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IEEE High Performance Extreme computing Conference (HPEC)

作者： Abualkibash, Munther Mahmood, Ausif Moslehpour, Saeid Univ Bridgeport Comp Sci & Engn Bridgeport CT 06604 USA Univ Bridgeport Elect & Comp Engn Bridgeport CT USA

ISBN: (纸本)9781467392860

Object detection (e.g., face detection) using supervised learning often requires extensive training, resulting in long execution times. If the system requires retraining to accommodate a missed detection, waiting several hours or even days in some cases before the system is ready, may not be acceptable in practical implementations. This paper presents a generalized object detection framework such that the system can efficiently adapt to misclassified data and be retrained within a few minutes. The methodology developed here is based on the popular AdaBoost algorithm for object detection. To reduce the learning time in object detection, we develop a highly efficient, parallel, and distributed AdaBoost algorithm that is able to achieve a training execution time of only 1.4 seconds per feature on 25 workstations. Further, we incorporate this parallel object detection algorithm into an adaptive framework such that a much smaller, optimized training subset is used to yield high detection rates while further reducing the retraining execution time. We demonstrate the usefulness of our adaptive framework on face and car detection.

关键词： parallel and distributed computing object detection face detection car detection AdaBoost master-slave architecture web services

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Operator Placement for Efficient distributed Complex Event Processing in MANETs 11

Operator Placement for Efficient Distributed Complex Event P...

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11th IEEE International Conference on Wireless and Mobile computing, Networking and Communications (WiMob)

作者： Starks, Fabrice Plagemann, Thomas Peter Univ Oslo Dept Informat Oslo Norway

ISBN: (纸本)9781467377010

Complex Event Processing (CEP) and Mobile Adhoc networks (MANETs) are two technologies that can be used to enable monitoring applications for Emergency and Rescue missions (ER). MANETs are characterized by energy limitations, and in-network processing or distributed CEP is one possible solution. Operator placement mechanism for distributed CEP has a direct impact on energy consumption. Existing operator placement mechanisms focus on static network topologies and are therefore inappropriate for MANETs scenarios. We propose a novel energy efficient decentralized distributed placement mechanism, designed to achieve fast convergence with minimal data transmission cost while achieving a near optimal placement assignment. We compare our decentralized placement mechanism with a centralized approach under different mobility scenarios. Furthermore, we evaluate the distributed CEP under different workload scenarios in order to gain additional insight into different performance characteristics of the system. Finally, we measure the impact of a simple placement replication scheme on the overall system performance in terms of delay and message overhead. Our decentralized placement mechanism achieves up to almost 50% lower message overhead compared to the centralized approach, and it has lower message overhead across different mobility scenarios compared to the centralized approach. The placement replication scheme achieves up to 51% lower delay compared to the decentralized placement mechanism with no replication.

关键词： Computer networks Mobile computing parallel and distributed computing Performance Wireless communications

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Use of the distributed computing at the Castings Solidification Simulation

Use of the Distributed Computing at the Castings Solidificat...

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International Conference on Mechanical Engineering, Automation and Control Systems (MEACS)

作者： Ol'khovik, E. O. Butsanets, A. A. Ageeva, A. A. Admiral Makarov State Univ Maritime & Inland Ship Sci & Innovat Dept St Petersburg Russia

ISBN: (纸本)9781467381147

Realization control volume method for calculation of non-stationary task of heat conductivity is presented in the article. This method can be applied for simulation of metal casting solidification in sand mold and other application. Distinctive feature of the developed method is possibility of application of the distributed computing which provides a good result on calculation speed, however demands the bigger volume of random access memory. In the calculation example, for a grid from 1 million elements the increase in calculation speed by 15 divided by 20% was reached when using 2 cores of the Intel Core I-5 processor and by 30% when using 3 cores. Also there is a possibility of increase of calculations accuracy for the account of increase in quantity of calculated elements at identical calculation time.

关键词： parallel and distributed computing transient heat transfer solidification simulation finite element method

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Big Data Processing in the ATLAS Experiment: Use Cases and Experience

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Procedia Computer Science 2015年 66卷 609-618页

作者： Mikhail Borodin Kaushik De Jose Garcia Navarro Dmitry Golubkov Alexei Klimentov Tadashi Maeno David South Alexandre Vaniachine Big Data Laboratory National Research Centre “Kurchatov Institute” Moscow Russia National Research Nuclear University “MEPhI” Moscow Russia University of Texas Arlington TX U.S.A Instituto de Fisica Corpuscular Universidad de Valencia Spain Institute for High Energy Physics Protvino Russia Brookhaven National Laboratory NY U.S.A Deutsches Elektronen-Synchrotron Hamburg Germany Argonne National Laboratory IL U.S.A

The physics goals of the next Large Hadron Collider run include high precision tests of the Standard Model and searches for new physics. These goals require detailed comparison of data with computational models simulating the expected data behavior. To highlight the role which modeling and simulation plays in future scientific discovery, we report on use cases and experience with a unified system built to process both real and simulated data of growing volume and variety.

关键词： Big Data Grid-based Simulation and computing parallel and distributed computing Large Scale Scientific Instruments

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Large-scale distributed systems and energy efficiency : a holistic view /

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2015年

作者： edited by Jean-Marc Pierson.

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AzureRender: A Cloud-Based parallel and distributed Rendering System

AzureRender: A Cloud-Based Parallel and Distributed Renderin...

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IEEE International Symposium on Cyberspace Safety and Security

作者： Zhenbang Liu Hengming Zou School of Software Shanghai Jiao Tong University

ISBN: (纸本)9781479989386

Generally, image rendering requires high computing capacity. It is really time consuming to render a movie on a single machine. The use of multiple machines to render a move requires much effort to control the workflow and data. With the emergence of cloud computing, more and more scientists and engineers are moving their tasks from laboratories to public clouds. This migration requires some sort experience on both the cloud architecture and coding in the cloud. This paper proposes a simple service to render movies on Microsoft Azure that accelerates movie rendering. This service, called AzureRender, also introduces task parallelism and cache management to improve performance and reduce cost. A comparative study on image rendering performance and cost between Microsoft Azure and desktop machines is given at the end of the paper.

关键词： Cloud Service High Performance computing parallel and distributed computing Scientific computing Microsoft Azure

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NNB: An efficient nearest neighbor search method for hierarchical clustering on large datasets

NNB: An efficient nearest neighbor search method for hierarc...

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International Conference on Semantic computing

作者： Wei Zhang Gongxuan Zhang Yongli Wang Zhaomeng Zhu Tao Li School of Computer Science and Technology Huaiyin Normal University Huaian China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781479979363

Nearest neighbor search is a key technique used in hierarchical clustering. The time complexity of standard agglomerative hierarchical clustering is O(n 3 ), while the time complexity of more advanced hierarchical clustering algorithms (such as nearest neighbor chain) is O(n 2 ). This paper presents a new nearest neighbor search method called nearest neighbor boundary(NNB), which first divides a large dataset into independent subsets and then finds nearest neighbor of each point in the subsets. When NNB is used, the time complexity of hierarchical clustering can be reduced to O(n log 2 n). Based on NNB, we propose a fast hierarchical clustering algorithm called nearest-neighbor boundary clustering(NBC), and the proposed algorithm can also be adapted to the parallel and distributed computing frameworks. The experimental results demonstrate that our proposal algorithm is practical for large datasets.

关键词： Hierarchical clustering MapReduce nearest neighbor boundary parallel and distributed computing

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Asynchronous optimisation with the use of a cascade search algorithm

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COMPUTERS & CHEMICAL ENGINEERING 2014年 66卷 276-289页

作者： Cecelja, F. Kokossis, A. Du, D. Yang, S. Univ Surrey Ctr Proc & Informat Syst Engn Guildford GU2 7XH Surrey England Natl Tech Univ Athens Sch Chem Engn GR-15780 Athens Greece

This paper introduces the development of an asynchronous approach coupled with a cascade optimisation algorithm. The approach incorporates concepts of asynchronous Markov processes and introduces a search process that is benefiting from distributed computing infrastructures. The algorithm uses concepts of partitions and pools to store intermediate solutions and corresponding objectives. Population inflections are performed periodically to ensure that Markov processes, still independent and asynchronous, make arbitrary use of intermediate solutions. Tested against complex optimisation problems and in comparison with commonly used Tabu Search, the asynchronous cascade algorithm demonstrates a significant potential in distributed operations with favourable comparisons drawn against synchronous and quasi-asynchronous versions of conventional algorithms. (c) 2014 Elsevier Ltd. All rights reserved.

关键词： Markov processes Asynchronous optimisation parallel and distributed computing

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Preconditioners for Schwarz relaxation methods applied to differential algebraic equations

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2014年第8期91卷 1775-1789页

作者： Magoules, Frederic Laurent-Gengoux, Pascal Pruvost, Florent Ecole Cent Paris F-92295 Chatenay Malabry France

In this paper, the authors investigate the ability of Schwarz relaxation (SR) methods to deal with large systems of differential algebraic equations (DAEs) and assess their respective efficiency. Since the number of iterations required to achieve convergence of the classical SR method is strongly related to the number of subdomains and the time step size, two new preconditioning techniques are here developed. A preconditioner based on a correction using the algebraic equations is first introduced and leads to a number of iterations independent on the number of subdomains. A second preconditioner based on a correction using the Schur complement matrix makes the convergence independent on both the number of subdomains and the integration step size. Application on European electricity network is presented to outline the performance, efficiency, and robustness of the proposed preconditioning techniques for the solution of DAEs.

关键词： domain decomposition method Schwarz relaxation method Schur complement preconditioning techniques parallel and distributed computing differential algebraic equations power systems

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distributed localized bi-objective search

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2014年第3期239卷 731-743页

作者： Derbel, Bilel Humeauc, Jeremie Liefooghe, Arnaud Verel, Sebastien Univ Lille 1 CNRS LIFL F-59655 Villeneuve Dascq France Inria Lille Nord Europe F-59650 Villeneuve Dascq France Ecole Mines Douai Dept IA F-59508 Douai France Univ Littoral Cote Dopale LISIC F-62228 Calais France

We propose a new distributed heuristic for approximating the Pareto set of bi-objective optimization problems. Our approach is at the crossroads of parallel cooperative computation, objective space decomposition, and adaptive search. Given a number of computing nodes, we self-coordinate them locally, in order to cooperatively search different regions of the Pareto front. This offers a trade-off between a fully independent approach, where each node would operate independently of the others, and a fully centralized approach, where a global knowledge of the entire population is required at every step. More specifically, the population of solutions is structured and mapped into computing nodes. As local information, every node uses only the positions of its neighbors in the objective space and evolves its local solution based on what we term a 'localized fitness function'. This has the effect of making the distributed search evolve, over all nodes, to a high quality approximation set, with minimum communications. We deploy our distributed algorithm using a computer cluster of hundreds of cores and study its properties and performance on rho MNK-landscapes. Through extensive large-scale experiments, our approach is shown to be very effective in terms of approximation quality, computational time and scalability. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Multiple objective programming Combinatorial optimization parallel and distributed computing Evolutionary computation

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