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Runoff Forecast Model Based on an EEMD-ANN and Meteorological Factors Using a Multicore parallel algorithm

WATER RESOURCES MANAGEMENT 2023年第4期37卷 1539-1555页

作者： Liao, Shengli Wang, Huan Liu, Benxi Ma, Xiangyu Zhou, Binbin Su, Huaying Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Yunnan Elect Power Dispatch Control Ctr Yunnan Pow Kunming 650011 Peoples R China Power Dispatching Control Ctr Guizhou Power Grid Guiyang 550000 Peoples R China

Accurate long-term runoff forecasting is crucial for managing and allocating water resources. Due to the complexity and variability of natural runoff, the most difficult problems currently faced by long-term runoff forecasting are the difficulty of model construction, poor prediction accuracy, and time intensive forecasting processes. Therefore, this study proposes a hybrid long-term runoff forecasting framework that uses the antecedent inflow and specific meteorological factors as the inputs, is modeled by ensemble empirical mode decomposition (EEMD) coupled with an artificial neural network (ANN), and computed by a parallel algorithm. First, the framework can transform monthly inflow and meteorological series into stationary signals via EEMD to more comprehensively explore the relationships of the input factors through the ANN. Second, the selected meteorological factors that are closely related to inflow formation can be filtered out by the single correlation coefficient method, which contributes to reducing coupling between input factors, and increases the accuracy of the prediction models. Finally, a multicore parallel algorithm that is easily accessed everywhere and that fully utilizes multiple calculation resources while flexibly contending with various optimization requirements will improve forecasting efficiency. The Xiaowan Hydropower Station (XW) is selected as the study area, and the final results of the study show that (1) the addition of targeted meteorological factors does indeed greatly enhance the performance of the prediction models;(2) the five criteria for evaluating the prediction accuracy show that the EEMD-ANN model is far superior to the prediction performance from the ordinary ANN model when run under the same input conditions;and (3) the optimization time of the 32-core model can be reduced by as much as 25 times, which significantly saves time during the forecast process.

关键词： Long-term runoff forecast parallel algorithm Ensemble empirical mode decomposition ANN Filtered meteorological factors

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A 10000-Image-per-Second parallel algorithm for Real-Time Detection of MARFEs on JET

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IEEE TRANSACTIONS ON PLASMA SCIENCE 2013年第2期41卷 341-349页

作者： de Albuquerque, Marcio Portes Murari, Andrea Giovani, M. Alves, Nilton, Jr. de Albuquerque, Marcelo Portes Ctr Brasileiro Pesquisas Fis BR-22299180 Rio De Janeiro Brazil Italian Natl Agcy New Technol Energy & Sustainabl European Atom Energy Community Consorzio Reversed Field EXpt Assoc I-35127 Padua Italy

This paper presents a very high-speed image processing algorithm applied to multi-faceted asymmetric radiation from the edge (MARFE) detection on the Joint European Torus. The algorithm was built in serial and parallel versions and written in C/C+ using OpenCV, cvBlob, and LibSVM libraries. The code implemented was characterized by its accuracy and run-time performance. The final result of the parallel version achieves a correct detection rate of 97.6% for MARFE identification and an image processing rate of more than 10 000 frame per second. The parallel version divides the image processing chain into two groups and seven tasks. One group is responsible for Background Image Estimation and Image Binarization modules, and the other is responsible for region Feature Extraction and Pattern Classification. At the same time and to maximize the workload distribution, the parallel code uses data parallelism and pipeline strategies for these two groups, respectively. A master thread is responsible for opening, signaling, and transferring images between both groups. The algorithm has been tested in a dedicated Intel symmetric-multiprocessing computer architecture with a Linux operating system.

关键词： Image processing multi-faceted asymmetric radiation from the edge detection multi-faceted asymmetric radiation from the edge identification parallel algorithm

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AN OPTIMAL parallel algorithm FOR GENERATING PERMUTATIONS IN MINIMAL CHANGE ORDER

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parallel COMPUTING 1994年第3期20卷 353-361页

作者： TSAY, JC LEE, WP Institute of Computer Science and Information Engineering College of Engineering National Chiao Tung University Hsinchu Taiwan 30050

Permutation generation is an important problem in combinatorial computing. In this paper we present an optimal parallel algorithm to generate all N! permutations of N objects. The algorithm is designed to be executed on a very simple computation model that is a linear array with N identical processors. Because of the simplicity and regularity of the processors, the model is very suitable for VLSI implementation. Another advantageous characteristic of this design is that it can generate all the permutations in minimal change order.

关键词： MINIMAL CHANGE ORDER parallel algorithm PERMUTATION GENERATION VLSI

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A parallel algorithm for improving the maximal property of Poisson disk sampling

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COMPUTER-AIDED DESIGN 2014年第1期46卷 37-44页

作者： Ying, Xiang Li, Zhenhua He, Ying Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore

This paper presents a simple yet effective algorithm to improve an arbitrary Poisson disk sampling to reach the maximal property, i.e., no more Poisson disk can be inserted. Taking a non-maximal Poisson disk sampling as input, our algorithm efficiently detects the regions allowing additional samples and then generates Poisson disks in these regions. The key idea is to convert the complicated plane or space searching problem into a simple searching on circles or spheres, which is one dimensional lower than the original sampling domain. Our algorithm is memory efficient and flexible, which generates maximal Poisson disk sampling in an arbitrary 2D polygon or 3D polyhedron. Moreover, our parallel algorithm can be extended from the Euclidean space to curved surfaces in an intrinsic manner. Thanks to its parallel structure, our method can be implemented easily on modern graphics hardware. We have observed significance performance improvement compared to the existing techniques. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Poisson disk sampling Maximal sampling parallel algorithm GPU Exponential map

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A parallel algorithm for computing Voronoi diagram of a set of spheres using restricted lower envelope approach and topology matching

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COMPUTERS & GRAPHICS-UK 2022年 106卷 210-221页

作者： Mukundan, Manoj Kumar Thayyil, Safeer Babu Muthuganapathy, Ramanathan Indian Inst Technol Madras Dept Engn Design Adv Geometr Comp Lab Chennai India Govt Engn Coll Palakkad Dept Informat Technol Palakkad Kerala India Rajiv Gandhi Inst Technol Dept Mech Engn Kottayam Kerala India

We present a parallel algorithm for computing the Voronoi diagram of a set of spheres, S in R3. The spheres have varying radii and do not intersect. We compute each Voronoi cell independently using a two-stage iterative procedure, assuming the input spheres are in general position. In the first stage, an initial Voronoi cell for a sphere si is computed using an iterative lower envelope approach restricted to a subset of spheres Li subset of S. This helps to avoid defining the bisectors between all pairs of input spheres and develop a distributed memory parallel algorithm. We use the Delaunay graph of sample points from the input spheres to select the subset Li for computing each Voronoi cell. In the second stage, Voronoi cells obtained from the first stage are matched for updating the subsets. If additional spheres are added to a subset Li, the correctness of the computed vertices is verified with the bisectors of spheres newly added to Li. Results and performance of the algorithm show robustness and speed of the algorithm in handling a large set of spheres.

关键词： Voronoi diagram Topology matching Delaunay graph Touching sphere Lower envelope parallel algorithm

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pSIN: A scalable, Parallel algorithm for Seismic INterferometry of large-N ambient-noise data

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COMPUTERS & GEOSCIENCES 2016年 93卷 88-95页

作者： Chen, Po Taylor, Nicholas J. Dueker, Ken G. Keifer, Ian S. Wilson, Andra K. McGuffy, Casey L. Novitsky, Christopher G. Spears, Alec J. Holbrook, W. Steven Univ Wyoming Dept Geol & Geophys Laramie WY 82071 USA

Seismic interferometry is a technique for extracting deterministic signals (i.e., ambient-noise Green's functions) from recordings of ambient-noise wavefields through cross-correlation and other related signal processing techniques. The extracted ambient-noise Green's functions can be used in ambient noise tomography for constructing seismic structure models of the Earth's interior. The amount of calculations involved in the seismic interferometry procedure can be significant, especially for ambient noise datasets collected by large seismic sensor arrays (i.e., "large-N" data). We present an efficient parallel algorithm, named pSIN (parallel Seismic INterferometry), for solving seismic interferometry problems on conventional distributed-memory computer clusters. The design of the algorithm is based on a two-dimensional partition of the ambient-noise data recorded by a seismic sensor array. We pay special attention to the balance of the computational load, inter-process communication overhead and memory usage across all MPI processes and we minimize the total number of I/O operations. We have tested the algorithm using a real ambient-noise dataset and obtained a significant amount of savings in processing time. Scaling tests have shown excellent strong scalability from 80 cores to over 2000 cores. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Seismic interferometry Ambient-noise parallel algorithm Message-passing interface

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An Efficient Distributed parallel algorithm for Optimal Consensus of Multiagent Systems

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2024年第3期11卷 1440-1451页

作者： Bai, Nan Wang, Qishao Duan, Zhisheng Peking Univ Coll Engn Dept Mech & Engn Sci State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China Beihang Univ Dept Dynam & Control Beijing 100191 Peoples R China

A parallel algorithm is presented in this article to efficiently solve the optimal consensus problem of multiagent systems. By utilizing a Jacobi-type proximal alternating direction multiplier framework, the optimization process is divided into two independent subproblems that can be solved in parallel to improve computational efficiency, followed by the Lagrangian multiplier update. The convergence analysis of the proposed algorithm is performed using the convex optimization theory, deriving the convergence conditions concerning the auxiliary parameters. Furthermore, the accelerated algorithm enjoys a convergence rate of O(1/t(2)) by adjusting the auxiliary parameters adaptively. To leverage the strengths of the collaboration of multiagent systems, the distributed implementation of the proposed parallel algorithm is further developed, where each agent addresses its private subproblems only using its own and its neighbor's information. Numerical simulations demonstrate the effectiveness of the theoretical results.

关键词： Optimization Multi-agent systems Convergence parallel algorithms Jacobian matrices Protocols Costs Convex optimization distributed optimization multiagent systems optimal consensus parallel algorithm

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A parallel algorithm for generating chain code of objects in binary images

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INFORMATION SCIENCES 2003年第4期149卷 219-234页

作者： Chia, TL Wang, KB Chen, LR Chen, Z Chung Cheng Inst & Technol Dept Elect Engn Taoyuan 33509 Taiwan Natl Chiao Tung Univ Inst Comp Sci & Informat Engn Hsinchu 30050 Taiwan

This paper addresses parallel execution of chain code generation on a linear array architecture. The contours in the proposed algorithm are viewed as a set of edges (or contour segments) that can be traced by a top-down contour tracing method to generate the chain codes for the outer and inner object contours. A parallel algorithm that contains the chain code generating rules and operations needed is also described, and the algorithm is mapped onto a one-dimensional systolic array containing [(1)/(2)(N + 1)] processing elements (PEs) to devise this architecture. The architecture extracts the contours of objects and quickly generates the corresponding chain codes after the image data in all rows are inputted in a linear fashion. The total processing time for generating the chain codes in an N x N image is O(3N). By doing so, the real-time requirement is fulfilled and its execution time is independent of the image content. In addition, a partition method is developed to process an image when the parallel architecture has a fixed number of PEs;say two or more. The total execution time for an N x N image by employing a fixed number of PEs is N(N + 1)/M + 2(M - 1), when M is the fixed number of PEs. (C) 2002 Elsevier Science Inc. All rights reserved.

关键词： chain code parallel algorithm chain collection chain linking

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A parallel algorithm for the Sylvester observer equation

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 1996年第3期17卷 686-698页

作者： Bischof, CH Datta, BN Purkayastha, A NO ILLINOIS UNIV DEPT MATH SCIDE KALBIL 60115 UNIV PUERTO RICO DEPT MATHMAYAGUEZPR 00681

We present a new algorithm for solving the Sylvester observer equation arising in the context of the Luenberger observer. The algorithm embodies two main computational phases: the solution of several independent equation systems and a series of matrix-matrix multiplications. The algorithm is, thus, well suited for parallel and high-performance computing. By reducing the coefficient matrix A to lower-Hessenberg form, one can implement the algorithm efficiently, with few floating-point operations and little workspace. The algorithm has been successfully implemented on a GRAY C90. A comparison, both theoretical and experimental, has been made with the well-known Hessenberg-Schur algorithm which solves an arbitrary Sylvester equation. Our theoretical analysis and experimental results confirm the superiority of the proposed algorithm, both in efficiency and speed, over the Hessenberg-Schur algorithm.

关键词： Sylvester observer equation parallel algorithm orthogonal factorization shared-memory parallelism Hessenberg-Schur algorithm

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Compact Local IRBF and Domain Decomposition Method for solving PDEs using a Distributed termination detection based parallel algorithm

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CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES 2013年第1期92卷 1-31页

作者： Pham-Sy, N. Tran, C. -D. Hoang-Trieu, T. -T. Mai-Duy, N. Tran-Cong, T. Univ So Queensland Fac Engn & Surveying Computat Engn & Sci Res Ctr Toowoomba Qld 4350 Australia

Compact Local Integrated Radial Basis Function (CLIRBF) methods based on Cartesian grids can be effective numerical methods for solving partial differential equations (PDEs) for fluid flow problems. The combination of the domain decomposition method and function approximation using CLIRBF methods yields an effective coarse-grained parallel processing approach. This approach has enabled not only each sub-domain in the original analysis domain to be discretised by a separate CLIRBF network but also compact local stencils to be independently treated. The present algorithm, namely parallel CLIRBF, achieves higher throughput in solving large scale problems by, firstly, parallel processing of sub-regions which constitute the original domain and, secondly, accelerating the convergence rate within each sub-region using groups of CLIRBF stencils in which function approximations are carried out by parallel processes. The procedure is illustrated with several numerical examples of PDEs and lid-driven cavity problem using Message Passing Interface supported by MATLAB.

关键词： Integrated RBFs Compact Local Stencils Domain Decomposition Method parallel algorithm Distributed Termination Detection

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