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Integration of 3D incompressible free surface Navier-Stokes equations on unstructured tetrahedral grid using distributed computation on TCP/IP networks

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7th International Conference on Advances in Fluid Mechanics

作者： Evstigneev, N. Acad Sci Dept Nonlinear Dynam Syst Inst Syst Anal Moscow Russia

ISBN: (纸本)9781845641092

The incompressible system of Navier-Stokes equations for an Initial-Boundary Value Problem is solved on an unstructured tetrahedral grid using a finite volume method. Implementation of a free surface calculation is done by using a combination of Level Set and Volume Of Fluid methods. A numerical scheme utilizes the method of fractional steps based on the predictor-corrector method and the artificial compressibility method. Invariant features of a tetrahedron are used in order to calculate fluxes over a control volume with higher order. A high order approximation in Navier-Stokes and VOF level set advection equations is made by a TVD SuperBEE scheme. The turbulence model is based on LES methodology. In order to decrease the time of solution for a large geometry, a distributed computation routine is incorporated into the method. The distributed calculation is based on a TCP/IP network and can use personal computers under Windows or UNIX. The efficiency of the distributed calculation is shown. The method is verified by comparison of results with other calculations and experiments - cavity flow case, dam break free surface flow case, turbulent flow in a circular pipe case - Poiseuille flow (turbulent energy distribution). The method is successfully used for CFD simulation of water intake on Zagorskaya Hydraulic Power Plant (Russia). The results are close between laboratory experiments and CFD computations.

关键词： unstructured grid finite volume method artificial compressibility method predictor-corrector method Navier-Stokes equations distributed computation

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distributed computation for Sparse Optimization with Linear Equality Constraints

Distributed Computation for Sparse Optimization with Linear ...

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第三十八届中国控制会议

作者： Wen Deng Weijian Li Yiguang Hong LSC Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences School of Information Science and Technology University of Science and Technology of China

In this paper, we propose two distributed algorithms for sparse optimization problems with linear equality constraints of the vector case and the matrix case. In the l-norm minimization with the linear algebraic equation constraint, we take the general block partition for the information matrix. In the l-norm minimization with the linear operator constraint, we mainly focus on the case that every node holds the local linear constraint, while the case that all nodes have a coupling constraint can be easily obtained in a similar way. The two algorithms are both based on the primal-dual subgradient method and derivative feedback techniques. Finally, we investigate the convergence properties for the proposed algorithms, and then numerical examples are given to verify the algorithms.

关键词： distributed computation sparse optimization nonsmooth analysis multi-agent network

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distributed computation of Common Lyapunov Functions

Distributed Computation of Common Lyapunov Functions

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第37届中国控制会议

作者： Xiong Zeng Xianlin Zeng Yiguang Hong LSC Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Beijing Institute of Technology

This paper investigates the distributed computation of common Lyapunov functions over multi-agent networks for switching problems. From an optimization perspective, we present a distributed algorithm for solving the nonlinear convex programming problem by means of the projection method. Then we prove that the proposed algorithm is Lyapunov stable and can converge to an exact optimal solution of the common Lyapunov functions problem.

关键词： distributed computation Common Lyapunov Functions Linear Matrix Inequalities Optimization

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distributed computation BY GRAPH REDUCTION

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SYSTEMS RESEARCH 1985年第4期2卷 285-295页

作者： KELLER, RM UNIV UTAH DEPT COMP SCISALT LAKE CITYUT 84112 USA

We describe the use and distributed implementation of a functional language based on the graph‐reduction concept. Attention is given to the issue of implementing higher‐order functions and concurrent evaluation. Pro... 详细信息

关键词： Functional programming graph reduction parallel computation distributed computation lambda calculus higher‐order functions Lisp closures equational language data‐flow

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A System for a distributed computation of a dynamic triangulated surface simulation and its analysis

ELEKTROTEHNISKI VESTNIK

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ELEKTROTEHNISKI VESTNIK 2019年第5期86卷 283-289页

作者： Penic, Samo Fosnaric, Miha Univ Ljubljani Fak Elektrotehniko Trzaska Cesta 25 Ljubljana 1000 Slovenia Univ Ljubljani Zdravstvena Fak Zdravstvena Pot 5 Ljubljana 1000 Slovenia

A dynamic triangulated surface simulations used in modelling lipid bilayers are time consuming. Frequently, the phase space of multiple parameters needs to be investigated by simulating each parameter set. Concurrent running of multiple simulations in parallel accelerates the investigation of the phase space. In the paper, we present a system for a parallel computation of a triangulated surface simulations using a simulator trisurf. A method of voluntary computing was applied, using a server-client technology. The simulator itself becomes the computing part of the system that is being executed on the client side and waits for a workload from the server. Besides, being a workload distributor, the server also acts as a simulation results collector and data archiver. The analysis of the data and metadata is performed on the server itself using a standard web browser. The technology used for the data analysis is the Jupyter notebook. The system is engineered based on experiences with similar systems and following good research practices for result reproducibility.

关键词： Monte Carlo simulations distributed computation paralelization database Jupyter biological membranes lipid bilayers

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Vietnamese Short Text Classification via distributed computation

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2021年第7期12卷 23-31页

作者： Hiep Xuan Huynh Linh Xuan Dang Duong-Trung, Nghia Cang Thuong Phan Can Tho Univ Can Tho City Vietnam Tech Univ Berlin Berlin Germany

Social networking has been growing rapidly in Vietnam. The sharing information is diverse and circulates in many forms. It requires user-friendly solutions such as topic sorting and perspectives analysis in analyzing community trends, advertisements or anticipating and monitoring the spread of bad news. Unfortunately, Vietnamese is highly different from other languages and little research has been conducted in the literature on messages classification. The implementation of machine learning models on Vietnamese has not been thoroughly investigated and these models' performance is unknown when applying in a different language. Vietnamese text is a serialization of syllables, hence, word boundary identification is not trivial. This research portrays our endeavor to construct an effective distributed framework for addressing the task of classification of short Vietnamese texts on social networks using the idea of probability categorization. The authors argue that addressing the task sharps the successful combination of machine learning, natural language processing, and ambient intelligence. The proposed framework is effective and enables fast calculation, suitable for implementation in Apache Spark, meeting the demand for dealing with large amounts of textual data on the current social networks. Our data has been collected from several online text sources of 12412 short messages classified into five different topics. The evaluation shows that our approach has achieved an average of 82.73% classification accuracy. Thoughtfully learning the literature, we could state that this is the first attempt to classify short Vietnamese messages under a distributed computation framework.

关键词： Short text classification Naive Bayes Apache Spark Vietnamese distributed computation

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On distributed Function computation in Structure-Free Random Wireless Networks

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IEEE TRANSACTIONS ON INFORMATION THEORY 2014年第1期60卷 432-442页

作者： Kamath, Sudeep Manjunath, D. Mazumdar, Ravi Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Indian Inst Technol Dept Elect Engn Bombay 400076 Maharashtra India Indian Inst Technol Bharti Ctr Commun Bombay 400076 Maharashtra India Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

We consider in-network computation of MAX and the approximate histogram in an n-node structure-free random multihop wireless network. The key assumption that we make is that the nodes do not know their relative or absolute locations and that they do not have an identity. For the Aloha MAC protocol, we first describe a protocol in which the MAX value becomes available at the origin in O(root n/ log n) slots (bit-periods) with high probability. This is within a constant factor of that required by the best coordinated protocol. A minimal structure (knowledge of hop-distance from the sink) is imposed on the network and with this structure, we describe a protocol for pipelined computation of MAX that achieves a rate of Omega(1/(log n)(2)). Finally, we show how the protocol for computation of MAX can be modified to achieve approximate computation of the histogram. The approximate histogram can be computed in O(n(7/2)(log n)(1/2)) bit-periods with high probability.

关键词： Communication and computation rate distributed computation in-network computation structure free networks wireless sensor networks

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Network Optimization via Smooth Exact Penalty Functions Enabled by distributed Gradient computation

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2021年第3期8卷 1430-1441页

作者： Srivastava, Priyank Cortes, Jorge Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92122 USA

This article proposes a distributed algorithm for a network of agents to solve an optimization problem with separable objective function and locally coupled constraints. Our strategy is based on reformulating the original constrained problem as the unconstrained optimization of a smooth (continuously differentiable) exact penalty function. Computing the gradient of this penalty function in a distributed way is challenging even under the separability assumptions on the original optimization problem. Our technical approach shows that the distributed computation problem for the gradient can be formulated as a system of linear algebraic equations defined by separable problem data. To solve it, we design an exponentially fast, input-tostate stable distributed algorithm that does not require the individual agent matrices to be invertible. We employ this strategy to compute the gradient of the penalty function at the current network state. Our distributed algorithmic solver for the original constrained optimization problem interconnects this estimation with the prescription of having the agents follow the resulting direction. Numerical simulations illustrate the convergence and robustness properties of the proposed algorithm.

关键词： distributed computation distributed optimization exact penalty functions interconnected systems linear algebraic equations with separable data

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distributed PageRank computation with improved round complexities

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INFORMATION SCIENCES 2022年 607卷 109-125页

作者： Luo, Siqiang Wu, Xiaowei Kao, Ben Nanyang Technol Univ Singapore Singapore Univ Macau IOTSC Zhuhai Peoples R China Univ Hong Kong Hong Kong Peoples R China

PageRank is a classic measure that effectively evaluates the importance of nodes in large graphs. It has been applied in numerous applications spanning data mining, Web algorithms, recommendation systems, load balancing, search and connectivity structures identification. Computing PageRank for large graphs is challenging and this has motivated the studies of distributed algorithms to compute PageRank. Previously, little works have been spent on the distributed PageRank algorithms with strong guarantees on both complexity and accuracy. In this paper, we focus on the theoretical aspect and study the complexity of distributed PageRank computation based on the well-known congested-clique model with a bandwidth generalization. An existing algorithm proposed by Sarma et al. (2015) can be applied in this model, which estimates PageRanks in an n-node graph using, with high (p ) ffiffiffiffiffiffiffiffiffiffi ( ) probability, O log n communication rounds and a bandwidth of O (log n)3 bits. We present Radar-Push (RP), which is a distributed PageRank algorithm that is strictly better in round complexities. Specifically, Radar-Push uses O( log log n) communication rounds ( ) and an edge bandwidth of O (log n)3 bits. We further show that Radar-Push can be adapted to efficiently compute an important variant of PageRank, namely, the batch onehop personalized PageRank, in O( log log n) communication rounds. (c) 2022 Elsevier Inc. All rights reserved.

关键词： PageRank distributed computation Graph Algorithms

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A Kind of Load Balance Multicast Routing Algorithm Based on distributed computation and Centralized Control

A Kind of Load Balance Multicast Routing Algorithm Based on ...

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The International Conference on Recent Trends in Materials and Mechanical Engineering(ICRTMME 2011)

作者： CHEN Xiang Tang Jun-yong ZHANG Yong School of Civil Engineering Xi'an Technological University Department of Computer Science and Engineering Xi'an Technological University Wuhan University of Science and Technology

distributed routing can find multicast tree and adapt to dynamic changes of multicast members in case of acknowledge local network stateMajority of current distributed multicast routing algorithms based on the shortest delay, which can achieve load balance large additional overheadThe paper presented a kind of load balance multicast routing algorithm based on distributed computation and centralized controlIt reside computation Agent in each node to compute forward probability and to maintain node routing table, node state table and forwarding probability tableIn addition, it can detect delay of adjacent nodes and coordinate session establishment based on the copy, parameter transmission and notification of control AgentOn this basis, the algorithm achieved dynamically joins and leave session of multicast membersAlgorithm analysis results show that the algorithm can improve the overall efficiency of network transmission.

关键词： multicast routing Agent distributed computation centralized control

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