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Artificial Intelligence and Soft Computing: 14th international conference, ICAISC 2015, Zakopane, Poland, June 14-28, 2015, Proceedings, Part II 1

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丛书名： Lecture Notes in Computer Science 9119

2015年

作者： Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (eds.)

ISBN: (数字)9783319193687;9783319193694

ISBN: (纸本)9783319193687;9783319193694

The two-volume set LNAI 9119 and LNAI 9120 constitutes the refereed proceedings of the 14th international conference on Artificial Intelligence and Soft Computing, ICAISC 2015, held in Zakopane, Poland in June 2015. The 142 revised full papers presented in the volumes, were carefully reviewed and selected from 322 submissions. These proceedings present both traditional artificial intelligence methods and soft computing techniques. The goal is to bring together scientists representing both areas of research. The first volume covers topics as follows neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, classification and estimation, computer vision, image and speech analysis and the workshop: large-scale visual recognition and machine learning. The second volume has the focus on the following subjects: data mining, bioinformatics, biometrics and medical applications, concurrent and parallel processing, agent systems, robotics and control, artificial intelligence in modeling and simulation and various problems of artificial intelligence.

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Handling Big Data Efficiently by using Map Reduce Technique

Handling Big Data Efficiently by using Map Reduce Technique

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2015 IEEE international conference on Computational Intelligence & Communication Technology (CICT 2015)

作者： Maitrey, Seema Jha, C. K. Krishna Inst Engn & Technol Dept CSE Ghaziabad UP India Banasthali Univ Dept CSE Niwai Rajasthan India

ISBN: (纸本)9781479960224

Extremely large amount of data is being captured by today's organizations and is continue to increase. It becomes computationally inefficient to analyze such huge data. Research in data mining has addressed problem in discovering knowledge from these continuously growing large data sets. The amount of raw data available has been increasing at an exponential rate. The valuable information is hidden in large databases. Data mining has become an interesting area to extract the embedded precious information from them. For many years it has been found its root in all kinds of application areas. Thus, gave evolution to many data mining methods which started to get applied in several real life fields. But not all the methods possess the capability to deal with and handle the huge collection of data. In recent years, numbers of computation and data intensive scientific data analyses are established. To perform the large scale data mining analyses so as to meet the scalability and performance requirements of big data, several efficient parallel and concurrent algorithms got applied. A lot of parallel algorithms are put into action using different parallelization techniques. Among them, some common techniques used are threads, MPI, MapReduce etc. which yield different performance and usability characteristics. In computing rigorous problems, the MPI model works efficiently. But it is a complicated task to bring this model into the practical use. There is currently considerable enthusiasm around the MapReduce paradigm for large-scale data analysis. It is inspired by functional programming which allows expressing distributed computations on massive amounts of data. It is designed for large-scale data processing as it allows to run on clusters of commodity hardware. A prominent parallel data processing tool MapReduce is gaining significant momentum from both industry and academia as the volume of data to analyze grows rapidly. In this paper, we are going to work around MapReduce

关键词： Data Mining Clustering DBMS parallel processing Hadoop MapReduce

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A distributed PMU for Electrical Substations With Wireless Redundant Process Bus

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2015年第5期64卷 1149-1157页

作者： Castello, Paolo Ferrari, Paolo Flammini, Alessandra Muscas, Carlo Pegoraro, Paolo Attilio Rinaldi, Stefano Univ Cagliari Dept Elect & Elect Engn I-09124 Cagliari Italy Univ Brescia Dept Informat Engn I-25100 Brescia Italy

Protection and measurement systems in electrical substations are required to have high availability. In an all-digital substation protection system, all the components (instrument transformers, processing units, merging units, intelligent electronic devices, communication network, and synchronization source) may affect the overall availability level. In this paper, a solution to enhance distributed PMU availability, during wired network failures, is presented. In the proposed scheme, the process bus has two parallel networks: 1) the classic wired Ethernet link and 2) a wireless link (implemented with industrial grade IEEE 802.11 devices), for sampled values packets, which carry measurement information. The time synchronization is carried out only through the wired Ethernet link, but the proposed solution is still able to compensate temporary failures of one of the communication links. Experimental tests have been performed to verify the performance of additional IEEE 802.11 link using different protocols and configurations. Communication parameters that can affect the PMU performance, like propagation latency, are characterized. It is shown that, if the measurement algorithm is opportunely designed, depending on the wireless link quality, it is possible to comply, with a single output, with M and P classes of the synchrophasor standard also during network restoration or, at least, to safeguard protection applications if higher latency occurs.

关键词： Availability communication latency measure hybrid network IEEE 802.11 phasor measurement unit (PMU) process bus substation automation system (SAS) synchrophasor wireless LAN

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distributed monitoring and management of exascale systems in the Argo project 15

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15th IFIP WG 6.1 international conference on distributed applications and Interoperable Systems, DAIS 2015 Held as Part of the 10th international Federated conference on distributed Computing techniques, DisCoTec 2015

作者： Perarnau, Swann Thakur, Rajeev Iskra, Kamil Raffenetti, Ken Cappello, Franck Gupta, Rinku Beckman, Pete Snir, Marc Hoffmann, Henry Schulz, Martin Rountree, Barry Argonne National Laboratory LemontIL60439 United States University of Chicago ChicagoIL60637 United States Lawrence Livermore National Laboratory LivermoreCA94550 United States

ISBN: (纸本)9783319191287

New computing technologies are expected to change the high-performance computing landscape dramatically. Future exascale systems will comprise hundreds of thousands of compute nodes linked by complex networks—resources that need to be actively monitored and controlled, at a scale difficult to manage from a central point as in previous systems. In this context, we describe here on-going work in the Argo exascale software stack project to develop a distributed collection of services working together to track scientific applications across nodes, control the power budget of the system, and respond to eventual failures. Our solution leverages the idea of enclaves: a hierarchy of logical partitions of the system, representing groups of nodes sharing a common configuration, created to encapsulate user jobs as well as by the user inside its own job. These enclaves provide a second (and greater) level of control over portions of the system, can be tuned to manage specific scenarios, and have dedicated resources to do so. © IFIP international Federation for Information processing 2015.

关键词： Complex networks

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I/O Optimization in the Checkpointing of OpenMP parallel applications

I/O Optimization in the Checkpointing of OpenMP Parallel App...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Nuria Losada María J. Martín Gabriel Rodríguez Patricia González Computer Architecture Group University of A Coruña Spain

Despite the increasing popularity of shared-memory systems, there is a lack of tools for providing fault tolerance support to shared-memory applications. Check pointing is one of the most popular fault tolerance techniques. However, check pointing cost in terms of computing time, network utilization or storage resources can be a limitation for its practical use. This work proposes different techniques for the optimization of the I/O cost in the check pointing of shared-memory parallel applications. The proposals are extensively evaluated using the OpenMP NAS parallel Benchmarks. Results show a significant decrease of the check pointing overhead.

关键词： Checkpointing Instruction sets Optimization Runtime Instruments Fault tolerance Fault tolerant systems

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Architecture Aware Resource Allocation for Structured Grid applications: Flood Modelling Case 15

Architecture Aware Resource Allocation for Structured Grid A...

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2015 15th IEEE ACM international Symposium on Cluster Cloud and Grid Computing (CCGrid 2015)

作者： Saxena, Vaibhav George, Thomas Sabharwal, Yogish Real, Lucas Villa IBM Res New Delhi India IBM Res Sao Paulo Brazil

ISBN: (纸本)9781479980062

Numerous problems in science and engineering involve discretizing the problem domain as a regular structured grid and make use of domain decomposition techniques to obtain solutions faster using high performance computing. However, the load imbalance of the workloads among the various processing nodes can cause severe degradation in application performance. This problem is exacerbated for the case when the computational workload is non-uniform and the processing nodes have varying computational capabilities. In this paper, we present novel local search algorithms for regular partitioning of a structured mesh to heterogeneous compute nodes in a distributed setting. The algorithms seek to assign larger workloads to processing nodes having higher computation capabilities while maintaining the regular structure of the mesh in order to achieve a better load balance. We also propose a distributed memory (MPI) parallelization architecture that can be used to achieve a parallel implementation of scientific modeling software requiring structured grids on heterogeneous processing resources involving CPUs and GPUs. Our implementation can make use of the available CPU cores and multiple GPUs of the underlying platform simultaneously. Empirical evaluation on real world flood modeling domains on a heterogeneous architecture comprising of multicore CPUs and GPUs suggests that the proposed partitioning approach can provide a performance improvement of up to 8x over a naive uniform partitioning.

关键词： Computational modeling Graphics processing units Partitioning algorithms Load modeling Predictive models Computer architecture

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parallel Architectures and Compilation techniques - conference Proceedings, PACT

Parallel Architectures and Compilation Techniques - Conferen...

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24th international conference on parallel Architecture and Compilation, PACT 2015

The proceedings contain 48 papers. The topics discussed include: phase aware warp scheduling: mitigating effects of phase behavior in GPGPU applications;NVMMU: a non-volatile memory management unit for heterogeneous GPU-SSD architectures;exploiting inter-warp heterogeneity to improve GPGPU performance;scalable SIMD-efficient graph processing on GPUs;parallel methods for verifying the consistency of weakly-ordered architectures;stadium hashing: scalable and flexible Hashing on GPUs;TSXProf: profiling hardware transactions;ALEA: fine-grain energy profiling with basic block sampling;towards general-purpose neural network computing;practical near-data processing for in-memory analytics frameworks;scalable task scheduling and synchronization using hierarchical effects;PENCIL: a platform-neutral compute intermediate language for accelerator programming;communication avoiding algorithms: analysis and code generation for parallel systems;and exploiting program semantics to place data in hybrid memory.

关键词： Neural networks

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15th international conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

15th International Conference on Algorithms and Architecture...

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15th international conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

ISBN: (纸本)9783319271361

The proceedings contain 59 papers. The special focus in this conference is on applications of parallel and distributed Computing. The topics include: On exploring a virtual agent negotiation inspired approach for route guidance in urban traffic networks;optimization of binomial option pricing on intel MIC heterogeneous system;stencil computations on HPC-oriented ARMv8 64-bit multi-core processor;a particle swarm optimization algorithm for controller placement problem in software defined network;a streaming execution method for multi-services in mobile cloud computing;economy-oriented deadline scheduling policy for render system using IaaS cloud;towards detailed tissue-scale 3D simulations of electrical activity and calcium handling in the human cardiac ventricle;task parallel implementation of matrix multiplication on multi-socket multi-core architectures;refactoring for separation of concurrent concerns;exploiting scalable parallelism for remote sensing analysis models by data transformation graph;resource-efficient vibration data collection in cyber-physical systems;a new approach for vehicle recognition and tracking in multi-camera traffic system;a scalable distributed fingerprint identification system;energy saving and load balancing for SDN based on multi-objective particle swarm optimization;pre-stack kirchhoff time migration on hadoop and spark;a cyber physical system with GPU for CNC applications;a solution of the controller placement problem in software defined networks;parallel column subset selection of kernel matrix for scaling up support vector machines;real-time deconvolution with GPU and spark for big imaging data analysis and parallel kirchhoff pre-stack depth migration on large high performance clusters.

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The Multifractal Load Balancing Method 2

The Multifractal Load Balancing Method

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2nd international Scientific-Practical conference Problems of Infocommunications Science and Technology (PIC S&T 2015)

作者： Ivanisenko, Igor Radivilova, Tamara Kharkiv Natl Univ Radio Elect Dept Appl Math Kharkov Ukraine Kharkiv Natl Univ Radio Elect Dept Telecommun Syst Dept Kharkov Ukraine

ISBN: (纸本)9789669751928

The load-balancing system, built on the basis of a subsystem load balancer and subsystem control and monitoring that closely interact with each other was propose in work. This system is presented as a queuing system with priority service discipline. In the described queuing system parallel processing flow applications occur in the multiple serving devices and successive junction of them into unified stream is done. The method of multifractal load balancing is submited on the basis of the developed system of load balancing.

关键词： load balancing distributed system queuing system multifractal traffic resource utilization self similar

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CodHoop: A System for Optimizing Big Data processing 9

CodHoop: A System for Optimizing Big Data Processing

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9th Annual IEEE international Systems conference (SysCon)

作者： Asad, Zakia Chaudhry, Mohammad Asad Rehman Malone, David Univ Toronto Edward S Rogers Sr Dept Elect & Comp Engn Toronto ON M5S 1A1 Canada Soptimizer Toronto ON Canada Natl Univ Ireland Hamilton Inst Maynooth Kildare Ireland

ISBN: (纸本)9781479959273

The rise of the cloud and distributed data-intensive (" Big Data") applications puts pressure on data center networks due to the movement of massive volumes of data. This paper proposes CodHoop a system employing network coding techniques, specifically index coding, as a means of dynamically-controlled reduction in volume of communication. Using Hadoop as a representative of this class of applications, a motivating use-case is presented. The proof-of-concept implementation results exhibit an average advantage of 31% compared to vanilla Hadoop implementation which depending on use-case translates to 31% less energy utilization of the equipment, 31% more jobs that run simultaneously, or to a 31% decrease in job completion time.

关键词： big data VOLUME REDUCTION Completion time energy utilisation jobs large volume data CLOUDS Clouds Communication Research data center Vanilla Network coding

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