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2012 8th International symposium on Chinese Spoken Language processing, ISCSLP 2012

2012 8th International Symposium on Chinese Spoken Language ...

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2012 8th International symposium on Chinese Spoken Language processing, ISCSLP 2012

ISBN: (纸本)9781467325059

the proceedings contain 96 papers. the topics discussed include: alternative hypothesis generation using a weighted kernel feature matrix for ASR substitution error correction;a synchronized pruning composition algorithm of weighted finite state transducers for large vocabulary speech recognition;a comparative study of fMPE and RDLT approaches to LVCSR;analyzing semantic orientation of terms using affinity propagation;effects of excitation spread on the intelligibility of Mandarin speech in cochlear implant simulations;articulatory and spectral characteristics of Cantonese vowels;Incorporating dynamic features into minimum generation error training for HMM-based speech synthesis;voice conversion using Bayesian mixture of probabilistic linear regressions and dynamic kernel features;detection and emphatic realization of contrastive word pairs for expressive text-to-speech synthesis;and phonotactic spoken language recognition: using diversely adapted acoustic models in parallel phone recognizers.

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distributed Multimedia Content Analysis with MapReduce

Distributed Multimedia Content Analysis with MapReduce

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ieee International symposium on Personal, Indoor and Mobile Radio Communications

作者： Arto Heikkinen Jouni Sarvanko Mika Rautiainen Mika Ylianttila Department of Communications Engineering University of Oulu Finland Center for Internet Excellence University of Oulu Finland Department of Computer Science and Engineering University of Oulu Finland

ISBN: (纸本)9781467362337

this paper introduces a scalable solution for distributing content-based video analysis tasks using the emerging MapReduce programming model. Scalable and efficient solutions are needed for this type of tasks, as the number of multimedia content is growing at an increasing rate. We present a novel implementation utilizing the popular Apache Hadoop MapReduce framework for both analysis job scheduling and video data distribution. We employ face detection as a case example because it represents a popular visual content analysis task. the main contribution of this paper is the performance evaluation of distribution models for video content processing in various configurations. In our experiments, we have compared the performance of our video data distribution method against two alternatives solutions on a seven node cluster. Hadoop's performance overhead in video content analysis was also evaluated. We found Hadoop to be a data efficient solution with minimal computational overhead for the face detection task.

关键词： MapReduce distributed video analysis Face detection parallel computing

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DCOSS 2012 Foreword

DCOSS 2012 Foreword

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8th ieee International Conference on distributed Computing in Sensor Systems, DCOSS 2012

作者： Lu, Dongming Xu, Wenyuan Wang, Zhi Rabbat, Michael Zhejiang University China University of South Carolina United States McGill University Canada

ISBN: (纸本)9780769547077

the 8th ieee International Conference on distributed Computing in Sensor Systems (DCOSS 2012) is taking place in Hangzhou, China, from Wednesday, May 16, to Friday, May 18, 2012. Previous editions have taken place in Barcelona, Spain (2011), Santa Barbara, USA (2010), Los Angeles, USA (2009), Santorini Island, Greece (2008), Santa Fe, USA (2007), San Francisco, USA (2006), and Marina del Rey, USA (2005). We are pleased to present the conference program to you. this year, the DCOSS program features high-quality research presentations, two keynotes, and a poster and work-inprogress session. the conference program covers several aspects of distributed computing in sensor systems aligned with the three main tracks: algorithms and analysis, signal processing and information theory, and systems and applications. this year we received 100 submissions. Each submitted paper was reviewed by at least three Technical Program Committee experts, and ultimately a total of 34 papers were accepted. We will also feature three interesting workshops and one poster/demonstration/ work-in-progress session. We are proud to feature two excellent keynotes from leading experts on issues currently driving the distributed computing and sensor systems community. We hope that the technical program will provide a stimulating forum for researchers and practitioners throughout all three days. © 2012 ieee.

关键词： distributed computer systems

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Hierarchical and distributed implementation of synchronization and coordination for discrete event multiple robot systems

Hierarchical and distributed implementation of synchronizati...

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ieee/ASME International Conference on Mechtronic and Embedded Systems and Applications, MESA

作者： Gen'ichi Yasuda Department of Human and Computer Intelligence Nagasaki Institute of Applied Science Nagasaki Japan

Since in the large and complex robotic systems such as multiple robot systems, the real robot controllers are spatially distributed according to their physical structure, it is desirable to realize the hierarchical and distributed control with a suitable parallel processing architecture. Hierarchical Petri net modeling is seemingly well suited for structured and predictable environments such as robotic manufacturing systems. the paper presents a discrete event net based distributed control architecture for multiple robot coordination. According to the parallelism among the robotic tasks in the system, the advantage of the parallel and distributed architecture of the control system will be taken to reach the high performance control capabilities.

关键词： Robot kinematics Firing Machining System recovery Loading Computer architecture

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parallel Local Search for the Costas Array Problem

Parallel Local Search for the Costas Array Problem

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ieee International symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Daniel Diaz Florian Richoux Yves Caniou Philippe Codognet Salvador Abreu Université de Paris 1-Sorbonne France JFLI CNRS/ UPMC University of Tokyo Japan JFLI CNRS / NII Japan Universidade de Évora and CENTRIA FCT/UNL Portugal

ISBN: (纸本)9781467309745

the Costas Array Problem is a highly combinatorial problem linked to radar applications. We present in this paper its detailed modeling and solving by Adaptive Search, a constraint-based local search method. Experiments have been done on both sequential and parallel hardware up to several hundreds of cores. Performance evaluation of the sequential version shows results outperforming previous implementations, while the parallel version shows nearly linear speedups up to 8,192 cores.

关键词： Arrays Search problems Program processors Adaptation models Benchmark testing Supercomputers

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Comparison between parallel and distributed molecular dynamics simulations of Lennard-Jones systems

Comparison between parallel and distributed molecular dynami...

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ieee International Conference on Intelligent Computer Communication and processing (ICCP)

作者： Vlad Baja Dorian Gorgan Titus Beu Computer Science Department Technical University of Cluj Napoca Cluj-Napoca Romania Faculty of Physics University Babes-Bolyai Cluj-Napoca Romania

this paper concerns mainly with parallel and distributed implementations of molecular dynamics simulations of the Lennard-Jones potential model. the reported research work studies and experiments different algorithms and parallelization techniques for shared memory and message passing architectures, and the programs are executed on single-core processors, multi-core processors, GPU, and GPU cluster. the solution based on efficient versions of the neighbor list algorithm and space division technique is further discussed. the obtained speedups for multi-core processor, GPU, and GPU cluster, relative to the single-core processor implementation of the program, are analyzed, and the advantages of the algorithms are highlighted.

关键词： Computational modeling Graphics processing units Multicore processing Computers Arrays Force Message systems

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An Approach to parallelize Kruskal's Algorithm Using Helper threads

An Approach to Parallelize Kruskal's Algorithm Using Helper ...

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ieee International symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Anastasios Katsigiannis Nikos Anastopoulos Konstantinos Nikas Nectarios Koziris School of Electrical and Computer Engineering Computing Systems Laboratory National and Technical University of Athens Greece

ISBN: (纸本)9781467309745

In this paper we present a Helper threading scheme used to parallelize efficiently Kruskal's Minimum Spanning Forest algorithm. this algorithm is known for exhibiting inherently sequential characteristics. More specifically, the strict order by which the algorithm checks the edges of a given graph is the main reason behind the lack of explicit parallelism. Our proposed scheme attempts to overcome the imposed restrictions and improve the performance of the algorithm. the results show that for a wide range of graphs of varying structure, size and density the parallelization of Kruskal's algorithm is feasible. Observed speedups reach up to 5.5 for 8 running threads, revealing the potentials of our approach.

关键词： Partitioning algorithms Arrays parallel processing Synchronization Instruction sets Educational institutions Multicore processing

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PARDA: A Fast parallel Reuse Distance Analysis Algorithm

PARDA: A Fast Parallel Reuse Distance Analysis Algorithm

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International symposium on parallel and distributed processing (IPDPS)

作者： Qingpeng Niu James Dinan Qingda Lu P. Sadayappan Ohio State University USA Argonne National Laboratory USA Intel Corporation USA

ISBN: (纸本)9781467309752

Reuse distance is a well established approach to characterizing data cache locality based on the stack histogram model. this analysis so far has been restricted to offline use due to the high cost, often several orders of magnitude larger than the execution time of the analyzed code. this paper presents the first parallel algorithm to compute accurate reuse distances by analysis of memory address traces. the algorithm uses a tunable parameter that enables faster analysis when the maximum needed reuse distance is limited by a cache size upper bound. Experimental evaluation using the SPEC CPU 2006 benchmark suite shows that, using 64 processors and a cache bound of 8 MB, it is possible to perform reuse distance analysis with full accuracy within a factor of 13 to 50 times the original execution times of the benchmarks.

关键词： Algorithm design and analysis Program processors Histograms Optimization parallel algorithms Arrays Analytical models

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Improving the Performance of Dynamical Simulations Via Multiple Right-Hand Sides

Improving the Performance of Dynamical Simulations Via Multi...

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International symposium on parallel and distributed processing (IPDPS)

作者： Xing Liu Edmond Chow Karthikeyan Vaidyanathan Mikhail Smelyanskiy School of Computational Science and Engineering College of Computing Georgia Institute of Technology Atlanta GA USA Parallel Computing Laboratory Intel Corporation Santa Clara CA USA

this paper presents an algorithmic approach for improving the performance of many types of stochastic dynamical simulations. the approach is to redesign existing algorithms that use sparse matrix-vector products (SPMV) with single vectors to instead use a more efficient kernel, the generalized SPMV (GSPMV), which computes with multiple vectors simultaneously. In this paper, we show how to redesign a dynamical simulation to exploit GSPMV in way that is not initially obvious because only one vector is available at a time. We study the performance of GSPMV as a function of the number of vectors, and demonstrate the use of GSPMV in the Stokesian dynamics method for the simulation of the motion of macromolecules in the cell. Specifically, for our application, we find that with modern multicore Intel microprocessors in clusters of up to 64 nodes, we can typically multiply by 8 to 16 vectors in only twice the time required to multiply by a single vector. After redesigning the Stokesian dynamics algorithm to exploit GSPMV, we measure a 30 percent speedup in performance in single-node, data parallel simulations.

关键词： Vectors Sparse matrices Heuristic algorithms Computational modeling Mathematical model Equations Kernel

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Low-Cost parallel Algorithms for 2:1 Octree Balance

Low-Cost Parallel Algorithms for 2:1 Octree Balance

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International symposium on parallel and distributed processing (IPDPS)

作者： Tobin Isaac Carsten Burstedde Omar Ghattas Institute for Computational Engineering and Sciences (ICES) University of Texas Austin USA Institut für Numerische Simulation (INS) Rheinische Friedrich-Wilhelms-Universität Germany Institute for Computational Engineering and Sciences (ICES) Jackson School of Geosciences Department of Mechanical Engineering University of Texas Austin USA

the logical structure of a forest of octrees can be used to create scalable algorithms for parallel adaptive mesh refinement (AMR), which has recently been demonstrated for several petascale applications. Among various frequently used octree-based mesh operations, including refinement, coarsening, partitioning, and enumerating nodes, ensuring a 2:1 size balance between neighboring elements has historically been the most expensive in terms of CPU time and communication volume. the 2:1 balance operation is thus a primary target to optimize. One important component of a parallel balance algorithm is the ability to determine whether any two given octants have a consistent distance/size relation. Based on new logical concepts we propose fast algorithms for making this decision for all types of 2:1 balance conditions in 2D and 3D. Since we are able to achieve this without constructing any parent nodes in the tree that would otherwise need to be sorted and communicated, we can significantly reduce the required memory and communication volume. In addition, we propose a lightweight collective algorithm for reversing the asymmetric communication pattern induced by non-local octant interactions. We have implemented our improvements as part of the opensource “p4est” software. Benchmarking this code with both synthetic and simulation-driven adapted meshes we are able to demonstrate much reduced runtime and excellent weak and strong scalability. On our largest benchmark problem with 5.13 × 10 11 octants the new 2:1 balance algorithm executes in less than 8 seconds on 112,128 CPU cores of the Jaguar Cray XT5 supercomputer.

关键词： Octrees Partitioning algorithms Arrays Vegetation Insulation Educational institutions USA Councils

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