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检索条件"任意字段=5th International Conference on Algorithms and Architectures for Parallel Processing"

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parallel K-Medoids Clustering Algorithm Based on Hadoop 5

Parallel K-Medoids Clustering Algorithm Based on Hadoop

引用

5th IEEE international conference on Software Engineering and Service Science (ICSESS)

作者： Jiang, Yaobin Zhang, Jiongmin E China Normal Univ Dept Comp Sci & Technol Shanghai 200062 Peoples R China

ISBN: (纸本)9781479932795

the K-Medoids clustering algorithm solves the problem of the K-Means algorithm on processing the outlier samples, but it is not be able to process big-data because of the time complexity[1]. MapReduce is a parallel programming model for processing big-data, and has been implemented in Hadoop. In order to break the big-data limits, the parallel K-Medoids algorithm HK-Medoids based on Hadoop was proposed. Every submitted job has many iterative MapReduce procedures: In the map phase, each sample was assigned to one cluster whose center is the most similar with the sample;in the combine phase, an intermediate center for each cluster was calculated;and in the reduce phase, the new center was calculated. the iterator stops when the new center is similar to the old one. the experimental results showed that HK-Medoids algorithm has a good clustering result and linear speedup for big-data.

关键词： Clustering Analysis K-Medoids MapReduce Hadoop Big-Data

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Concurrent Nomadic and Bundle Search: A Class of parallel algorithms for Local Optimization 1

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Voglis, Costas Papageorgiou, Dimitrios G. Lagaris, Isaac E. Nodalpoint Syst LTD Athens Greece

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

We present a family of algorithms for local optimization that exploit the parallel architectures of contemporary computing systems to accomplish significant performance enhancements. this capability is important for demanding real time applications, as well as, for problems with time-consuming objective functions. the proposed concurrent schemes namely nomadic and bundle search are based upon well established techniques such as quasi-Newton updates and line searches. the parallelization strategy consists of (a) distributed computation of an approximation to the Hessian matrix and (b) parallel deployment of line searches on different directions (bundles) and from different starting points (nomads). Preliminary results showed that the new parallel algorithms can solve problems in less iterations than their serial rivals.

关键词： parallel local search Nomadic search Concurrent search Nested parallelism Line search Quasi-Newton

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Document clustering using multi-objective genetic algorithms with parallel programming based on CUDA 11

Document clustering using multi-objective genetic algorithms...

引用

11th international conference on Informatics in Control, Automation and Robotics, ICINCO 2014

作者： Lee, Jung Song Park, Soon Cheol Lee, Jong Joo Ham, Han Heeh Division of Electronics and Information Engineering Chonbuk National University Jeonju-si Korea Republic of Department of Korean Language and Literature Chonbuk National University Jeonju-si Korea Republic of Department of Archeology and Cultural Anthropology Chonbuk National University Jeonju-si Korea Republic of

ISBN: (纸本)9789897580390

In this paper, we propose a method of enhancing Multi-Objective Genetic algorithms (MOGAs) for document clustering with parallel programming. the document clustering using MOGAs shows better performance than other clustering algorithms. However, the overall computation time of the MOGAs is considerably long as the number of documents increases. To effectively avoid this problem, we implement the MO-GAs with General-Purpose computing on Graphics processing Units (GPGPU) to compute the document similarities for the clustering. Furthermore, we introduce two thread architectures (Term-threads and Document-threads) in the CUDA (Compute Unified Device Architecture) language. the experimental results show that the parallel MOGAs with CUDA are tremendously faster than the general MOGAs.

关键词： Graphics processing unit

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parallel Programming of Resistive Cross-point Array for Synaptic Plasticity 5

Parallel Programming of Resistive Cross-point Array for Syna...

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5th Annual international conference on Biologically Inspired Cognitive architectures (BICA)

作者： Xu, Zihan Mohanty, Abinash Chen, Pai-Yu Kadetotad, Deepak Lin, Binbin Ye, Jieping Vrudhula, Sarma Yu, Shimeng Seo, Jae-sun Cao, Yu Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA Arizona State Univ Sch Comp Informat & Decis Syst Engn Tempe AZ 85281 USA

this paper proposes a parallel programming scheme for the cross-point array with resistive random access memory (RRAM). Synaptic plasticity in unsupervised learning is realized by tuning the conductance of each RRAM cell. Inspired by the spike-timing-dependent-plasticity (STDP), the programming strength is encoded into the spike firing rate (i.e., pulse frequency) and the overlap time (i.e., duty cycle) of the pre-synaptic node and post-synaptic node, and simultaneously applied to all RRAM cells in the cross-point array. Such an approach achieves parallel programming of the entire RRAM array, only requiring local information from pre-synaptic and post-synaptic nodes to each RRAM cell. As demonstrated by digital peripheral circuits implemented in 65nm CMOS, the programming time of a 40kb RRAM array is 84 ns, indicating 900X speedup as compared to state-of-the-art software approach of sparse coding in image feature extraction.

关键词： Resistive cross-point array parallel programming Synaptic plasticity Dictionary learning

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Stream oriented modular architecture with polymorphic processing engines 26

Stream oriented modular architecture with polymorphic proces...

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26th IEEE international Symposium on Computer Architecture and High Performance Computing Workshops, SBAC-PADW 2014

作者： Gorobets, Andriy Pratas, Frederico Roma, Nuno Tomís, Pedro INESC-ID IST Universidade de Lisboa Portugal

ISBN: (纸本)9781479970148

Stream computing has shown to be an effective technique to decouple communication from computation in many application domains. It provides an efficient mitigation of bandwidth restrictions, by reducing the amount of memory accesses and by maximizing the available computational resources, potentiating the parallel processing using multiple execution engines. However, it frequently implies significant development costs, since efficient stream-based architectures are usually attained through application-specific full-custom processors, often tightened to the application at hand. To circumvent this limitation, a modular stream computing architecture aiming generic and high performance applications is presented. the proposed architecture, designed for reconfigurable hardware, is composed of modular processing engines that can be customized by the end-user in many ways, such as in terms of their number, type and precision of the functional units. Furthermore, these processing engines are designed as programmable cores, allowing the execution of a wide set of applications using the same configuration. From the conducted evaluation by using a series of benchmark case studies, it was observed that the proposed architecture achieves competitive results when compared with alternative solutions. © 2014 IEEE.

关键词： Engines

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thread Mapping and parallel Optimization for MIC Heterogeneous parallel Systems

Thread Mapping and Parallel Optimization for MIC Heterogeneo...

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14th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Ju, Tao Zhu, Zhengdong Wang, Yinfeng Li, Liang Dong, Xiaoshe Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Peoples R China Shenzhen Inst Informat Technol Shenzhen 518172 Peoples R China

ISBN: (纸本)9783319111940;9783319111933

there is no dedicated thread mapping method for Many Integrated Core (MIC) heterogeneous system in the traditional multithread programming model. the unreasonable thread mapping will lead the promising computing power of MIC coprocessor not to be fully exploited. In order to fully exploit the computing potential of MIC coprocessor, this paper discussed effective multi threads mapping strategies through comparing the computing performance and analyzing the performance differences between various mapping methods. Meanwhile, for the further exploiting the high computing power of MIC heterogeneous system, the specific program porting and performance optimization strategies were explored by using the k-means application program. Experimental results show that the proposed mapping and parallel optimization strategies are effective, which can be guide the programmer to port and optimize applications effectively to MIC heterogeneous parallel system.

关键词： Computing power

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COMPARING parallel TECHNOLOGIES BASED ON GPU AND CPU IN NUMERICALLY SOLVING SINGLE PHASE FLOW PROBLEMS 11

COMPARING PARALLEL TECHNOLOGIES BASED ON <i>GPU</i> AND <i>C...

引用

11th World Congress on Computational Mechanics (WCCM) / 5th European conference on Computational Mechanics (ECCM) / 6th European conference on Computational Fluid Dynamics (ECFD)

作者： Dominguez, Dany S. Orellana, Esbel. V. Santos, Bruno P. Iglesias, Susana M. Univ Estadual Santa Cruz Posgrad Modelagem Computac Rodovia Jorge Amado Km 16 BR-45662900 Ilheus BA Brazil Univ Estadual Santa Cruz Dept Ciencias Exatas & Tecnol BR-45662900 Ilheus BA Brazil

ISBN: (纸本)9788494284472

A numerical solution for a single phase flow in a porous medium problem is relevant in many fields of science and engineering. Due to the high computational cost these problems should be solved using parallel processing techniques. Initially, the MPI and OpenMP models were used for CPU architecture as the main parallel technique. Recently the CUDA model for graphic processing units has settled as the main technique for solving large scientific problems. this work presents a numerical solution for a single phase flow in a porous medium problem using GPU-CUDA technology. the mathematical model uses the Poisson mixed equation. the numerical solution is based in the Raviart-thomas finite element method and a domain decomposition method. In this work were implemented three parallel codes: the first using the MPI model, the second using an MPI-OPenMP hybrid model and the last one using CUDA. Were made performance tests for various spatial meshes in CPU and GPU architectures and performance metrics were calculated. the applied tests showed that CUDA and GPU are excellent alternatives to solve single phase flow problems in porous medium.

关键词： parallel computing GPU CPU Single phase flow

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SignalPU: A programming model for DSP applications on parallel and heterogeneous clusters 16

SignalPU: A programming model for DSP applications on parall...

引用

16th IEEE Int Conf on High Performance Computing and Communications/11th IEEE Int Conf on Embedded Software and Systems\6th Int Symposium on Cyberspace Safety and Security

作者： Mansouri, Farouk Huet, Sylvain Houzet, Dominique Univ Stendhal CNRS INPG UJF GIPSA Lab UMR 5216 F-38402 Grenoble France

ISBN: (纸本)9781479961238

the biomedical imagery, the numeric communications, the acoustic signal processing and many others digital signal processing (DSP) applications are present more and more in the numeric world. they process growing data volume which is represented with more and more accuracy, and use complex algorithms with time constraints to satisfying. Consequently, a high requirement of computing power characterize them. To satisfy this need, it's inevitable today to use parallel and heterogeneous architectures in order to speedup the processing, where the best examples are today's supercomputers like "Tianhe-2" and "Titan" of Top500 ranking. these architectures with their multi-core nodes supported by many-core accelerators offer a good response to this problem. However, they are still hard to program to make performance because of many reasons: parallelism expression, task synchronization, memory management, hardware specifications handling, load balancing ... In the present work, we are characterizing DSP applications and propose a programming model based on their distinctiveness in order to implement them easily and efficiently on heterogeneous clusters.

关键词： Digital signal processing data flow graph graphic processing unit model of programming parallel and heterogenous programming Digital signal processing data flow graphs Demonstration programmes parallel Lines Graphics processing Unit Desmoplakin Gene Programming computational power Time constraints

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Elliptic Solver Performance Evaluation on Modern Hardware architectures

Elliptic Solver Performance Evaluation on Modern Hardware Ar...

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Ciznicki, Milosz Kopta, Piotr Kulczewski, Michal Kurowski, Krzysztof Gepner, Pawel Poznan Supercomp & Networking Ctr Noskowskiego 10 St PL-61704 Poznan Poland Intel Corp Swindon SN3 1RJ Wilts England

ISBN: (纸本)9783642552243

the recent advent of novel multi-and many-core architectures forces application programmers to deal with hardware-specific implementation details and to be familiar with software optimisation techniques to benefit from new high-performance computing machines. An extra care must be taken for communication-intensive algorithms, which may be a bottleneck for forthcoming era of exascale computing. this paper aims to present performance evaluation of preliminary adaptation techniques to hybrid MPI+OpenMP parallelisation schemes we provided into the EULAG code. Various techniques are discussed, and the results will lead us toward efficient algorithms and methods to scale communication-intensive elliptic solver with preconditioner, including GPU architectures to be provided later in the future.

关键词： Elliptic solver Preconditioning EULAG High performance computing Petascale computing Hybrid parallelisation Intel Xeon Phi

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A modification of the parallel spline interpolation algorithms 5

A modification of the parallel spline interpolation algorith...

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5th international conference in Image processing and Communications, IP&C 2013

作者： Knas, Michal Cierniak, Robert Institute of Computational Intelligence Armii Krajowej 36 Czestochowa42-200 Poland

ISBN: (纸本)9783319016214

An extension of standard interpolation algorithm for image zooming is proposed. the presented method of the spline function arguments are modified, what makes the images more sharper. Implementation on Compute Unified Device Architecture is made what makes this re-sampling very fast. © Springer international Publishing Switzerland 2014.

关键词： Interpolation

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