms for Approximate String Matching with <i>...

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26th IEEE International parallel and Distributed Processing Symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Liu, Yu Guo, Longjiang Li, Jinbao Ren, Meirui Li, Keqin Heilongjiang Univ Sch Comp Sci & Technol Harbin 150080 Peoples R China Key Lab Database & Parallel Comp uting Harbin 150080 Heilongjiang Peoples R China SUNY Coll New Paltz Dept Comp Sci New Paltz NY 12561 USA

ISBN: (纸本)9780769546766

Approximate string matching using the.. mismatch technique has been widely applied to many fields such as virus detection and computational biology. The traditional parallel algorithms are all based on multiple processors, which have high costs of computing and communication. GPU has high parallel processing capability, low cost of computing, and less time of communication. To the best of our knowledge, there is no any parallel algorithm for approximate string matching with.. mismatches on GPU. With a new parallel programming model based on CUDA, we present three parallel algorithms and their implementations on GPU, namely, the thread parallel algorithm, the block-thread parallel algorithm, and the OPT-block-thread parallel algorithm. The OPT-block-thread parallel algorithm can take full advantage of the powerful parallel capability of GPU. Furthermore, it balances the load among the threads and optimizes the execution time with the memory model of GPU. Experimental results show that compared with the traditional sequential algorithm on CPU, our best parallel algorithm on GPU in this paper achieves speedup of 40-80.

关键词： Approximate string matching CUDA GPU Hamming distance parallel algorithm

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Research and Implementation of Petri nets parallelization model

Research and Implementation of Petri nets parallelization mo...

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13th International Symposium on Distributed Computing and Applications to Business,Engineering & Science（DCABES 2014）

作者： Xuan Wang Wen-jing LI Ze-yu Tang Weizhi LIAO College of Computer and Information Engineering Guangxi Teachers Education University

In order to solve parallel algorithm of Petri net system with concurrent functions and implement parallel control and execution of Petri net, parallel programming model of Petri net based on multi-core clusters is put forward. First, P-invariant technology is used to do the functional division of Petri net system and the parallel analysis of Petri net process. Next, based on architecture of multi-core cluster and combined with parallelism of Petri net process, Petri net system model is ***, parallel algorithm of Petri net system is raised. Finally, under the environment of multi-core cluster,the simulation experiment of parallel algorithm is done. The experimental results show that parallel algorithm based on Petri net system model is correct and feasible. The model can effectively simulate the actual operation of the system and is an effective model of Petri net parallelization system.

关键词： Petri Net parallelism Multi-core Cluster parallel Model parallel algorithm

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parallelization of Point Operations on Conic Curves over Finite Field GF(2(n))

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INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING 2014年第3期7卷 287-298页

作者： Li, Yongnan Xiao, Limin Beihang Univ State Key Lab Software Dev Environm Beijing 100191 Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing 100191 Peoples R China

It becomes more and more important to design high-speed parallel cryptographic algorithms due to a growing need for information security. Conic curves cryptography is a new developing direction in the field of information security in recent years and there are less works focused on the parallel encryption algorithms for conic curves crypto system. This paper proposes four parallel algorithms for conic curves cryptosystem over finite field GF(2(n)). One parallel algorithm of modular-multiplication is designed by analyzing its data dependency and making some modifications of several steps. In order to figure out the average runtime, we consider the probability distributions of different cases to compute the mathematical expectation. The operations of point-addition, point-double and pointmultiplication, three fundamental point operations in conic curves cryptosystem over finite field GF(2(n)), are paralleled based on this parallel algorithm of modular-multiplication and two parallel algorithms we proposed before. Time complexities and speedup ratios of the parallel algorithms and the sequential algorithms are calculated to make the quantitative comparison. The performance evaluation shows better efficiencies of the proposed parallel algorithms compared to the traditional algorithms.

关键词： parallel algorithm Conic curves Finite field GF(2(n)) Point-addition Pointdouble Point-multiplication

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Research and Implementation of Petri nets parallelization model

Research and Implementation of Petri nets parallelization mo...

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The 13th International Symposium on Distributed Computing and Applications to Business,Engineering and Science(DCABES 2014)(第十三届分布式计算及其应用国际学术研讨会)

作者： Xuan Wang Wen-jing LI Ze-yu Tang Weizhi LIAO College of Computer and Information Engineering Guangxi Teachers Education University Nanning 530001 Guangxi Key laboratory of hybrid computation and IC design analysis Nanning 530006China

ISBN: (纸本)9781479941681

In order to solve parallel algorithm of Petri net system with concurrent functions and implement parallel control and execution of Petri net,parallel programming model of Petri net based on multi-core clusters is put ***,P-invariant technology is used to do the functional division of Petri net system and the parallel analysis of Petri net ***,based on architecture of multi-core cluster and combined with parallelism of Petri net process,Petri net system model is ***,parallel algorithm of Petri net system is ***,under the environment of multi-core cluster,the simulation experiment of parallel algorithm is *** experimental results show that parallel algorithm based on Petri net system model is correct and *** model can effectively simulate the actual operation of the system and is an effective model of Petri net parallelization system.

关键词： Petri Net parallelism Multi-core Cluster parallel Model parallel algorithm

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Feature Selection parallel Technique for Remotely Sensed Imagery Classification

Feature Selection Parallel Technique for Remotely Sensed Ima...

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13th International Conference on Computational Science and Its Applications (ICCSA)

作者： LeKhac, NhienAn Wu, Bo Chen, ChongCheng Kechadi, M-Tahar Univ Coll Dublin Sch Comp Sci & Informat Dublin 4 Ireland Fuzhou Univ Key Lab Spatial Data Mining & Informat Sharing Fuzhou Peoples R China

ISBN: (纸本)9783642396434

Remote sensing research focusing on feature selection has long attracted the attention of the remote sensing community because feature selection is a prerequisite for image processing and various applications. Different feature selection methods have been proposed to improve the classification accuracy. They vary from basic search techniques to clonal selections, and various optimal criteria have been investigated. Recently, methods using dependence-based measures have attracted much attention due to their ability to deal with very high dimensional datasets. However, these methods are based on Cramer's V test, which has performance issues with large datasets. In this paper, we propose a parallel approach to improve their performance. We evaluate our approach on hyper-spectral and high spatial resolution images and compare it to the proposed methods with a centralized version as preliminary results. The results are very promising.

关键词： feature selection parallel algorithm Cramer's V Test min-max association image classification

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parallel Performance of Numerical algorithms on Multi-core System Using OpenMP

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2nd International Conference on Advances in Computing and Informaiton Technology (ACITY 2012)

作者： Sharma, Sanjay Kumar Gupta, Kusum Banasthali Univ Banasthali Rajasthan India

ISBN: (纸本)9783642315510

The current microprocessors are concentrating on the multiprocessor or multi-core system architecture. The parallel algorithms are recently focusing on multi-core system to take full utilization of multiple processors available in the system. The design of parallel algorithm and performance measurement is the major issue on today's multi-core environment. Numerical problems arise in almost every branch of science which requires fast solution .System of linear equations has applications in fusion energy, structural engineering, ocean modeling and method of moment formulation. In this paper parallel algorithms for computing the solution of system of linear equations and approximate value of pi are presented. The parallel performance of numerical algorithms on multi-core system have been analyzed and presented. The experimental results reveal that the performances of parallel algorithms are better than sequential. We implemented the parallel algorithms using multithreading features of OpenMP.

关键词： Multi-core processors parallelization parallel computation parallel algorithm Performance analysis

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parallel Triangle Counting in Massive Streaming Graphs 13

Parallel Triangle Counting in Massive Streaming Graphs

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22nd ACM International Conference on Information and Knowledge Management (CIKM)

作者： Tangwongsan, Kanat Pavan, A. Tirthapura, Srikanta IBM Res Yorktown Hts NY 10598 USA Iowa State Univ Ames IA USA

ISBN: (纸本)9781450322638

The number of triangles in a graph is a fundamental metric widely used in social network analysis, link classification and recommendation, and more. In these applications, modern graphs of interest tend to both large and dynamic. This paper presents the design and implementation of a fast parallel algorithm for estimating the number of triangles in a massive undirected graph whose edges arrive as a stream. Our algorithm is designed for shared-memory multicore machines and can make efficient use of parallelism and the memory hierarchy. We provide theoretical guarantees on performance and accuracy, and our experiments on real-world datasets show accurate results and substantial speedups compared to an optimized sequential implementation.

关键词： triangle counting streaming algorithm parallel algorithm parallel cache oblivious (PCO) massive graphs

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A Distributed parallel AdaBoost algorithm for Face Detection

A Distributed Parallel AdaBoost Algorithm for Face Detection

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2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

作者： ZheHuang Huang Xiaodong Shi School of Mathematics Sciences Huaqiao University Quanzhou 362021 Cognitive Science Department X Cognitive Science Department Xiamen University Xiamen361005 China Fujian Key Laboratory of the Br

ISBN: (纸本)9781424465828

AdaBoost is an excellent machine-learning algorithm, which produces a strong classifier by selecting the discriminating features and combining them linearly. But the computational complexity of AdaBoost algorithms is very high that restricts its studies and applications. In this paper we utilize parallel processing techniques to implement the parallel algorithm based on AdaBoost. The experiment results show the parallel algorithm can reduce the run time and has a high speedup.

关键词： AdaBoost Face Detection parallel algorithm Distributed computing

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