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Performance analysis of a parallel algorithm for restoring large-scale CT images

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2017年第0期310卷 104-114页

作者： Harizanov, Stanislav Lirkov, Ivan Georgiev, Krassimir Paprzycki, Marcin Ganzha, Maria Bulgarian Acad Sci Inst Informat & Commun Technol Acad G BonchevBl 25A BU-1113 Sofia Bulgaria Polish Acad Sci Syst Res Inst Ul Newelska 6 PL-01447 Warsaw Poland Warsaw Univ Technol Dept Math & Informat Sci Ul Koszykowa 75 PL-00661 Warsaw Poland Warsaw Management Acad Dept Management & Tech Sci Ul Kaweczynska 36 PL-03772 Warsaw Poland

In multiple areas of image processing, such as Computed Tomography, in which data acquisition is based on counting particles that hit a detector surface, Poisson noise occurs. Using variance-stabilizing transformations, the Poisson noise can be approximated by a Gaussian one, for which classical denoising filters can be used. This paper presents an experimental performance study of a parallel implementation of the Poissonian image restoration algorithm, introduced in Harizanov et al. (2013). Hybrid parallelization based on MPI and OpenMP standards is investigated. The convergence rate of the algorithm heavily depends on both the image size and the choice of input parameters (rho, sigma), thus maximizing its, parallel efficiency is vital for real-life applications. The implementation is tested for high-resolution radiographic images, on Linux clusters with Intel processors and on an IBM supercomputer. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Primal-dual algorithm Anscombe transform Image restoration parallel algorithm Epigraphical projection

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A parallel algorithm FOR CONSTRAINED OPTIMIZATION PROBLEMS

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 1995年第2期61卷 225-230页

作者： ZHONG, C FEI, PS WUHAN UNIV DEPT MATHWUHAN 430072PEOPLES R CHINA

Starting from the idea introduced by Hestenes (1969) and Pardalos et al. (1993) in this paper we describe an asynchronous parallel algorithm for solving constrained optimization problems by means of augmented Lagrange multiplier methods. Under suitable assumptions, we discuss convergence of this algorithm. Finally we show the numerical results of this algorithm.

关键词： parallel algorithm CONSTRAINED OPTIMIZATION MULTIPLIER METHOD

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A neural network parallel algorithm for meeting schedule problems

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APPLIED INTELLIGENCE 1997年第3期7卷 205-213页

作者： Tsuchiya, K Takefuji, Y KEIO UNIV FAC ENVIRONM INFORMAT FUJISAWA KANAGAWA 252 JAPAN CASE WESTERN RESERVE UNIV DEPT ELECT ENGN & APPL PHYS CLEVELAND OH 44106 USA

A parallel algorithm for solving meeting schedule problems is presented in this paper where the problem is NP-complete. The proposed system is composed of two maximum neural networks which interact with each other. One is an M x S neural network to assign meetings to available time slots on a timetable where M and S are the number of meetings and the number of time slots, respectively The other is an M x P neural network to assign persons to the meetings where P is the number of persons. The simulation results show that the state of the system always converges to one of the solutions. Our empirical study shows that the solution quality of the proposed algorithm does not degrade with the problem size.

关键词： neural network parallel algorithm scheduling meeting schedule

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A cost optimal parallel algorithm for weighted distance transforms

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parallel COMPUTING 1999年第4期25卷 405-416页

作者： Fujiwara, A Inoue, M Masuzawa, T Fujiwara, H Kyushu Inst Technol Dept Comp Sci & Elect Iizuka Fukuoka 8208502 Japan Nara Inst Sci & Technol Grad Sch Informat Sci Nara 6300101 Japan

The distance transform and the nearest feature transform are useful operations in image processing. These transforms are based on various kinds of distance functions because the distance functions have different efficiency or usefulness. In this paper, we consider these transforms based on the weighted distance, which is a generalization of many distances, such as city block, chessboard and chamfer distances. This paper presents a parallel algorithm for these transforms of an n x n binary image. The algorithm runs in O(log n) time using n(2)/log n processors on the EREW PRAM and in O(log log n) time using n(2)/log log n processors on the common CRCW PRAM. The algorithm also runs in O(n(2)/p(2) + n) time on a p x p mesh and in O(n(2)/p(2) + (n log p)/p) time on a p(2) processor hypercube (for 1 less than or equal to p less than or equal to n). From these complexities, the algorithm is cost optimal on all models. Also we obtained an Omega(log n) lower bound for the transform on the CREW PRAM. This implies that the algorithm is time optimal on the EREW PRAM. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： parallel algorithm distance transform nearest feature transform PRAM mesh hypercube

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A parallel algorithm for constructing Voronoi diagrams based on point-set adaptive grouping

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2014年第2期26卷 434-446页

作者： Wang, Jiechen Cui, Can Rui, Yikang Cheng, Liang Pu, Yingxia Wu, Wenzhou Yuan, Zhenyu Nanjing Univ Jiangsu Prov Key Lab Geog Informat Sci & Technol Nanjing 210093 Jiangsu Peoples R China Univ Utrecht Fac Geosci Urban & Reg Res Ctr Utrecht NL-3584 CS Utrecht Netherlands Royal Inst Technol S-10044 Stockholm Sweden Inst Geog Sci & Nat Resources Res State Key Lab Resources & Environm Informat Syst Beijing 100101 Peoples R China

This paper presents a parallel algorithm for constructing Voronoi diagrams based on point-set adaptive grouping. The binary tree splitting method is used to adaptively group the point set in the plane and construct sub-Voronoi diagrams for each group. Given that the construction of Voronoi diagrams in each group consumes the majority of time and that construction within one group does not affect that in other groups, the use of a parallel algorithm is *** constructing the sub-Voronoi diagrams, we extracted the boundary points of the four sides of each sub-group and used to construct boundary site Voronoi diagrams. Finally, the sub-Voronoi diagrams containing each boundary point are merged with the corresponding boundary site Voronoi diagrams. This produces the desired Voronoi diagram. Experiments demonstrate the efficiency of this parallel algorithm, and its time complexity is calculated as a function of the size of the point set, the number of processors, the average number of points in each block, and the number of boundary points. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： Voronoi diagrams parallel algorithm adaptive grouping geographical information system computational geometry

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A parallel algorithm for linear programs with an additional reverse convex constraint

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JOURNAL OF parallel AND DISTRIBUTED COMPUTING 1997年第2期45卷 91-103页

作者： Liu, SM Papavassilopoulos, GP Ind Technol Res Inst Optoelect & Syst Labs Chutung 310 Taiwan Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA

A parallel method for globally minimizing a linear program with an additional reverse convex constraint is proposed which combines the outer approximation technique and the cutting plane method. Basically p (less than or equal to n) processors are used for a problem with a variables and a globally optimal solution is found effectively in a finite number of steps. Computational results are presented for test problems with a number of variables up to 80 and 63 linear constraints (plus nonnegativity constraints). These results were obtained on a distributed-memory MIMD parallel computer, DELTA, by running both serial and parallel algorithms with double precision. Also, based on 40 randomly generated problems of the same size, with 16 variables and 32 linear constraints (plus x greater than or equal to 0), the numerical results from different number processors are reported, including the serial algorithm's. (C) 1997 Academic Press.

关键词： reverse convex constraint linear program global optimization parallel algorithm

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An efficient parallel algorithm for the layered planar monotone circuit value problem

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algorithmICA 1997年第3期18卷 384-404页

作者： Ramachandran, V Yang, HH Department of Computer Sciences University of Texas at Austin Austin TX 78712 USA. vlr@cs.utexas.edu. yanghh@cs.utexas.edu. US

A planar monotone circuit (PMC) is a Boolean circuit that can be embedded in the plane and that contains only AND and OR gates. A layered PMC is a PMC in which all input nodes are in the external face, and the gates can be assigned to layers in such a way that every wire goes between gates in successive layers. Goldschlager, Cook and Dymond, and others have developed NC2 algorithms to evaluate a layered PMC when the output node is in the same face as the input nodes. These algorithms require a large number of processors (Omega(n(6)), where n is the size of the input circuit). In this paper we give an efficient parallel algorithm that evaluates a layered PMC of size n in O (log(2)n) time using only a linear number of processors on an EREW PRAM. Our parallel algorithm is the best possible to within a polylog factor, and is a substantial improvement over the earlier algorithms for the problem.

关键词： circuit value problem planar monotone circuit plant graph parallel algorithm EREW PRAM

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A parallel algorithm for static slicing of concurrent programs

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2004年第8期16卷 751-769页

作者： Goswami, D Mall, R Indian Inst Technol Dept Comp Sci & Engn Gauhati India Indian Inst Technol Dept Comp Sci & Engn Kharagpur W Bengal India

Slicing of concurrent programs is a compute-intensive task. To speed up the slicing process, we have developed a parallel algorithm. For this purpose we used the concurrent control flow graph (CCFG) as the intermediate representation. We used a network of communicating processes to develop our parallel algorithm. We have implemented our parallel algorithm and the experimental results appear promising. Copyright (C) 2004 John Wiley Sons, Ltd.

关键词： program slicing static slicing process network program representation parallel algorithm concurrent program

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A parallel algorithm for accurate dot product

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parallel COMPUTING 2008年第6-8期34卷 392-410页

作者： Yamanaka, N. Ogita, T. Rump, S. M. Oishi, S. Waseda Univ Grad Sch Sci & Engn Tokyo 1698555 Japan Tokyo Womans Christian Univ Dept Math Tokyo 1678555 Japan Waseda Univ Fac Sci & Engn Tokyo 1698555 Japan Hamburg Univ Tcchnol Inst Reliable Comp D-21071 Hamburg Germany

parallel algorithms for accurate summation and dot product are proposed, They are parallelized versions of fast and accurate algorithms of calculating sum and dot product using error-free transformations which are recently proposed by Ogita et al. [T. Ogita, S.M. Rump, S. Oishi, Accurate sum and dot product, SIAM J. Sci. Comput. 26 (6) (2005) 1955-1988]. They have shown their algorithms are fast in terms of measured computing time. However, due to the strong data dependence in the process of their algorithms, it is difficult to parallelize them. Similarly to their algorithms, the proposed parallel algorithms in this paper are designed to achieve the results as if computed in K-fold working precision with keeping the fastness of their algorithms. Numerical results are presented showing the performance of the proposed parallel algorithm of calculating dot product. (C) 2008 Elsevier B.V. All rights reserved.

关键词： parallel algorithm accurate dot product accurate summation higher precision

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A new parallel algorithm for vertex priorities of data flow acyclic digraphs

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JOURNAL OF SUPERCOMPUTING 2014年第1期68卷 49-64页

作者： Mo, Zeyao Zhang, Aiqing Yang, Zhang Inst Appl Phys & Computat Math Lab Computat Phys Beijing 100088 Peoples R China

Data flow acyclic directed graphs (digraph) are widely used to describe the data dependency of mesh-based scientific computing. The parallel execution of such digraphs can approximately depict the flowchart of parallel computing. During the period of parallel execution, vertex priorities are key performance factors. This paper firstly takes the distributed digraph and its resource-constrained parallel scheduling as the vertex priorities model, and then presents a new parallel algorithm for the solution of vertex priorities using the well-known technique of forward-backward iterations. Especially, in each iteration, a more efficient vertex ranking strategy is proposed. In the case of simple digraphs, both theoretical analysis and benchmarks show that the vertex priorities produced by such an algorithm will make the digraph scheduling time converge non-increasingly with the number of iterations. In other cases of non-simple digraphs, benchmarks also show that the new algorithm is superior to many traditional approaches. Embedding the new algorithm into the heuristic framework for the parallel sweeping solution of neutron transport applications, the new vertex priorities improve the performance by 20 % or so while the number of processors scales up from 32 to 2048.

关键词： Acyclic digraph parallel algorithm Neutron transport

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