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18th International Conference on Geoinformatics

作者： Wang, Hongping Zhang, Juan Liu, Xiuguo Huang, Xiaodong China Univ Geosci Fac Informat Engn Wuhan 430074 Peoples R China

ISBN: (纸本)9781424473021

In the PC cluster environment, parallel algorithms can significantly improve the efficiency of remote sensing image processing. The remote sensing dataset is the raster data stored by order of band, therefore, it is feasible to assign executable tasks to some computing nodes by band and complete the processing tasks together through communicating each other amount the computing nodes by MPI interface. In addition, the multi-thread processing algorithm is scheduled based on OpenMP library toward the single computing node with multi-core CPU. The experiment evaluates image radiation performance about the four-band HJ-1A CCD remote sensing image in the PC cluster environment which consists of 4 sets of dual-core computers. Its performance is increased by 6 times to 6.5 times comparing with a single PC. Through validating, the dual level design pattern is available based on integrating MPI and OpenMP to improve the efficiency of remote sensing image processing.

关键词： parallel algorithm Remote Sensing Image Processing MPI OpenMP PC Cluster Environment

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Optimal parallel algorithm for the Knapsack Problem Without Memory Conflicts

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Journal of Computer Science & Technology 2004年第6期19卷 760-768页

作者： Ken-LiLi Ren-FaLi Qing-HuaLi SchoolofComputerandCommunication HunanUniversityChangsha410082P.R.China SchoolofComputerScienceandTechnology HuazhongUniversityofScienceandTechnologyWuhan430074P.R.China

The knapsack problem is well known to be NP-complete. Due to its importance in cryptosystem and in number theory, in the past two decades, much effort has been made in order to find techniques that could lead to practical algorithms with reasonable running time. This paper proposes a new parallel algorithm for the knapsack problem where the optimal merging algorithm is adopted. The proposed algorithm is based on anEREW-SIMD machine with shared memory. It is proved that the proposed algorithm is both optimal and the first without memory conflicts algorithm for the knapsack problem. The comparisons of algorithm performance show that it is an improvement over the past researches. Keywords knapsack problem - NP-complete - parallel algorithm - optimal algorithm - memory conflict Supported by the National Natural Science Foundation of China under Grant No.60273075, the National High Technology Development 863 Program of China under Grant No.863-306-ZD-11-01-06. Ken-Li Li received his B.S. and M.S. degrees in mathematics from National University of Defense Technology and Central South University in 1995 and 2000 respectively and he is now a Ph.D. candidate in computer software and theory at Huazhong University of Science and Technology. His main research interests include parallel computing and combinatorial optimization. Ren-Fa Li received his Ph.D. degree in computer software and theory at Huazhong University of Science and Technology, and he is concurrently a professor and Ph.D. supervisor in School of Computer and Communication, Human University. His main research interests include network computing. Qing-Hua Li received his M.S. degree in computer science from Huazhong University of Science and Technology in 1981, and he is concurrently a professor and Ph.D. supervisor in School of Computer Science and Technology, Huazhong University of Science and Technology. His current research interests include parallel processing, combinatorial optimization, and grid comp

关键词： knapsack problem NP-complete parallel algorithm optimal algorithm memory conflict

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parallel algorithm for Solving the System of Simultaneous Linear Equations by Jacobi Method on Extended Fibonacci Cubes

Parallel Algorithm for Solving the System of Simultaneous Li...

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3rd IEEE International Advance Computing Conference (IACC)

作者： Tripathy, Alok Ranjan Ray, B. N. B. Coll Engn Bhubaneswar Dept Comp Sci & Engn Bhubaneswar 751024 Orissa India Utkal Univ Dept Comp Sci & Applicat Bhubaneswar 751004 Orissa India

ISBN: (纸本)9781467345286

This work suggests parallel algorithms for solving a sparse system of N - linear equations in N - unknowns by Jacobi method on Extended Fibonacci Cube EFC1(n) [3]. Where n is the degree of EFC1(n) and N is the number of processors of EFC1(n). Two parallel versions of the algorithm are discussed. The single pass of the first algorithm involves 2 (N - 1) data communications in N steps. Whereas the second algorithm achieves the same number of data communications in N/2 + logN steps. Further each pass of both algorithms have 3N/2 + 1 additions, N/2 - 1 subtractions, N - 1 multiplications and N divisions.

关键词： Jacobi Method Hamiltonian cycle Extended Fibonacci Cube parallel algorithm

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parallel algorithm for Binomial Series(Special Cases) Using Mesh Architecture

Parallel Algorithm for Binomial Series(Special Cases) Using ...

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2nd IEEE International Conference on parallel, Distributed and Grid Computing (PDGC)

作者： Gupta, Ashish Indian Sch Mines Dept Comp Sci & Engn Dhanbad 826004 Jharkhand India

ISBN: (纸本)9781467329255

In this paper we map a well known mathematical equation called Binomial function on popular mesh architecture in parallel manner. Binomial function is very useful in real time applications such as forecasting, computing profit and loss, defining ranks of students and probability analysis etc. We present here a parallel algorithm for special cases of Binomial Series. This parallel algorithm takes 10( n - 1) + O( 1) steps for mapping of special cases of Binomial Series of n(2) + 1 terms on nxn Mesh Architecture.

关键词： parallel algorithm Binomial Series Time complexity

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An efficient parallel algorithm for DNS of buoyancy-driven turbulent flows

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Journal of Hydrodynamics 2019年第6期31卷 1159-1169页

作者： Yi-zhao Zhang Shu-ning Xia Yu-hong Dong Bo-fu Wang Quan Zhou Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai Institute of Applied Mathematics and MechanicsSchool of Mechanics and Engineering ScienceShanghai UniversityShanghai 200072China

In this paper,an explicit low-storage simplified M-stage Runge-Kutta(SRK)scheme for high Reynolds-number incompressible flows is *** the SRK scheme,the Poisson equation is solved only once in the final substage of each time *** taking advantage of the SRK scheme and the advanced hybrid MPI+MPI model,we have developed an efficient parallel solver for buoyancy-driven turbulent *** spatial and temporal accuracies of the solver are validated with Taylor-Green vortex *** the RK and SRK schemes are implemented for the simulation of turbulent Rayleigh-Benard convection as well as Rayleigh-Taylor *** results show that the SRK scheme can save approximately 20%of the computation time.

关键词： Direct numerical simulation(DNS) parallel algorithm turbulent flows

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On the convergence of asynchronous parallel algorithm for large-scale linearly constrained minimization problem

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APPLIED MATHEMATICS AND COMPUTATION 2009年第2期211卷 434-441页

作者： Han, Congying Wang, Yongli He, Guoping Shandong Univ Sci & Technol Sch Informat Sci & Engn Qingdao 266510 Shandong Peoples R China

As a synchronization parallel framework, the parallel variable transformation (PVT) algorithm is effective to solve unconstrained optimization problems. In this paper, based on the idea that a constrained optimization problem is equivalent to a differentiable unconstrained optimization problem by introducing the Fischer Function, we propose an asynchronous PVT algorithm for solving large-scale linearly constrained convex minimization problems. This new algorithm can terminate when some processor satisfies terminal condition without waiting for other processors. Meanwhile, it can enhances practical efficiency for large-scale optimization problem. Global convergence of the new algorithm is established under suitable assumptions. And in particular, the linear rate of convergence does not depend on the number of processors. Crown Copyright (c) 2009 Published by Elsevier Inc. All rights reserved.

关键词： parallel algorithm Constrained convex optimization Nonlinear programming Large-scale minimization

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An exact parallel algorithm to compare very long biological sequences in clusters of workstations

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2007年第2期10卷 187-202页

作者： Boukerche, Azzedine Magalhaes, Alba Cristina de Melo, Alves Sandes, Edans Flavius de Oliveira Ayala-Rincon, Mauricio Univ Ottawa SITE Ottawa ON Canada Univ Brasilia Brasilia DF Brazil

Biological Sequence Comparison is one of the most important operations in Computational Biology since it is used to determine how similar two sequences are. Smith and Waterman proposed an exact algorithm (SW), based on dynamic programming, that is able to obtain the best local alignment between two sequences in quadratic time and space. In order to compare long biological sequences, SW is rarely used since the computation time and the amount of memory required becomes prohibitive. For this reason, heuristic methods like BLAST are widely used. Although faster, these heuristic methods do not guarantee that the best result will be produced. In this paper, we propose an exact parallel variant of the SW algorithm that obtains the best local alignments in quadratic time and reduced space. The results obtained in two clusters (8-machine and 16-machine) for DNA sequences longer than 32 KBP (kilo base-pairs) were very close to linear and, in some cases, superlinear. For very Iona DNA sequences (1.6 MBP), we were able to reduce execution time from 12.25 hours to 1.54 hours, in our 8-machine cluster. As far as we know, this is the first time 1.6 MBP sequences are compared with an exact SW variant. In this case, 30240 best local alignments were obtained.

关键词： biological sequence comparison parallel algorithm

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Fine-grained parallel algorithm for unstructured surface mesh generation

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COMPUTERS & STRUCTURES 2015年 154卷 177-191页

作者： Zhao, Dawei Chen, Jianjun Zheng, Yao Huang, Zhengge Zheng, Jianjing Zhejiang Univ Ctr Engn & Sci Computat Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Sch Aeronaut & Astronaut Hangzhou 310027 Zhejiang Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SA2 8PP W Glam Wales

A parallel surface meshing algorithm is proposed by exploiting the parallelism within the meshing process of a surface, which is more efficient than the conventional scheme that meshes surfaces individually. One integral part is the domain decomposition approach adopted, which ensures no small inter-domain angles;therefore, the parallel meshing procedure can fix the inter-domain boundary without compromising mesh quality. Combining the parallel surface mesher with the parallel tetrahedral mesher and improver developed previously, a parallel preprocessing pipeline for large-scale simulations is set up. It only consumes minutes to prepare a mesh containing hundreds of millions of elements. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Mesh generation parallel algorithm Surface mesh Domain decomposition Graph partitioning

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UNIFIED parallel algorithm FOR GRID ADAPTATION ON A MULTIPLE-INSTRUCTION MULTIPLE-DATA ARCHITECTURE

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AIAA JOURNAL 1994年第9期32卷 1800-1807页

作者： VIDWANS, A KALLINDERIS, Y UNIV TEXAS DEPT AEROSP ENGN & ENGN MECHAUSTINTX 78712

A unified parallel algorithm for grid adaptation by local refinement/coarsening is presented. It is designed to be independent from the type of the grid. This is achieved by employing a generic data template that can be configured to capture the data structures for any computational grid regardless of structure and dimensionality. Furthermore, the algorithm itself is specified in terms of generic parallel primitives that are completely independent of the underlying parallel architecture. The unified parallel algorithm is employed for dynamic adaptation of three-dimensional unstructured tetrahedral grids on a partitioned memory multiple-instruction multiple-data architecture. Performance results are presented for the Intel iPSC/860.

关键词： parallel algorithm Unstructured Grid Blast Wave Navier Stokes algorithm parallel Computers parallel Computing Transonic Flow Interprocessor Communication Adaptive Grid algorithms Navier Stokes Equations

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parallel algorithm for Minimum Partial Dominating Set in Unit Disk Graph 15th

Parallel Algorithm for Minimum Partial Dominating Set in Uni...

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15th Annual International Conference on Combinatorial Optimization and Applications (COCOA)

作者： Hong, Weizhi Zhang, Zhao Ran, Yingli Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321004 Zhejiang Peoples R China

ISBN: (纸本)9783030926816;9783030926809

In this paper, we consider the minimum partial dominating set problem in unit disk graphs (MinPDS-UD). Given a set of points V on the plane with vertical bar V vertical bar = n, two points in V are adjacent in the unit disk graph if their Euclidean distance is no larger than one unit length. A point dominates itself and all its neighboring points. For an integer k <= n, the goal of MinPDS-UD is to find a minimum subset of points D subset of V such that at least k points are dominated by D. We present the first parallel algorithm for MinPDS-UD. It runs in O(log n) rounds on O(n) machines, and achieves a constant approximation ratio.

关键词： Partial dominating set Unit disk graph parallel algorithm Approximation ratio

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