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parallel algorithm implementation for multi-object tracking and surveillance

IET COMPUTER VISION 2016年第3期10卷 202-211页

作者： Elbahri, Mohamed Taleb, Nasreddine Kpalma, Kidiyo Ronsin, Joseph Univ Djillali Liabes Sidi Bel Abbes Dept Comp Sci Sidi Bel Abbes Algeria Univ Djillali Liabes Sidi Bel Abbes Dept Elect RCAM Lab Sidi Bel Abbes Algeria UEB INSA IETR Dept Image & Automat F-35708 Rennes France

A recently developed sparse representation algorithm, has been proved to be useful for multi-object tracking and this study is a proposal for developing its parallelisation. An online dictionary learning is used for object recognition. After detection, each moving object is represented by a descriptor containing its appearance features and its position feature. Any detected object is classified and indexed according to the sparse solution obtained by an orthogonal matching pursuit (OMP) algorithm. For a real-time tracking, the visual information needs to be processed very fast without reducing the results accuracy. However, both the large size of the descriptor and the growth of the dictionary after each detection, slow down the system process. In this work, a novel accelerating OMP algorithm implementation on a graphics processing unit is proposed. Experimental results demonstrate the efficiency of the parallel implementation of the used algorithm by significantly reducing the computation time.

关键词： parallel algorithms Tracking algorithms Orthogonal matching pursuit Feature extraction (Data processing) Computer software

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parallel Identification of Power System Dynamic Models Under Scheduling Constraints

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IEEE TRANSACTIONS ON POWER SYSTEMS 2016年第6期31卷 4584-4594页

作者： Xue, Nan Chakrabortty, Aranya North Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA

In this paper we present two sets of parallel algorithms for identifying real-time, small-signal dynamic models of power systems using multiple sources of Synchrophasor data. The first problem is posed in terms of identifying the transfer matrix of single-input multiple-output (SIMO) power system models using linear least-squares (LLS), where parallelism can be implemented through parallel execution of matrix multiplications using multiple processors or workers. Given the constraints of sequential communication and limited local memory, which may arise due to multiple applications running in the workers at the same time, a novel scheduling algorithm is proposed to enable flexible deadlines that meet these constraints. The scheduling algorithm minimizes the total time of execution under constraints, and can be solved via integer programming. The second problem is posed as a similar parallel algorithm for identifying a linearized state-variable (SV) model of a power system using both linear and nonlinear least-squares (NLS) in presence of scheduling. The performance of all the algorithms are studied via simulations of an IEEE 145-bus, 50-machine power system model, and compared with their centralized, non-parallel implementation.

关键词： parallel algorithms system identification least-squares integer programming synchrophasor

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Efficient parallel Sorting for Migrating Birds Optimization When Solving Machine-Part Cell Formation Problems

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SCIENTIFIC PROGRAMMING 2016年第1期2016卷 1-40页

作者： Soto, Ricardo Crawford, Broderick Almonacid, Boris Paredes, Fernando Pontificia Univ Catolica Valparaiso Valparaiso 2362807 Chile Univ Autonoma Chile Santiago 7500138 Chile Univ Cient Sur Lima 18 Peru Univ Cent Chile Santiago 8370178 Chile Univ San Sebastian Santiago 8420524 Chile Univ Diego Portales Santiago 8370109 Chile

The Machine-Part Cell Formation Problem (MPCFP) is a NP-Hard optimization problem that consists in grouping machines and parts in a set of cells, so that each cell can operate independently and the intercell movements are minimized. This problem has largely been tackled in the literature by using different techniques ranging from classic methods such as linear programming to more modern nature-inspired metaheuristics. In this paper, we present an efficient parallel version of the Migrating Birds Optimization metaheuristic for solving the MPCFP. Migrating Birds Optimization is a population metaheuristic based on the V-Flight formation of the migrating birds, which is proven to be an effective formation in energy saving. This approach is enhanced by the smart incorporation of parallel procedures that notably improve performance of the several sorting processes performed by the metaheuristic. We perform computational experiments on 1080 benchmarks resulting from the combination of 90 well-known MPCFP instances with 12 sorting configurations with and without threads. We illustrate promising results where the proposal is able to reach the global optimum in all instances, while the solving time with respect to a nonparallel approach is notably reduced.

关键词： MACHINE parts parallel algorithms PARTICLE swarm optimization METAHEURISTIC algorithms PERFORMANCE evaluation

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Parameter estimation of photovoltaic model via parallel particle swarm optimization algorithm

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2016年第3期40卷 343-352页

作者： Ma, Jieming Man, Ka Lok Guan, Sheng-Uei Ting, T. O. Wong, Prudence W. H. Suzhou Univ Sci & Technol Sch Elect & Informat Engn 1 Ke Rui RdSuzhou High Tech Zone Suzhou 215009 Jiangsu Peoples R China Xian Jiaotong Liverpool Univ Dept Comp Sci & Software Engn CSSE Sci Bldg111 Renai RdSuzhou Ind Pk Suzhou 215123 Jiangsu Peoples R China Xian Jiaotong Liverpool Univ Dept Elect & Elect Engn EEE Sci Bldg111 Renai RdSuzhou Ind Pk Suzhou 215123 Jiangsu Peoples R China Univ Liverpool Dept Comp Sci Ashton BldgAshton St Liverpool L69 3BX Merseyside England

Recently, bio-inspired metaheuristic algorithms have been widely used as powerful optimization tools to estimate crucial parameters of photovoltaic (PV) models. However, the computational cost involved in terms of the time increases as data size or the complexity of the applied PV electrical model increases. Hence, to overcome these limitations, this paper presents the parallel particle swarm optimization (PPSO) algorithm implemented in Open Computing Language (OpenCL) to solve the parameter estimation problem for a wide range of PV models. Experimental and simulation results demonstrate that the PPSO algorithm not only has the capability of obtaining all the parameters with extremely high accuracy but also dramatically improves the computational speed. This is possible and is shown in this work via the inherent capabilities of the parallel processing framework. Copyright (C) 2015 John Wiley & Sons, Ltd.

关键词： photovoltaic cells modeling parameter estimation parallel algorithms solar energy

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parallel-computing-based implementation of fast algorithms for discrete Gabor transform

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IET SIGNAL PROCESSING 2015年第7期9卷 546-552页

作者： Lin, Chen Tao, Liang Kwan, Hon Keung Anhui Univ Sch Comp Sci & Technol MOE Key Lab Intelligent Comp & Signal Proc Hefei 230039 Anhui Peoples R China Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada

parallel-computing-based implementation of the two recent fast parallel algorithms for the discrete Gabor transform (DGT) is presented in this paper. First of all, the first existing block time-recursive DGT algorithm with parallel lattice structure is analysed, and then an improved implementation method under a parallel computing environment is presented. Each parallel channel (i.e. process in parallel computing) in the improved method is independent, thereby reducing the interprocess communication by 99.2% on average over the original algorithm. Second, the second existing fast parallel DGT algorithm based on multirate filtering is analysed. Through the use of parallel computing, the communication overhead of the multirate filtering-based parallel DGT algorithm is optimised and its time efficiency is raised from 31.26 times to 54.52 times faster than the serial fast DGT algorithm in processing of long sequences. Finally, the experimental results are compared and analysed, which indicate that the proposed fast DGT implementation methods are attractive for real-time signal processing.

关键词： parallel algorithms Gabor filters discrete transforms filtering theory parallel-computing-based implementation discrete Gabor transform block time-recursive DGT algorithm parallel lattice structure parallel channel interprocess communication fast parallel DGT algorithm multirate filtering communication overhead real-time signal processing

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parallel in/out systolic AB² architecture with low complexity in GF(2^m)

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ELECTRONICS LETTERS 2016年第13期52卷 1138-1139页

作者： Choi, S-H. Lee, K-J. Kyungpook Natl Univ Sch Architectural Civil Environm & Energy Engn Daegu 41566 South Korea

Efficient GF(2(m)) arithmetic clearly affects the performance of compute-intensive applications. A new low-complexity parallel-in/out systolic AB(2) multiplier based on the least significant bit-first scheme is presen... 详细信息

关键词： multiplying circuits parallel algorithms systolic arrays compute-intensive application least significant bit-first scheme low-complexity parallel-in-out systolic AB2 multiplier architecture lower area-time complexity

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parallel acceleration of HEVC decoder based on CPU+GPU heterogeneous platform

Parallel acceleration of HEVC decoder based on CPU+GPU heter...

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International Conference on Information Science and Technology (ICIST)

作者： Aidi Ma Chengan Guo School of Information and Communication Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9781509054022

The High Efficiency Video Coding (HEVC) standard, as the newest generation video coding standard issued in 2013, significantly improves compression performance relative to existing standards in about 50% bit-rate reduction for equal perceptual video quality with the cost of greatly increasing the computation complexity of the encoder/decoder. In order to improve the decoding efficiency, we design a set of parallel decoding algorithms based on the CPU+GPU heterogeneous platform for the HEVC decoder, in which, the reconstruction processes with high computation complexity, including the inverse quantization (IQ), the inverse discrete cosine transformation (IDCT), the intra/inter decoder, the de-blocking filter (DF), and the sample adaptive offset (SAO), are processed by GPU in parallel, while the network abstract layer (NAL) bit stream parsing and the CABAC bit stream decoding are processed by CPU using serial algorithms on account that they are not suitable for parallel implementation due to their internally contextual relevance. We implement the parallel algorithms by using the compute unified device architecture (CUDA) and test them with various video sequences. The experimental results show that our method can achieve a significant improvement on the computation efficiency for the whole decoding processes and can achieve real-time decoding with more than 39 frames per second for HD videos.

关键词： Decoding parallel algorithms Quantization (signal) Standards Graphics processing units Algorithm design and analysis Streaming media

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Primal-Dual parallel Algorithm for Optimal Content Delivery in Cloud CDNs

Primal-Dual Parallel Algorithm for Optimal Content Delivery ...

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IEEE International Conference on Computational Intelligence and Computing Research

作者： Gadiraju Mahesh V V R Maheswara Rao R Shiva Shankar GN V G Sirisha Dept. of C.S.E. S.R.K.R. Engineering College Bhimavaram A.P. India Dept. of C.S.E. Shri Vishnu Engineering College for Women Bhimavaram A.P. India

ISBN: (纸本)9781509066223

Content delivery networks have been providing content delivery services for the last two decades using their own infrastructure. Now-a-days content delivery networks have the better option of using storage cloud sites as edge servers. The problems of replicating the content required by the users on optimal sites in Cloud and assigning the sites to users are considered in this work. Given a set of current user requests and cloud sites potential to the user, the combined problem of finding the optimal sites for content placement and content dissemination is set-cover problem. The Previous works solved this problem by using greedy algorithm. Primal-dual parallel algorithm for optimal content delivery in Cloud content delivery networks is proposed in this work. The proposed algorithm is an efficient parallel algorithm that requires only local information. Primal-dual algorithm takes less time than greedy algorithm and the experimental results demonstrate the fact.

关键词： Servers Cloud computing Greedy algorithms Approximation algorithms parallel algorithms Content distribution networks Topology

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parallel multi-splitting proximal method for star networks

Parallel multi-splitting proximal method for star networks

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American Control Conference

作者： Ermin Wei Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60202 United States of America

ISBN: (纸本)9781509045839

We develop a parallel algorithm based on proximal method to solve the problem of minimizing summation of convex (not necessarily smooth) functions over a star network. We show that this method converges to an optimal solution for any choice of constant stepsize for convex objective functions. Under further assumption of Lipschitz-gradient and strong convexity of objective functions, the method converges linearly.

关键词： choice constant stepsize step size Star networks Constants Objective function Convexity parallel algorithms optimal solution

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Alphabet-dependent parallel algorithm for suffix tree construction for pattern searching

arXiv

引用

arXiv 2017年

作者： Kaniwa, Freeson Kuthadi, Venu Madhav Dinakenyane, Otlhapile Schroeder, Heiko Botswana International University of Science and Technology

Suffix trees have recently become very successful data structures in handling large data sequences such as DNA or Protein sequences. Consequently parallel architectures have become ubiquitous. We present a novel alphabet-dependent parallel algorithm which attempts to take advantage of the perverseness of the multicore architecture. Microsatellites are important for their biological relevance hence our algorithm is based on time efficient construction for identification of such. We experimentally achieved up to 15x speedup over the sequential algorithm on different input sizes of biological sequences. Copyright © 2017, The Authors. All rights reserved.

关键词： parallel algorithms

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