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Proceedings of the eleventh workshop on parallel and distributed simulation

作者： David M. Nicol Michael M. Johnson Ann S. Yoshimura Michael E. Goldsby Dept. of Computer Science Dartmouth College Hanover NH Sandia National Laboratories Livermore CA

ISBN: (纸本)9780818679650

The IDES project at Sandia National Laboratories is developing a large scale portable parallel simulator for use in stockpile stewardship. IDES will use the Breathing-Time-Buckets synchronization protocol; to support IDES development, this paper studies a performance model and describes performance experiments on expected work load and architectural parameters. A new parallel algorithm for terminating the window quickly is also described and analyzed.

关键词： IDES project stockpile stewardship parallel programming parallel algorithm Breathing-Time-Buckets large scale portable parallel simulator discrete event simulation work load performance modeling window termination architectural parameters Sandia National Laboratories synchronization protocol

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Sequential Approximation to Virtual Boundary for parallelization of Hybrid-SRM Scheme

Sequential Approximation to Virtual Boundary for Paralleliza...

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2001 International Symposium on Distributed Computing and Applications to Business, Engineering and Science

作者： Chen Xianqiao Cuo Qingping College of Computer Science & Technology,Wuhan University Technology,Wuhan 430063 Lin Ping Department of Mathematics,The National University of Singapore,Singapore 117543

Hybrid Scheme is a important formulation in solving Vavier-Stokes equations(incompressible flow problems),and SRM algorithm keeps the benefits of the penalty method,that is,velocity and pressure can be obtained separately and no pressure-Poisson equation is involved,unlike the penalty method the SRM is more stable,less *** then case that a large number of time steps are needed,we introduce Domain-Decomposition based parallel techniques,and apply Sequential Approximation Virtual Boundary to compute the internal boundaries of sub-domains,less iterative is needed., computational results shows that the result is very well,and the speedup ratio of our method is larger.

关键词： Hybrid Scheme Sequential Regularization Method(SRM) Sequential Approximation Virtual Boundary(SAVB) parallel algorithm Domain-Decomposition

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Optimized parallelization of Binary Classification algorithms Based on Spark

Optimized Parallelization of Binary Classification Algorithm...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Yushui Geng Jianguo Zhang School of Information Qilu University Of Technology Jinan China

ISBN: (纸本)9781509035595

In recent years, parallel computing and machine learning have gradually became a research hotspot in big data field. Now users who are familiar with the R language can easily complete the data analysis on the platform of Apache Spark with the programming interface called SparkR provided by Apache Spark. There are several realized classification algorithms (including multiple classification and binary classification) in SparkR, in order to speed up the training process in binary-class classification, this paper proposes a theory of adopting an iterative calculation model for the local optimization on the basis of conventional parallelization. The experimental result shows that the design of parallelization of binary classification algorithm based on spark is much better and faster comparing with the MapReduce on Hadoop.

关键词： MapReduce parallel algorithm memory computing Spark classification

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ON IMPROVING THE PERFORMANCE OF TREE MACHINES

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INTERNATIONAL JOURNAL OF HIGH SPEED COMPUTING 1995年第2期7卷 251-263页

作者： GUPTA, AK WANG, H PURDUE UNIV DEPT COMP SCIW LAFAYETTEIN 47907

In this paper we introduce a class of trees, called generalized compressed trees. Generalized compressed trees can be derived from complete binary trees by performing certain 'contraction' operations. A generalized compressed tree CT of height h has approximately 25% fewer nodes than a complete binary tree T of height h. We show that these trees have smaller (up to a 74% reduction) 2-dimensional and 3-dimensional VLSI layouts than the complete binary trees. We also show that algorithms initially designed for T can be simulated by CT with at most a constant slow-down. In particular, algorithms having non-pipelined computation structure and originally designed for T can be simulated by CT with no slow-down.

关键词： BINARY TREE MACHINE EMBEDDING HYPERCUBE parallel algorithm PIPELINED COMPUTATION NODE LOAD SIMULATION VLSI LAYOUT (2-DIMENSIONAL AND 3-DIMENSIONAL)

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Spark-based Large-scale Matrix Inversion for Big Data Processing

Spark-based Large-scale Matrix Inversion for Big Data Proces...

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IEEE Conference on Computer Communications Workshops

作者： Yang Liang Jun Liu Cheng Fang Nirwan Ansari Center for Data Science Beijing University of Posts and Telecommunications China 100876 Electrical and Computer Engineering Department New Jersey Institute of Technology US 07102

ISBN: (纸本)9781467399562

Matrix inversion is a fundamental operation to solve linear equations for many computational applications. However, it is a challenging task to invert large-scale matrices of extremely high order (several thousands), which are common in most of web-scale systems like social networks and recommendation systems. In this paper, we present a LU decomposition based block-recursive algorithm for large-scale matrix inversion, and its well-designed implementation with optimized data structure, reduction of space complexity and effective matrix multiplication on the Spark parallel computing platform. The experimental evaluation results show that the proposed algorithm is efficient to invert large-scale matrices on a cluster composed of commodity servers and scalable to invert even larger matrices. The proposed algorithm and implementation will be a solid base to build a high-performance linear algebra library on Spark for big data processing.

关键词： Matrix inversion LU decomposition Linear algebra parallel algorithm Distributed computing Spark

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Clustering using Artificial Bee Colony on CUDA

Clustering using Artificial Bee Colony on CUDA

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Jan Janousek Jan Platos Vaclav Snasel Department of Computer Science FEECS IT4 Innovations VSB - Technical University of Ostrava

ISBN: (纸本)9781479938414

Artificial bee colony is a meta-heuristic optimization algorithm based on the behavior of honey bee swarm. These bees work largely independently of other bees, making the algorithm suitable for parallel implementation. Within this paper, we introduce the algorithm itself and its subsequent parallelization utilizing the CUDA platform. The runtime speedup is demonstrated on several commonly used test functions for optimization. The algorithm is subsequently applied to the problem of clustering real data.

关键词： parallel algorithm Artificial bee colony CUDA Clustering

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SparkSCAN: A Structure Similarity Clustering algorithm on Spark

SparkSCAN: A Structure Similarity Clustering Algorithm on Sp...

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2015大数据技术及应用论坛

作者： Qijun Zhou Jingbin Wang Department of Mathematics and Computer Science Fuzhou University

The existing directed graph clustering algorithms are born with some problems such as high latency, resource depletion and poor performance of iterative data processing. A distributed parallel algorithm of structure similarity clustering on Spark(Spark SCAN) is proposed to solve these problems: considering the interaction between nodes in the network, the similar structure of nodes are clustered together;Aiming at the large-scale characteristics of directed graphs, a data structure suitable for distributed graph computing is designed, and a distributed parallel clustering algorithm is proposed based on Spark framework, which improves the processing performance on the premise of the accuracy of clustering results. The experimental results show that the Spark SCAN have a good performance, and can effectively deal with the problem of clustering algorithm for large-scale directed graph.

关键词： Directed graph clustering parallel algorithm Spark RDD

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Research and Implementation of Petri nets parallelization model

Research and Implementation of Petri nets parallelization mo...

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13th International Symposium on Distributed Computing and Applications to Business,Engineering & Science（DCABES 2014）

作者： Xuan Wang Wen-jing LI Ze-yu Tang Weizhi LIAO College of Computer and Information Engineering Guangxi Teachers Education University

In order to solve parallel algorithm of Petri net system with concurrent functions and implement parallel control and execution of Petri net, parallel programming model of Petri net based on multi-core clusters is put forward. First, P-invariant technology is used to do the functional division of Petri net system and the parallel analysis of Petri net process. Next, based on architecture of multi-core cluster and combined with parallelism of Petri net process, Petri net system model is ***, parallel algorithm of Petri net system is raised. Finally, under the environment of multi-core cluster,the simulation experiment of parallel algorithm is done. The experimental results show that parallel algorithm based on Petri net system model is correct and feasible. The model can effectively simulate the actual operation of the system and is an effective model of Petri net parallelization system.

关键词： Petri Net parallelism Multi-core Cluster parallel Model parallel algorithm

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Multi-Modal Search with Convex Bounding Neighbourhood

Multi-Modal Search with Convex Bounding Neighbourhood

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： D.H.M.NGUYEN K.P.WONG C.Y.CHUNG School of Engineering Science Murdoch University Computational Intelligence Applications Research Laboratory Department of Electrical EngineeringTh

This paper presents a new dynamic method of subpopulation in solving multi-modal search problems with evolutionary algorithms. The new method identify the modes found at each generation and equalises the subpopulation sizes assigned to each mode. Modes are identified sequentially starting with the highest fitness mode. Mode membership is determined by successive grouping of fitness dominated convex bounding neighbours, starting from the fittest individual. This new dynamic modal subpopulation approach is able to fmd a representative sample of optima for multi-modal landscape with infinite number of global and local optima with uneven heights and non-uniform distribution. The algorithm also facilitates parallel implementation.

关键词： Multi-modal search evolutionary computation parallel algorithm subpopulation techniques

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parallelization of Point Operations on Conic Curves over Finite Field GF(2(n))

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INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING 2014年第3期7卷 287-298页

作者： Li, Yongnan Xiao, Limin Beihang Univ State Key Lab Software Dev Environm Beijing 100191 Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing 100191 Peoples R China

It becomes more and more important to design high-speed parallel cryptographic algorithms due to a growing need for information security. Conic curves cryptography is a new developing direction in the field of information security in recent years and there are less works focused on the parallel encryption algorithms for conic curves crypto system. This paper proposes four parallel algorithms for conic curves cryptosystem over finite field GF(2(n)). One parallel algorithm of modular-multiplication is designed by analyzing its data dependency and making some modifications of several steps. In order to figure out the average runtime, we consider the probability distributions of different cases to compute the mathematical expectation. The operations of point-addition, point-double and pointmultiplication, three fundamental point operations in conic curves cryptosystem over finite field GF(2(n)), are paralleled based on this parallel algorithm of modular-multiplication and two parallel algorithms we proposed before. Time complexities and speedup ratios of the parallel algorithms and the sequential algorithms are calculated to make the quantitative comparison. The performance evaluation shows better efficiencies of the proposed parallel algorithms compared to the traditional algorithms.

关键词： parallel algorithm Conic curves Finite field GF(2(n)) Point-addition Pointdouble Point-multiplication

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