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

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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A parallel algorithm for multi-AGV systems

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2022年第4期13卷 2309-2323页

作者： Yu, Dingding Hu, Xianliang Liang, Kewei Ying, Jun Zhejiang Univ Inst Sci & Engn Comp Hangzhou 310027 Peoples R China Zhejiang Univ Inst Stat Inst Sci & Engn Comp Hangzhou 310027 Peoples R China Shanghai Normal Univ Coll Informat Mech & Elect Engn Shanghai 200234 Peoples R China

Automated guided vehicles are widely used in various applications, especially in manufacturing. In this paper, we present a novel parallel algorithm for multi-AGV systems. The overall structure is composed of three parts: task assignment, path planning, and vehicle navigation. According to the priorities of AGVs, a greedy method is introduced to assign jobs. For path planning, a mixed-integer programming model of a multi-AGV system is formulated, which can be transformed into a series of sub-problems under certain conditions. Then, an improved routing method with a penalty item is adopted to generate the optimal paths of AGVs. To avoid collisions between vehicles, a simple and effective control method based on resource locking is proposed under the premise of parallelization. Furthermore, we design the experiments according to the warehousing systems. Various practical simulations are performed to illustrate the efficiency and robustness of the new algorithm.

关键词： Multi-AGV system parallel algorithm Path planning Vehicle navigation

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A parallel algorithm for three-dimensional numerical manifold elements generation

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ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS 2024年 163卷 448-464页

作者： Yi, Xiongwei Tan, Fei Tong, Defu Jiao, Yuyong China Univ Geosci Badong Natl Observat & Res Stn Geohazards Wuhan 430074 Peoples R China China Univ Geosci Fac Engn Wuhan 430074 Peoples R China

Numerical Manifold Method (NMM) has gained widespread application in engineering practice due to its capacity to effectively address both continuous and discontinuous problems in a unified framework. With the advancement of 3D-NMM, there remains a deficiency in ready-made preprocessing tools. Hence, the generation of 3D manifold elements (MEs) is the primary prerequisite for 3D-NMM. In this study, a parallel algorithm to generate the MEs is proposed. Firstly, a novel 3D block identification algorithm is developed to improve the modeling efficiency. Then, 3D joint networks are simulated using the geological statistical results. Thirdly, the mathematical cover system is constructed using uniformly regular hexahedral meshes. Subsequently, the physical domain is cut using the Boolean algorithm to generate the related manifold blocks (MBs) and the Union -Find algorithm is used to determine the relationship of MBs with mathematical patches (MPs) and physical patches (PPs). The proposed program incorporates the OpenMP parallel library for CPU parallelization to enhance its efficiency and the OpenGL library is used to build a real-time visualization program. Finally, the proposed program is validated using several representative examples, and the obtained results demonstrate its efficient capability in generating MEs.

关键词： 3D numerical manifold method Block identification parallel algorithm Manifold elements Union-Find algorithm

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K-Dimensional Optimal parallel algorithm for the Solution of a General Class of Recurrence Equations

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Journal of Computer Science & Technology 1995年第5期10卷 417-424页

作者：高庆狮刘志勇 The Institute of Intelligence Language and Computer Science Beijing University of Science and Technology Beijing Institute of Computing Technology The Chinese Academy of Sciences Beijing

This paper proposes a parallel algorithm, called KDOP (K-DimensionalOptimal parallel algorithm), to solve a general class of recurrence equations efficiently. The KDOP algorithm partitions the computation into a series of sub-computations, each of which is executed in the fashion that all the processors work simultaneously with each one executing an optimal sequential algorithm to solve a subcomputation task. The algorithm solves the equations in O(N/p)steps in EREW PRAM model (Exclusive Read Exclusive Write parallel Ran-dom Access Machine model) using palgorithm (itsspeedup is O(p)) in the case of palgorithm can be implemented on machines with multiple processing elements or pipelined vector machines with parallel memory systems.

关键词： parallel algorithm optimal algorithm first-order linear recurrence equations recursive doubling algorithm tridiagonal systems of linear equations

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A convergence result for a parallel algorithm for solving the Navier-Stokes equations

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 1998年第4期35卷 71-88页

作者： Soto, JLC Canalejo, MCC Beltran, MM Fernandez-Cara, E Univ Cordoba Dept Math E-14004 Cordoba Spain Univ Seville Dept Differential Equat & Numer Anal E-41012 Seville Spain

This work is concerned with the convergence/stability analysis of a parallel algorithm which is used to solve the incompressible Navier-Stokes problem. This relies on a splitting of the main differential operator, thanks to which the most important difficulties (nonlinearity and incompressibility) can be considered independently. Thus, one is led to the formulation of subproblems of two kinds which can be solved simultaneously by two different processors. We prove conditional stability and convergence;this can serve to justify the accuracy of previous numerical results.

关键词： numerical simulation computational fluid dynamics parallel algorithm Navier-Stokes equations splitting methods

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Efficient parallel algorithm for detecting influential nodes in large biological networks on the Graphics Processing Unit

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2020年 106卷 1-13页

作者： Xiao, Lei Wang, Shuangyan Mei, Gang China Univ Geosci Beijing Sch Engn & Technol Beijing 100083 Peoples R China

In biological networks, some nodes are more influential than others. The most influential nodes are those whose elimination induces a network collapse, and detecting these nodes is crucial in many circumstances. However, this is a difficult task when the size of the biological networks is large. In this paper, we have designed and implemented an efficient parallel algorithm for detecting influential nodes for large biological networks by exploiting a Graphics Processing Unit (GPU). The essential concept behind the proposed parallel algorithm is that several computationally expensive procedures in detecting influential nodes are redesigned and transformed into quite efficient GPU-accelerated primitives such as parallel sort, scan, and reduction. Four local metrics, including the Degree Centrality (DC), Companion Behavior (CB), Clustering Coefficient (CC), and H-Index, are used to measure the nodal influence. To evaluate the efficiency of the proposed parallel algorithm, five large real biological networks are employed in the experiments. The experimental results show that (1) the proposed parallel algorithm can achieve speedups of approximately 48 similar to 94 over the corresponding serial algorithm;(2) compared to a baseline parallel algorithm developed on a multi-core CPU, the proposed parallel algorithm yields speedups of 5 similar to 9 for DC and H-Index, while it is slightly slower for CB and CC due to the uneven degree distribution;and (3) when using DC and H-Index, the proposed parallel algorithm is capable of detecting the influential nodes in a large biological network consisting of 150 million edges in less than 3 s. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Biological networks Influential nodes Degree Centrality Clustering Coefficient H-Index parallel algorithm

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An Efficient parallel algorithm for the Calculation of Unrestricted Canonical MP2 Energies

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JOURNAL OF COMPUTATIONAL CHEMISTRY 2011年第15期32卷 3304-3312页

作者： Baker, Jon Wolinski, Krzysztof Parallel Quantum Solut Fayetteville AR 72703 USA Univ Arkansas Dept Chem Fayetteville AR 72701 USA Marie Curie Sklodowska Univ Dept Chem Lublin Poland

We present details of our efficient implementation of full accuracy unrestricted open-shell second-order canonical Moller-Plesset (MP2) energies, both serial and parallel. The algorithm is based on our previous restricted closed-shell MP2 code using the Saebo-Almlof direct integral transformation. Depending on system details, UMP2 energies take from less than 1.5 to about 3.0 times as long as a closed-shell RMP2 energy on a similar system using the same algorithm. Several examples are given including timings for some large stable radicals with 90- atoms and over 3600 basis functions. (C) 2011 Wiley Periodicals, Inc. J Comput Chem 32: 3304-3312, 2011

关键词： UMP2 energies Saebo-Almlof direct integral transformation parallel algorithm

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An efficient parallel algorithm for the efficient domination problem on distance-hereditary graphs

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 2002年第9期13卷 985-993页

作者： Hsieh, SY Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan 701 Taiwan

In the literature, there are quite a few sequential and parallel algorithms for solving problems on distance-hereditary graphs. With an n-vertex and m-edge distance-hereditary graph G, we show that the efficient domination problem on G can be solved in O(log(n)(2)) time using O(n + m) processors on a CREW PRAM. Moreover, if a binary tree representation of G is given, the problem can be optimally solved in O(log n) time using O(n/log n) processors on an EREW PRAM.

关键词： parallel algorithm PRAM distance-hereditary graphs the efficient domination problem binary tree contraction technique

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Research on an improved parallel algorithm based on user's requirement in cognitive radar network

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2015年第1期2015卷 1页

作者： Yan, Bingxin Wang, Shubin Bao, Yuanyuan Inner Mongolia Univ Coll Elect Informat Engn Hohhot Peoples R China

In cognitive radar network, a parallel algorithm can allocate idle spectrum to cognitive radars, but it often ignores the user's requirement. According to the graph theory, the topology of the network is divided into two different groups. In the process of distributing spectrum, each group summarizes the distributed information after completing a distribution. When a user's demand is satisfied, every group is informed to not allocate the spectrum for the user anymore and deletes it from the topology at the same time. As a result, by deleting the node which the user's requirement has already been met, the other nodes which are interfered with the node on the same channel can participate into spectrum allocation. The improved algorithm can ensure high spectrum utilization taking a little time that is spent on the spectrum allocation. The simulation result shows that the spectrum utilization of the improved algorithm is higher than that of the traditional parallel algorithm, and the user's satisfaction increases greatly. Therefore, this paper aims to attempt to explore an improved parallel algorithm to resolve the problem by considering user's requirement.

关键词： Cognitive radar Spectrum utilization Graph theory parallel algorithm User's requirement

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