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检索条件"任意字段=13th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2013"

共 35 条记录，以下是11-20 订阅

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PSIS: parallel semantic indexing system-preliminary experiments

PSIS: Parallel semantic indexing system-preliminary experime...

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13th international conference on algorithms and architectures for parallel processing, ica3pp 2013

作者： Amato, Flora Gargiulo, Francesco Moscato, Vincenzo Persia, Fabio Picariello, Antonio University of Naples Federico II Dipartimento di Ingegneria Elettrica e Tecnologie Dell'Informazione via Claudio 21 80125 Naples Italy Italy

ISBN: (纸本)9783319038889

In this paper, we address the problem of defining a semantic indexing techniques based on RDF triples. In particular, we define algorithms for: i) defining clustering techniques of semantically similar RDF triplets;ii) defining algorithms for inserting, deleting and searching on a K-d based semantic tree built on the base of such clusterings;iii) defining a parallel implementation of the search algorithms. Preliminary experiments runned on a GRID-based parallel machines are designed and preliminary implemented and discusses, showing the performances of the proposed system. © Springer international Publishing Switzerland 2013.

关键词： Resource Description Framework (RDF)

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New Multi-objectives Scheduling Strategies in Docker SwarmKit 18th

New Multi-objectives Scheduling Strategies in Docker SwarmKi...

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18th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Menouer, Tarek Cerin, Christophe Leclercq, Etienne Univ Paris 13 Sorbonne Paris Cite LIPN CNRS UMR 7030 F-93430 Villetaneuse France

ISBN: (纸本)9783030050573;9783030050566

this paper presents new multi-objectives scheduling strategies implemented in Docker SwarmKit. Docker SwarmKit is a container toolkit for orchestrating distributed systems at any scale. Currently, Docker SwarmKit has one scheduling strategy called Spread. Spread is based only on one objective to select from a set of cloud nodes, one node to execute a container. However, the containers submitted by users to be scheduled in Docker SwarmKit are configured according to multi-objectives criteria, as the number of CPUs and the memory size. To better address the multi-objectives configuration problem of containers, we introduce the concept and the implementation of new multi-objectives scheduling strategies adapted for Cloud Computing environments and implemented in Docker SwarmKit. the principle of our multi-objectives strategies consist to select a node which has a good compromise between multi-objectives criteria to execute a container. the proposed scheduling strategies are based on a combinaison of PROMEthEE and Kung multi-objectives decision algorithms in order to place containers. the implementation in Docker SwarmKit and experiments of our new strategies demonstrate the potential of our approach under different scenarios.

关键词： Systems software Scheduling and resource management Container technology Cloud computing Application of parallel and distributed algorithms

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Efficient algorithms of parallel Skyline Join over Data Streams 18th

Efficient Algorithms of Parallel Skyline Join over Data Stre...

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18th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Zhang, Jinchao Gu, JingZi Cheng, Shuai Li, Bo Wang, Weiping Meng, Dan Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9783030050511;9783030050504

the issue of finding skyline tuples over multiple relations, more commonly known as the skyline join problem, has been well studied in scenarios in which the data is static. Most recently, it has become a new trend that performing skyline queries on data streams, where tuples arrive or expire in a continuous approach. A few algorithms have been proposed for computing skylines on two data streams. However, those literatures did not consider the inherent parallelism, or employ serial algorithms to solve the skyline query problem, which cannot leverage the multi-core processors. Based on this motivation, in this paper, we address the problem of parallel computing for skyline join over multiple data streams. We developed a Novel Iterative framework based on the existing work and study the inherent parallelism of the Novel Iterative framework. then we propose two parallel skyline join algorithms over sliding windows, NP-SWJ and IP-SWJ. To the best of our knowledge, this is the first paper that addresses parallel computing of skyline join over multiple data streams. Extensive experimental evaluations on real and synthetic data sets show that the algorithms proposed in this paper provide large gains over the state-of-the-art serial algorithm of skyline join over data streams.

关键词： Skyline join Sliding window Data stream parallel computing

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GPU-Based Heterogeneous Coding Architecture for HEVC 16th

GPU-Based Heterogeneous Coding Architecture for HEVC

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Cebrian-Marquez, Gabriel Migallon, Hector Luis Martinez, Jose Lopez-Granado, Otoniel Pinol, Pablo Cuenca, Pedro Univ Castilla La Mancha Albacete Res Inst Informat I3A Plz Univ 2 Albacete 02071 Spain Miguel Hernandez Univ Dept Phys & Comp Architecture Elche 03202 Spain

ISBN: (纸本)9783319495835;9783319495828

the High Efficiency Video Coding (HEVC) standard has nearly doubled the compression efficiency of prior standards. Nonetheless, this increase in coding efficiency involves a notably higher computing complexity that should be overcome in order to achieve real-time encoding. For this reason, this paper focuses on applying parallel processing techniques to the HEVC encoder with the aim of reducing significantly its computational cost without affecting the compression performance. Firstly, we propose a coarse-grained slice-based parallelization technique that is executed in a multi-core CPU, and then, with finer level of parallelism, a GPU-based motion estimation algorithm. Both techniques define a heterogeneous parallel coding architecture for HEVC. Results show that speed-ups of up to 4.06x can be obtained on a quad-core platform with low impact in coding performance.

关键词： H.265 HEVC Heterogeneous parallel encoding GPU

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A Platform for Stock Market Simulation with Distributed Agent-Based Modeling 1

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14th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Wang, Chunyu Yu, Ce Wu, Hutong Chen, Xiang Li, Yuelei Zhang, Xiaotao Tianjin Univ Sch Comp Sci & Technol Tianjin 300072 Peoples R China Tianjin Univ Sch Econ & Management Tianjin Peoples R China

ISBN: (数字)9783319111940

ISBN: (纸本)9783319111940;9783319111933

Agent-based modeling (ABM) has been widely used in stock market simulation. However, traditional simulations of stock markets with ABM on single computers are limited by the computing capability as breakthroughs in financial research need much larger amount of agents. this paper introduces a platform for stock market simulation with ABM focusing on large scale parallel agents in a distributed computing environment such as Cluster and Mpp. With the customized trade strategies inside the agents, the runtime system of the platform can distribute the massive amount of agents to multiple computing nodes automatically during the execution of the simulation. And agents exchange information with each other and the market through a uniform communication system. With this platform financial researchers can design their own financial model without caring about the complexity of parallelization and related problems. the sample simulation on the platform is verified to be compatible with the data from Euronext-NYSE and the platform shows fair scalability and performance under different parallelism configurations.

关键词： stock market simulation agent-based modeling parallel distributed environment

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Torus-connected cycles: An implementation-friendly topology for interconnection networks of massively parallel systems

Torus-connected cycles: An implementation-friendly topology ...

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13th international conference on algorithms and architectures for parallel processing, ica3pp 2013

作者： Bossard, Antoine Kaneko, Keiichi Advanced Institute of Industrial Technology Tokyo Metropolitan University Japan Graduate School of Engineering Tokyo University of Agriculture and Technology Japan

ISBN: (纸本)9783319038889

the number of nodes inside supercomputers is continuously increasing. As detailed in the TOP500 list, there are now systems that include more than one million nodes;for instance China's Tianhe-2. To cope with this huge number of cores, many interconnection networks have been proposed in the literature. However, in most cases, proposed topologies have shown gaps preventing these topologies from being actually implemented and manufactured. In this paper, we propose a new, implementation-friendly, topology for interconnection networks of massively parallel systems: torus-connected cycles (TCC). Torus-based networks have proven very popular in the recent years: the Fujitsu K and Cray Titan are two examples of supercomputers whose interconnection networks are based on the torus topology. © Springer international Publishing Switzerland 2013.

关键词： Topology

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Multi-objective parallel machines scheduling for fault-tolerant cloud systems

Multi-objective parallel machines scheduling for fault-toler...

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13th international conference on algorithms and architectures for parallel processing, ica3pp 2013

作者： Gasior, Jakub Seredyński, Franciszek Systems Research Institute Polish Academy of Sciences Warsaw Poland Cardinal Stefan Wyszynski University Warsaw Poland

ISBN: (纸本)9783319038582

We present in this paper a security-driven solution for scheduling of N independent jobs on M parallel machines that minimizes three different objectives simultaneously, namely the failure probability, the total completion time of the jobs and their respective tardiness. As this problem is NP-hard in the strong sense, a meta-heuristic method NSGA-II is proposed to solve it. this approach is based on the Pareto dominance relationship, providing no single optimal solution, but a set of solutions which are not dominated by each other. thus, it was necessary to provide decision-making mechanisms selecting the best strategy from the Pareto frontier. the performance of the presented model and the applied GA is verified by a number of numerical experiments. the related results show the effectiveness of the proposed model and GA for small and mediumsized scheduling problems. © Springer international Publishing Switzerland 2013.

关键词： Multiobjective optimization

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A Distributed Framework for Online Stream Data Clustering 20th

A Distributed Framework for Online Stream Data Clustering

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20th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Ding, Jiafeng Fang, Junhua Chao, Pingfu Xu, Jiajie Zhao, PengPeng Zhao, Lei Soochow Univ Dept Comp Sci & Technol Suzhou Peoples R China Univ Queensland Brisbane Qld Australia

ISBN: (纸本)9783030602451;9783030602444

the recent prevalence of positioning sensors and mobile devices generates a massive amount of spatial-temporal data from moving objects in real-time. As one of the fundamental processes in data analysis, the clustering on spatial-temporal data creates various applications, like event detection and travel pattern extraction. However, most of the existing works only focus on the offline scenario, which is not applicable to online time-sensitive applications due to their low efficiency and ignorance of temporal features. In this paper, we propose a distributed streaming framework for spatial-temporal data clustering, which accepts various clustering algorithms while ensuring low resource consumption and result correctness. the framework includes a dynamic partitioning strategy for continuous load-balancing and a cluster-merging algorithm based on convex hulls [10], which guarantees the result correctness. Extensive experiments on real dataset prove the effectiveness of our proposed framework and its advantage over existing solutions.

关键词： Real-time cluster analysis Distributed stream processing Spatial-temporal data mining Top-k query parallel computing

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Message from the ica3pp 2013 program chairs

Lecture Notes in Computer Science (including subseries Lectu...

引用

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2013年第PART 1期8285 LNCS卷 vii-viii页

作者： Kolodziej, Joanna Talia, Domenico Xiong, Kaiqi

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parallel social influence model with Levy flight pattern introduced for large-graph mining on ***

Parallel social influence model with Levy flight pattern int...

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13th international conference on algorithms and architectures for parallel processing, ica3pp 2013

作者： Wu, Benbin Yang, Jing He, Liang Department of Computer Science and Technology East China Normal University 200241 Shanghai China

ISBN: (纸本)9783319038889

With a suitable method to rank the user influence in micro-blogging service, we could get influential individuals to make information reach large populations. Here a novel parallel social influence model is proposed to face to these challenges. In this paper, we firstly propose impact factors named Social Network Centricity and Weibo Heat Trend, describe a general algorithm named ActionRank to calculate the user influence based on these factors and the user-weibo behavior graph. Secondly, we introduce the Levy flight pattern into ActionRank, for the random large distance jumping phenomenon and the power-law distribution of the retweet cascade hops on *** meet its requirement. thirdly, the parallel ActionRank is proposed with the help of MapReduce for large-scale graphs. Experiment results demonstrate that ActionRank on Levy flight pattern outperforms other algorithms and show the consistency of parallel ActionRank on datasets with sizes ranging from 20M to 1100 M edges. © Springer international Publishing Switzerland 2013.

关键词： MapReduce

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