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Data-intensive applications, challenges, techniques and technologies: A survey on Big Data

INFORMATION SCIENCES 2014年 275卷 314-347页

作者： Chen, C. L. Philip Zhang, Chun-Yang Univ Macau Fac Sci & Technol Dept Comp & Informat Sci Macau Peoples R China

It is already true that Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. As the speed of information growth exceeds Moore's Law at the beginning of this new century, excessive data is making great troubles to human beings. However, there are so much potential and highly useful values hidden in the huge volume of data. A new scientific paradigm is born as data-intensive scientific discovery (DISD), also known as Big Data problems. A large number of fields and sectors, ranging from economic and business activities to public administration, from national security to scientific researches in many areas, involve with Big Data problems. On the one hand, Big Data is extremely valuable to produce productivity in businesses and evolutionary breakthroughs in scientific disciplines, which give us a lot of opportunities to make great progresses in many fields. There is no doubt that the future competitions in business productivity and technologies will surely converge into the Big Data explorations. On the other hand, Big Data also arises with many challenges, such as difficulties in data capture, data storage, data analysis and data visualization. This paper is aimed to demonstrate a close-up view about Big Data, including Big Data applications, Big Data opportunities and challenges, as well as the state-of-the-art techniques and technologies we currently adopt to deal with the Big Data problems. We also discuss several underlying methodologies to handle the data deluge, for example, granular computing, cloud computing, bio-inspired computing, and quantum computing. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Big Data Data-intensive computing e-Science parallel and distributed computing Cloud computing

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NSF/IEEE-TCPP Curriculum Implementation at the State University of Nizhni Novgorod 28

NSF/IEEE-TCPP Curriculum Implementation at the State Univers...

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28th IEEE International parallel & distributed Processing Symposium Workshops (IPDPSW)

作者： Gergel, Victor Liniov, Alexey Meyerov, Iosif Sysoyev, Alexander State Univ Nizhni Novgorod Fac Computat Math & Cybernet Nizhnii Novgorod Russia

ISBN: (纸本)9781479941162

This work is concerned with the integration of the NSF/IEEE-TCPP Curriculum Initiative on parallel and distributed computing propositions into the curriculum for bachelors in Applied Mathematics and Informatics at the State University of Nizhni Novgorod (UNN). The article compares the NSF/IEEE-TCPP Curriculum with the recommendations developed within the framework of the Russian Supercomputing Education Project. The results of modernization of 18 courses for bachelors in Applied Mathematics and Informatics are also provided. A logical sequence of these courses is presented and coverage of areas of knowledge by the NSF/IEEE-TCPP Curriculum is assessed. Following a pilot implementation the results can be used to increase quality of training in parallel and distributed computing in UNN and other Russian and foreign universities.

关键词： component parallel and distributed computing supercomputing technologies computing curricula NSF/IEEE-TCPP Curriculum education

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Scalable Bootstrap Clustering for Massive Data 15

Scalable Bootstrap Clustering for Massive Data

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15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Wang, Haocheng Zhuang, Fuzhen Ao, Xiang He, Qing Shi, Zhongzhi Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9781479956043

The bootstrap provides a simple and powerful means of improving the accuracy of clustering. However, for today's increasingly large datasets, the computation of bootstrap-based quantities can be prohibitively demanding. In this paper we introduce the Bag of Little Bootstraps Clustering (BLBC), a new procedure which utilizes the Bag of Little Bootstraps technique to obtain a robust, computationally efficient means of clustering for massive data. Moreover, BLBC is suited to implementation on modern parallel and distributed computing architectures which are often used to process large datasets. We investigate empirically the performance characteristics of BLBC and compare to the performances of existing methods via experiments on simulated data and real data. The results show that BLBC has a significantly more favorable computational profile than the bootstrap based clustering while maintaining good statistical correctness.

关键词： data mining machine learning bag of little bootstraps clustering parallel and distributed computing

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Coupling and Simulation of Fluid-Structure Interaction Problems for Automotive Sun-roof on Graphics Processing Unit 16

Coupling and Simulation of Fluid-Structure Interaction Probl...

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16th IEEE Int Conf on High Performance computing and Communications/11th IEEE Int Conf on Embedded Software and Systems\6th Int Symposium on Cyberspace Safety and Security

作者： Lai, Liang S. Lai, Choi-Hong Ahamed, Abal-Kassim Cheik Magoules, Frederic Univ Greenwich Sch Comp & Math Sci London SE18 6PF England Ecole Cent Paris Paris France

ISBN: (纸本)9781479961238

In this paper, the authors propose an analysis of the frequency response function in a car compartment, subject to some fluctuating pressure distribution along the open cavity of the sun-roof at the top of a car. Coupling of a computational fluid dynamics and of a computational acoustics code is considered to simulate the acoustic fluid-structure interaction problem. Iterative Krylov methods and domain decomposition methods, tuned on Graphic Processing Unit (GPU), are considered to solve the acoustic problem with complex number arithmetics with double precision. Numerical simulations illustrate the efficiency, robustness and accuracy of the proposed approaches.

关键词： parallel and distributed computing GPU Krylov method domain decomposition method computational fluid dynamics acoustics

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Connectivity results of hierarchical cubic networks as associated with linearly many faults 17

Connectivity results of hierarchical cubic networks as assoc...

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IEEE 17th International Conference on Computational Science and Engineering (CSE)

作者： Cheng, Eddie Qiu, Ke Shen, Zhizhang Oakland Univ Dept Math & Stat Rochester MI 48309 USA Brock Univ Dept Comp Sci St Catharines ON L2S 3A1 Canada Plymouth State Univ Dept Comp Sci & Technol Plymouth NH 03264 USA

ISBN: (纸本)9781479979813

We establish a general fault-tolerance property for the interesting hierarchical cubic networks, when a linear number of vertices are removed from such a network. As its application, we discuss and derive several connectivity results of its underlying graph, including its restricted connectivity, cyclic vertex-connectivity, component connectivity, and conditional diagnosability. These results demonstrate several fault-tolerance properties of the hierarchical cubic networks.

关键词： Hierarchical cubic network graph connectivity fault-tolerance property parallel and distributed computing

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parallel Sub-Structuring Methods for solving Sparse Linear Systems on a cluster of GPU 16

Parallel Sub-Structuring Methods for solving Sparse Linear S...

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16th IEEE Int Conf on High Performance computing and Communications/11th IEEE Int Conf on Embedded Software and Systems\6th Int Symposium on Cyberspace Safety and Security

作者： Ahamed, Abal-Kassim Cheik Magoules, Frederic Ecole Cent Paris CUDA Res Ctr Paris France

ISBN: (纸本)9781479961238

The main objective of this work consists in analyzing sub-structuring method for the parallel solution of sparse linear systems with matrices arising from the discretization of partial differential equations such as finite element, finite volume and finite difference. With the success encountered by the general-purpose processing on graphics processing units (GPGPU), we develop an hybrid multiGPUs and CPUs sub-structuring algorithm. GPU computing, with CUDA, is used to accelerate the operations performed on each processor. Numerical experiments have been performed on a set of matrices arising from engineering problems. We compare C+MPI implementation on classical CPU cluster with C+MPI+CUDA on a cluster of GPU. The performance comparison shows a speed-up for the sub-structuring method up to 19 times in double precision by using CUDA.

关键词： Sub-structuring method Linear algebra Conjugate Gradient parallel and distributed computing Graphics Processing Unit GPU computing CUDA Finite element

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String Sorting on Multi and Many-threaded Architectures: A Comparative Study

String Sorting on Multi and Many-threaded Architectures: A C...

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International Conference on High Performance computing and Applications (ICHPCA)

作者： Neelima, B. Narayan, Aniian S. Prabhu, Rithesh G. NMAM Inst Technol Dept Comp Sci & Engn Udupi India

ISBN: (纸本)9781479959587

The increase in the amount of data is evident in recent times. The amount of data stored and retrieved is increasing at a fast rate. Processing text data consumes large amount of memory in terms of storage and extraction. Sorting the stored data is one of the most favorable methods that can be used in order to increase the efficiency of extracting stored data. Graphic Processing Units (GPUs) have evolved from being used as dedicated graphic rendering modules to being used to exploit fast parallelism for large computational purposes. The use of GPUs for sorting strings large in size has produced effective and fast results when compared to using CPUs. This paper produces a comparative study on the most popular and efficient string sorting algorithms that have been implemented on CPU and GPU machines. This paper also proposes an efficient parallel multi-key quicksort implementation which uses ternary search tree in order to increase the speed up and efficiency of sorting large set of string data.

关键词： Hybrid machines Graphic processing units String sorting parallel and distributed computing parallel string sorting

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Beam-tracing domain decomposition method for urban acoustic pollution 13

Beam-tracing domain decomposition method for urban acoustic ...

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13th International Symposium on distributed computing and Applications to Business, Engineering and Science (DCABES)

作者： Gbikpi-Benissan, Guillaume Magoules, Frederic Ecole Cent Paris Chatenay Malabry France

ISBN: (纸本)9781479941698

This paper covers the fast solution of large acoustic problems on low-resources parallel platforms. A domain decomposition method is coupled with a dynamic load balancing scheme to efficiently accelerate a geometrical acoustic method. The geometrical method studied implements a beam-tracing method where intersections are handled as in a ray-tracing method. Beyond the distribution of the global processing upon multiple sub-domains, a second parallelization level is operated by means of multi-threading and shared memory mechanisms. Numerical experiments show that this method allows to handle large scale open domains for parallel computing purposes on few machines. Urban acoustic pollution arrising from car traffic was simulated on a large model of the Shinjuku district of Tokyo, Japan. The good speed-up results illustrate the performance of this new domain decomposition method.

关键词： Domain decomposition methods parallel and distributed computing Acoustics Ray-tracing methods Beam-tracing methods

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Benchmarking Different MapReduce Implementations for Computer-Aided Hardware Development

Benchmarking Different MapReduce Implementations for Compute...

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International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)

作者： Schoemig, Milan Neuhaeuser, David Seidler, Ralf Buecker, H. Martin Univ Jena Dept Comp Sci & Math D-07737 Jena Germany

ISBN: (纸本)9781479943241

In the design of fast arithmetic circuits, the two's complement number representation can be alternatively replaced by a signed digit number representation. Compared to standard full adders used in two's complement arithmetic, signed digit adder cells offer the potential for improved performance. Designing an efficient signed digit adder cell leads to the problem of analyzing 2 to the power of 44 truth tables originating from different signed digit encodings. Since different digit encodings can produce identical truth tables, it is favorable to reduce this large number of truth tables by identifying identical ones. We introduce a novel approach for the solution of this problem using the MapReduce programming model. We take a step towards solving this problem using three different implementations of MapReduce (Hadoop, Disco, and MR-MPI) and compare their performance on an Opteron-based cluster using up to 64 physical cores.

关键词： MapReduce Hadoop Disco MR-MPI Big Data parallel and distributed computing Signed Digit

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Beam-tracing domain decomposition method for urban acoustic pollution

Beam-tracing domain decomposition method for urban acoustic ...

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13th International Symposium on distributed computing and Applications to Business,Engineering & Science（DCABES 2014）

作者： Guillaume Gbikpi-Benissan Frdric Magoulès Ecole Centrale Paris

This paper covers the fast solution of large acoustic problems on low-resources parallel platforms. A domain decomposition method is coupled with a dynamic load balancing scheme to efficiently accelerate a geometrical acoustic method. The geometrical method studied implements a beam-tracing method where intersections are handled as in a ray-tracing method. Beyond the distribution of the global processing upon multiple sub-domains, a second parallelization level is operated by means of multi-threading and shared memory *** experiments show that this method allows to handle large scale open domains for parallel computing purposes on few machines. Urban acoustic pollution arrising from car traffic was simulated on a large model of the Shinjuku district of Tokyo, Japan. The good speed-up results illustrate the performance of this new domain decomposition method.

关键词： Domain decomposition methods parallel and distributed computing Acoustics Ray-tracing methods Beam-tracing methods

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