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Towards a distributed Large-Scale Dynamic Graph Data Store 30

Towards a Distributed Large-Scale Dynamic Graph Data Store

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30th IEEE international parallel and distributed processing symposium (IPDPS)

作者： Iwabuchi, Keita Sallinen, Scott Pearce, Roger Van Essen, Brian Gokhale, Maya Matsuoka, Satoshi Lawrence Livermore Natl Lab Ctr Appl Sci Comp Lawrence KS 94550 USA Tokyo Inst Technol Dept Math & Comp Sci Tokyo Japan Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada Tokyo Inst Technol Global Sci Informat & Comp Ctr Tokyo Japan

ISBN: (纸本)9781509036820

In many graph applications, the structure of the graph changes dynamically over time and may require real time analysis. However, constructing a large graph is expensive, and most studies for large graphs have not focused on a dynamic graph data structure, but rather a static one. To address this issue, we propose DegAwareRHH, a high performance dynamic graph data store designed for scaling out to store large, scale-free graphs by leveraging compact hash tables with high data locality. We extend DegAwareRHH for multiple processes and distributed memory, and perform dynamic graph construction on large scale-free graphs using emerging 'Big Data HPC' systems such as the Catalyst cluster at LLNL. We demonstrate that DegAwareRHH processes a request stream 206.5x faster than a state-of-the-art shared-memory dynamic graph processing framework, when both implementations use 24 threads/processes to construct a graph with 1 billion edge insertion requests and 54 million edge deletion requests. DegAwareRHH also achieves a processing rate of over 2 billion edge insertion requests per second using 128 compute nodes to construct a large-scale web graph, containing 128 billion edges, the largest open-source real graph dataset to our knowledge.

关键词： Bigdata Graph processing

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distributed Local Search for Elastic Image Matching 2nd

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2nd international Conference on Swarm Intelligence Based Optimization (ICSIBO)

作者： Wang, Hongjian Mansouri, Abdelkhalek Creput, Jean-Charles Ruichek, Yassine Univ Technol Belfort Montbeliard IRTES SeT F-90010 Belfort France

ISBN: (纸本)9783319503073;9783319503066

We propose a distributed local search (DLS) algorithm, which is a parallel formulation of a local search procedure in an attempt to follow the spirit of standard local search metaheuristics. applications of different operators for solution diversification are possible in a similar way to variable neighborhood search. We formulate a general energy function to be equivalent to elastic image matching problems. A specific example application is stereo matching. Experimental results show that the GPU implementation of DLS seems to be the only method that provides an increasing acceleration factor as the instance size augments, among eight tested energy minimization algorithms.

关键词： parallel and distributed computing Variable neighborhood search Stereo matching Graphics processing unit

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Learning from internet: Handling uncertainty in robotic environment modeling 17

Learning from internet: Handling uncertainty in robotic envi...

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9th Asia-Pacific symposium on Internetware, Internetware 2017

作者： Li, Yiying Wang, Huaimin Ding, Bo Che, Huimin National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology ChangSha China

ISBN: (纸本)1595930361

Uncertainty is a great challenge for environment perception of autonomous robots. For instance, while building semantic maps (i.e., maps with semantic labels such as object names), the robot may encounter unexpected objects of which it has no knowledge. It will lead to inevitable failures in traditional environment modeling software. The abundant knowledge being accumulated on the Internet has the potential to assist robots to handle such kind of uncertainty. However, existing researches have not touched this issue yet. This paper proposes a cloud-based semantic mapping engine named SemaCloud, which can not only augment robot's environment modeling capability by the rich cloud resources but also cope with uncertainty by utilizing the Internet knowledge on necessary. It adopts a state-of-art Deep Neural Network (DNN) for real-time and accurate recognition of pre-trained objects. If an object is beyond the knowledge of this DNN, a special mechanism named QoS-aware cloud phase transition is triggered to seek help from existing recognition services on the Internet. By a set of carefullydesigned algorithms, it can maximize benefits and minimize the negative impacts on the Quality of Service (QoS) properties of robotic applications, which is essential to many robot scenarios. The experiments on both open datasets and real robots show that our work can handle uncertainty successfully in robotic semantic mapping without sacrificing critical real-time constraints. © 2017 Association for Computing Machinery.

关键词： Deep neural networks

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Subgraph Counting: Color Coding Beyond Trees 30

Subgraph Counting: Color Coding Beyond Trees

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30th IEEE international parallel and distributed processing symposium (IPDPS)

作者： Chakaravarthy, Venkatesan T. Kapralov, Michael Murali, Prakash Petrini, Fabrizio Que, Xinyu Sabharwal, Yogish Schieber, Baruch IBM Res Yorktown Hts NY 10598 USA Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9781509021406

The problem of counting occurrences of query graphs in a large data graph, known as subgraph counting, is fundamental to several domains such as genomics and social network analysis. Many important special cases (e.g. triangle counting) have received significant attention. Color coding is a very general and powerful algorithmic technique for subgraph counting. Color coding has been shown to be effective in several applications, but scalable implementations are only known for the special case of tree queries (i.e. queries of treewidth one). In this paper we present the first efficient distributed implementation for color coding that goes beyond tree queries: our algorithm applies to any query graph of treewidth 2. Since tree queries can be solved in time linear in the size of the data graph, our contribution is the first step into the realm of color coding for queries that require superlinear worst case running time. This superlinear complexity leads to significant load balancing problems on graphs with heavy tailed degree distributions. Our algorithm works around high degree nodes in the data graph, and achieves very good runtime and scalability on a diverse collection of data and query graph pairs. We also provide a theoretical analysis of our algorithmic techniques, exhibiting asymptotic improvements in runtime on random graphs with power law degree distributions, a popular model for real world graphs.

关键词： Motif counting approximate counting parallel algorithm

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Performance Improvement of Read Operations in distributed File System Through Anticipated parallel processing 2nd

Performance Improvement of Read Operations in Distributed Fi...

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2nd international Conference on Computer and Communication Technologies

作者： Rangaswamy, B. Geethanjali, N. Ragunathan, T. Kumar, B. Sudheer Prosoft Resources Pvt Ltd Hyderabad Andhra Pradesh India Sri Krishnadevaraya Univ Anantapur 515003 Andhra Pradesh India ACE Engn Coll Kancheepuram India

ISBN: (纸本)9788132225171;9788132225164

A distributed system (DS) consists of a set of computers networked together and gives an impression to the users that it is a single system. The main storage component to be used in a DS is distributed file system (DFS). The DFS is used as the main file storage system in the cloud computing systems. Most of the cloud-based applications require a good performance from the DFS as for as read operations are concerned. Many caching and pre-fetching techniques have been proposed in the literature for improving the performance of the DFS. But all of these techniques use synchronous approach which increases read access time. In the literature, a speculation-based technique has been proposed for improving the performance of read access in the DFS which implements asynchronous reading using client-side caching technique. In this paper, we have proposed a new read algorithm for the DFS based on asynchronous reading, client-side caching technique, and anticipated parallel processing. We have carried out performance analysis of the speculation-based algorithm and our proposed algorithm based on anticipated parallel processing. The results of analysis indicate that our proposed algorithm performs better than the earlier speculation-based algorithm.

关键词： File organization

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HPGraph: A High parallel Graph processing System Based on Flash Array

HPGraph: A High Parallel Graph Processing System Based on Fl...

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18th IEEE international Conference on High Performance Computing and Communications, 14th IEEE international Conference on Smart City and 2nd IEEE international Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016

作者： Xing, Yuxuan Feng, Ya Yu, Songping Chen, Zhengguo Liu, Fang Xiao, Nong State Key Lab. of High Performance Comput. Nat. Univ. of Defense Technol. Changsha China School of Data and Computer Science Sun Yat-sun University Guangzhou China

ISBN: (纸本)9781509042968

Large graphs analytics has been an important aspect of many big data applications, such as web search, social networks and recommendation systems. Many research focuses on processing large scale graphs using distributed system over past few years. And numbers of studies turn to construct graph processing system on a single server-class machine in consideration of cost, usability and maintainability. HPGraph is a high parallel graph processing system which adopts the edge-centric model, our contributions are as follows: (1) designing an efficient data allocation and access strategy for NUMA machine, and providing tasks scheduling to keep load balance, (2) raising a fine-grained edge-block filtering mechanism to avoid accessing unnecessary edge data, (3) constructing a high-speed flash array as the second storage. We made a detailed evaluation on a 16-core machine using asset of popular real word and synthetic data sets, and the results show that HPGraph always outperforms the state-of-the-art single machine graph processing systems-GridGraph. And HPGraph can achieve 1.27X faster than GridGraph for specific application. Our source code is available at https://***/xinghuan1990/HPGraph. © 2016 IEEE.

关键词： Scheduling

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2nd international Workshop on Brain-Inspired Computing, BrainComp 2015

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2nd international Workshop on Brain-Inspired Computing, BrainComp 2015

ISBN: (纸本)9783319508610

The proceedings contain 14 papers. The special focus in this conference is on Brain-Inspired Computing. The topics include: Human brainnetome atlas and its potential applications in brain-inspired computing;workflows for ultra-high resolution 3D models of the human brain on massively parallel supercomputers;including gap junctions into distributed neuronal network simulations;finite-difference time-domain simulation for three-dimensional polarized light imaging;visual processing in cortical architecture from neuroscience to neuromorphic computing;bio-inspired filters for audio analysis;sophisticated LVQ classification models - beyond accuracy optimization;classification of FDG-PET brain data by generalized matrix relevance LVQ;a cephalomorph real-time computer;towards the ultimate display for neuroscientific data analysis;sentiment analysis and affective computing;methods and applications and deep representations for collaborative robotics.

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20th East-European Conference on Advances in Databases and Information Systems, ADBIS 2016 and Workshop on 3rd international Workshop on Big Data applications and Principles, BigDap 2016, 2nd Workshop on Data-Centered Smart applications, DCSA 2016, Workshop on Doctoral Consortium, DC 2016

20th East-European Conference on Advances in Databases and I...

引用

20th East-European Conference on Advances in Databases and Information Systems, ADBIS 2016 and Workshop on 3rd international Workshop on Big Data applications and Principles, BigDap 2016, 2nd Workshop on Data-Centered Smart applications, DCSA 2016, Workshop on Doctoral Consortium, DC 2016

ISBN: (纸本)9783319440651

The proceedings contain 24 *** special focus in this conference is on Short Papers, Big Data applications and Principles, Data centered Smart applications and ADBIS Doctoral *** topics include: Towards automated performance optimization of BPMN business processes;pixel-based analysis of information dashboard attributes;towards adaptive distributed top-k query processing;basis functions as pivots in space of users preferences;towards semi-structured JSON big data;skyline algorithms on streams of multidimensional data;canonical data model for data warehouse;a quality-based query rewriting algorithm for data integration, towards spatial crowdsourcing in vehicular networks using mobile agents;shift of image processing technologies to column-oriented databases;influence of parallelism property of streaming engines on their performance;reducing big data by means of context-aware tailoring;feature ranking and selection for big data sets;a bagged associative classifier for big data frameworks;a new parallel approximate subspace clustering algorithm;smart modeling for lightweight mobile application development methods;an implementation method of an information credibility calculation system for emergency such as natural disasters;model capsules for research and engineering networks;usage of aspect-oriented programming in adaptive application structure;short-term user behaviour changes modelling and framework for managing distinct versions of data in relational databases.

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Towards An Effective and Efficient Approximation Algorithm for Advanced Computer Vision applications based on Two-Dimensional Dynamic Programming 22

Towards An Effective and Efficient Approximation Algorithm f...

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22nd international Conference on distributed Multimedia Systems (DMS 2016)

作者： Cuzzocrea, Alfredo Mumolo, Enzo Grasso, Giorgio Mario Vercelli, Gianni Univ Trieste DIA Dept I-34127 Trieste Italy ICAR CNR Arcavacata Di Rende CS Italy Univ Messina CSECS Dept I-98100 Messina Italy Univ Genoa DIBRIS Dept Genoa Italy

ISBN: (纸本)9781891706400

The Dynamic Programming Algorithm (DPA) was developed in the fifties. However, it is sometimes still used nowadays in various fields because it can easily find the global optimum in certain optimization problems. DPA has been applied to problems of one, two or three dimensions. When the dimension of the problem solved by DPA is equal to one the complexity of the algorithm is polynomial but if the size is greater than one, the complexity becomes NP complete. In such cases a practical implementation of the algorithm is possible only using some approximation. In this paper we present a novel approximation of the two-dimensional Dynamic Programming Algorithm (2D-DPA) with polynomial complexity. We then describe a parallel implementation of the algorithm on a recent Graphics processing Unit (GPU).

关键词： Graphics processing unit

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An accurate FDD-based approach for discovering distributed firewalls misconfigurations 15

An accurate FDD-based approach for discovering distributed f...

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Joint 15th IEEE international Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE international Conference on Big Data Science and Engineering and 14th IEEE international symposium on parallel and distributed processing with applications, IEEE TrustCom/BigDataSE/ISPA 2016

作者： Saâdaoui, Amina Souayeh, Nihel Ben Youssef Ben Bouhoula, Adel University of Carthage Tunisia

ISBN: (纸本)9781509032051

Problems arising from firewalls are common, cost time and money and have dramatic consequences for the operations of networks, especially in multi-firewall enterprise network. In fact, any misconfiguration that can arise between rules creates ambiguity in classification and filtering of the traffic. The discovery and removal of these misconfigurations is a serious and complex problem to solve. Several solutions have been proposed, though these methods are useful for discovering anomalies, most of them identify each overlap between two rules with different actions as a configuration error while, in some cases, network administrator add, intentionally, overlapping rules. Also, in a distributed environment, they deal only with pair-wise filtering rules in a simple firewall and they consider relations between only two firewalls even if a network path could contain more than two firewalls and anomaly could happen between different rules from different firewalls. In this paper, we present (1) a new classification of anomalies in multi-firewall environment bringing out real configurations errors, (2) we use a data structure (FDD) to represent relations between different rules in different firewalls in the network, (3) a new approach to rule-set optimization and clean-up by removing superfluous rules from a simple firewall and firewalls in a distributed environment and (4) formal specification and validation of proposed techniques, we also proved its correctness and completeness and demonstrated its scalability and applicability. © 2016 IEEE.

关键词： Computer system firewalls

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