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A semantic search engine in the cloud

A semantic search engine in the cloud

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8th international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Amato, Flora Gargiulo, Francesco Mazzeo, Antonino Romano, Sara Sansone, Carlo Univ Naples Federico II Dipartimento Ingn Elettr & Tecnol Informaz Naples Italy

ISBN: (纸本)9780769550947

Due to the ease of data production within the Internet era, knowledge workers are increasingly overwhelmed by information from multiple information sources and yet still find it hard to navigate and search for accessing the specific information required for the task at hand. this implies that knowledge worker productivity is reduced and that organizations may be making decisions on the basis of incomplete knowledge. Most search engines in use today strongly rely on keywords matching and on the ability of the user in the query expression. this leads to the retrieval of a large amount of irrelevant information with a direct impact on the user that spends a lot of time in browsing the results and/or to construct more complex queries to refine the search output. To overcome this limitation semantic-based solution are increasingly adopted. In this work we propose a general architecture that implements a semantic search engine in the cloud that exploits semantic technologies to retrieve and present the right information to the user. Our search engine is aimed at providing support in the task of document composition, suggesting to the user the adequate section that could be inserted within a document.

关键词： cloud computing query processing search engines

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Multi level parallelism of Multiple implicitly/explicitly restarted Arnoldi methods for post-petascale computing

Multi level parallelism of Multiple implicitly/explicitly re...

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8th international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Tsuji, Miwako Dandouna, Makarem Emad, Nahid Univ Versailles PRiSM Versailles France

ISBN: (纸本)9780769550947

the iterative methods are widely used to solve eigen problems in scientific computation. We focus on multiple restarted Arnoldi methods (MRAM) [4] which manage iterative co-methods to accelerate their convergence. these methods are considered as good candidate for emerging large scale computational systems thanks to their asynchronous communication schema, their potential load balancing and their multi-level parallelism. Both coarse grain parallelism between co-methods and fine grain parallelism inside each co-method need to be flexibly mapped to large scale distributed memory systems like hierarchical supercomputer, the cloud or P2P platforms. In this paper, we investigate such possibility in MRAMs by developing and executing them with a development and execution environment called FP2C (Framework for Post-Petascale Computing) [11]. the FP2C is a user-friendly and hierarchical-system-oriented development and execution environment based on workflow and distributed parallel methodologies. Our first goal is to show the feasibility of the approach FP2C to realize complex applications such as MRAMs. the next objective of the paper is to point out the adaptability of MRAMs to new generation of supercomputers (Petascale and futur Exascale). In addition, we show by our experiments that, collaboration of multiple iterative methods based on coarse grain parallelism accelerates convergence, and co-working processors within each iterative method based on fine grain parallelism accelerates the time per iteration.

关键词： iterative methods parallel machines parallel processing peer-to-peer computing

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Character of graph analysis workloads and recommended solutions on future parallel systems

Character of graph analysis workloads and recommended soluti...

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13th international conference on algorithms and architectures for parallel processing, ICA3PP 2013

作者： Tanabe, Noboru Tomimori, Sonoko Takata, Masami Joe, Kazuki Toshiba Research and Development Center Kawasaki Kanagawa 212-8582 Japan Nara Women's University Nara Nara 630-8506 Japan

ISBN: (纸本)9783319038582

Graph500 is a benchmark suite for big data analysis. Matrices used for Graph500 inherit the properties of graph analysis such as breadth first search for SNS and PageRank for web searching engine. Especially power saving is very important for its execution on future massively parallel processors and clouds. the spatial locality of sparse matrices used for Graph500 and its behaviors on cache memory are investigated. the experimental results show the spatial locality of sparse matrices used for Graph500 is very low. It is very difficult to solve the problem by just software approach because of the huge size and the randomness of their accesses. therefore, we recommend hardwired scatter/gather functions at memory side. they improve the processing speed in an order of magnitude. For achieving both of low power and high throughput of random access, we recommend implementing hardwired scatter/gather functions on logic-base in Hybrid Memory Cube (HMC). We also describe brief considerations of the power saving in the case of low cache hit rate application such as graph500. For example, when the hit rate is 15%, the power saving ratio of memory access is about 30-fold. © Springer international Publishing Switzerland 2013.

关键词： Cache memory

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Visual Data Encryption for Privacy Enhancement in Surveillance Systems 1

引用

15th international conference on Advanced Concepts for Intelligent Vision Systems (ACIVS)

作者： Cichowski, Janusz Czyzewski, Andrzej Kostek, Bozena Gdansk Univ Technol Multimedia Syst Dept Narutowicza 11-12 PL-80233 Gdansk Poland Gdansk Univ Technol Audio Acoust Lab PL-80233 Gdansk Poland

ISBN: (数字)9783319028958

ISBN: (纸本)9783319028958;9783319028941

In this paper a methodology for employing reversible visual encryption of data is proposed. the developed algorithms are focused on privacy enhancement in distributed surveillance architectures. First, motivation of the study performed and a short review of preexisting methods of privacy enhancement are presented. the algorithmic background, system architecture along with a solution for anonymization of sensitive regions of interest are described. An analysis of efficiency of the developed encryption approach with respect to visual stream resolution and the number of protected objects is performed. Experimental procedures related to stream processing on a single core, single node and multiple nodes of the supercomputer platform are also provided. the obtained results are presented and discussed. Moreover, possible future improvements of the methodology are suggested.

关键词： privacy protection data security information security cryptography multicore processing

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Image guided cost aggregation for hierarchical depth map fusion

Image guided cost aggregation for hierarchical depth map fus...

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8th international conference on Computer Vision theory and Applications, VISAPP 2013

作者： Borgmann, thilo Sikora, thomas Communication Systems Group Technische Universität Berlin Berlin Germany

ISBN: (纸本)9789898565471

Estimating depth from a video sequence is still a challenging task in computer vision with numerous applications. Like other authors we utilize two major concepts developed in this field to achieve that task which are the hierarchical estimation of depth within an image pyramid as well as the fusion of depth maps from different views. We compare the application of various local matching methods within such a combined approach and can show the relative performance of local image guided methods in contrast to commonly used fixed-window aggregation. Since efficient implementations of these image guided methods exist and the available hardware is rapidly enhanced, the disadvantage of their more complex but also parallel computation vanishes and they will become feasible for more applications.

关键词： Stereo image processing

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Language and Automata theory and Applications: 7th international conference, LATA 2013, Bilbao, Spain, April 2-5, 2013, Proceedings

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2013年

作者： Adrian Horia Dediu Carlos Martn-Vide Bianca Truthe

ISBN: (纸本)9783642370656

this book constitutes the refereed proceedings of the 7th international conference on Language and Automata theory and Applications, LATA 2013, held in Bilbao, Spain in April 2013. the 45 revised full papers presented together with 5 invited talks were carefully reviewed and selected from 97 initial submissions. the volume features contributions from both classical theory fields and application areas (bioinformatics, systems biology, language technology, artificial intelligence, etc.). Among the topics covered are algebraic language theory; algorithms for semi-structured data mining; algorithms on automata and words; automata and logic; automata for system analysis and program verification; automata, concurrency and Petri nets; automatic structures; cellular automata; combinatorics on words; computability; computational complexity; computational linguistics; data and image compression; decidability questions on words and languages; descriptional complexity; DNA and other models of bio-inspired computing; document engineering; foundations of finite state technology; foundations of XML; fuzzy and rough languages; grammars (Chomsky hierarchy, contextual, multidimensional, unification, categorial, etc.); grammars and automata architectures; grammatical inference and algorithmic learning; graphs and graph transformation; language varieties and semigroups; language-based cryptography; language-theoretic foundations of artificial intelligence and artificial life; parallel and regulated rewriting; parsing; pattern recognition; patterns and codes; power series; quantum, chemical and optical computing; semantics; string and combinatorial issues in computational biology and bioinformatics; string processing algorithms; symbolic dynamics; symbolic neural networks; term rewriting; transducers; trees, tree languages and tree automata; weighted automata.

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Work efficient parallel algorithms for large graph exploration

Work efficient parallel algorithms for large graph explorati...

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international conference on High Performance Computing

作者： Dip Sankar Banerjee Shashank Sharma Kishore Kothapalli International Institute of Information Technology Hyderabad India

Graph algorithms play a prominent role in several fields of sciences and engineering. Notable among them are graph traversal, finding the connected components of a graph, and computing shortest paths. there are several efficient implementations of the above problems on a variety of modern multiprocessor architectures. It can be noticed in recent times that the size of the graphs that correspond to real world data sets has been increasing. parallelism offers only a limited succor to this situation as current parallel architectures have severe short-comings when deployed for most graph algorithms. At the same time, these graphs are also getting very sparse in nature. this calls for particular work efficient solutions aimed at processing large, sparse graphs on modern parallel architectures. In this paper, we introduce graph pruning as a technique that aims to reduce the size of the graph. Certain elements of the graph can be pruned depending on the nature of the computation. Once a solution is obtained for the pruned graph, the solution is extended to the entire graph. We apply the above technique on three fundamental graph algorithms: breadth first search (BFS), Connected Components (CC), and All Pairs Shortest Paths (APSP). To validate our technique, we implement our algorithms on a heterogeneous platform consisting of a multicore CPU and a GPU. On this platform, we achieve an average of 35% improvement compared to state-ofthe-art solutions. Such an improvement has the potential to speed up other applications that rely on these algorithms.

关键词： Graphics processing units Arrays Algorithm design and analysis parallel architectures Instruction sets parallel processing

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Adaptive task size control on high level programming for GPU/CPU work sharing

Adaptive task size control on high level programming for GPU...

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13th international conference on algorithms and architectures for parallel processing, ICA3PP 2013

作者： Odajima, Tetsuya Boku, Taisuke Sato, Mitsuhisa Hanawa, Toshihiro Kodama, Yuetsu Namyst, Raymond thibault, Samuel Aumage, Olivier Graduate School of Systems and Information Engineering University of Tsukuba Japan Center for Computational Sciences University of Tsukuba Japan University of Bordeaux LaBRI INRIA Bordeaux Sud-Ouest France

ISBN: (纸本)9783319038889

On the work sharing among GPUs and CPU cores on GPU equipped clusters, it is a critical issue to keep load balance among these heterogeneous computing resources. We have been developing a runtime system for this problem on PGAS language named XcalableMP-dev/ StarPU [1]. through the development, we found the necessity of adaptive load balancing for GPU/CPU work sharing to achieve the best performance for various application codes. In this paper, we enhance our language system XcalableMP-dev/ StarPU to add a new feature which can control the task size to be assigned to these heterogeneous resources dynamically during application execution. As a result of performance evaluation on several benchmarks, we confirmed the proposed feature correctly works and the performance with heterogeneous work sharing provides up to about 40% higher performance than GPU-only utilization even for relatively small size of problems. © Springer international Publishing Switzerland 2013.

关键词： Graphics processing unit

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OpenOF: Framework for sparse non-linear least squares optimization on a GPU

OpenOF: Framework for sparse non-linear least squares optimi...

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8th international conference on Computer Vision theory and Applications, VISAPP 2013

作者： Wefelscheid, Cornelius Hellwich, Olaf Computer Vision and Remote Sensing Berlin University of Technology Sekr. MAR 6-5 Marchstrasse 23 D-10587 Berlin Germany

ISBN: (纸本)9789898565471

In the area of computer vision and robotics non-linear optimization methods have become an important tool. For instance, all structure from motion approaches apply optimizations such as bundle adjustment (BA). Most often, the structure of the problem is sparse regarding the functional relations of parameters and measurements. the sparsity of the system has to be modeled within the optimization in order to achieve good performance. With OpenOF, a framework is presented, which enables developers to design sparse optimizations regarding parameters and measurements and utilize the parallel power of a GPU. We demonstrate the universality of our framework using BA as example. the performance and accuracy is compared to published implementations for synthetic and real world data.

关键词： Graphics processing unit

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A linguistic-based method for automatically extracting spatial relations from large non-structured data

A linguistic-based method for automatically extracting spati...

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13th international conference on algorithms and architectures for parallel processing, ICA3PP 2013

作者： Elia, Annibale Guglielmo, Daniela Maisto, Alessandro Pelosi, Serena Department of Political Social and Communication Science SemanticItaLab University of Salerno via Giovanni Paolo II 132 84084 Fisciano Italy Department of Electric Engineering and Information Technologies University of Naples Federico II via Claudio 21 80125 Napoli Italy

ISBN: (纸本)9783319038889

this paper presents a Lexicon-Grammar based method for automatic extraction of spatial relations from Italian non-structured data. We used the software Nooj to build sophisticated local grammars and electronic dictionaries associated with the lexicon-grammar classes of the Italian intransitive spatial verbs (i.e. 234 verbal entries) and we applied them to the Italian text Il Codice da Vinci ('the Da Vinci Code', by Dan Brown) in order to parse the spatial predicate-arguments structures. In addition, Nooj allowed us to automatically annotate (in XML format) the words (or the sequence of words) that in each sentence (S) of the text play the 'spatial roles' of Figure (F), Motion (M) and Ground (G). Finally the results of the experiment and the evaluation of this method will be discussed. © Springer international Publishing Switzerland 2013.

关键词： Natural language processing systems

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