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A Novel Weighted Dynamic Time Warping for Light Weight Speaker-Dependent Speech Recognition in Noisy and Bad Recording Conditions

A Novel Weighted Dynamic Time Warping for Light Weight Speak...

引用

2nd international Conference on Mechanical Design and Power Engineering (ICMDPE 2013)

作者： Zhang, Xianglilan Sun, Jiping Huang, Xuhui Luo, Zhigang Natl Univ Def Technol Sch Comp Sci Natl Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China Univ Waterloo David R Cheriton Sch Comp Sci Waterloo N2L 3G1 ON Canada Natl Univ Def Technol Sch Comp Sci Natl Lab parallel & distributed Proc Changsha 410073 Peoples R China

ISBN: (纸本)9783038350019

Lightweight speaker-dependent (SD) automatic speech recognition (ASR) is a promising solution for the problems of possibility of disclosing personal privacy and difficulty of obtaining training material for many seldom used English words and (often non-English) names. Dynamic time warping (DTW) algorithm is the state-of-the-art algorithm for small foot-print SD ASR applications, which have limited storage space and small vocabulary. In our previous work, we have successfully developed two fast and accurate DTW variations for clean speech data. However, speech recognition in adverse conditions is still a big challenge. In order to improve recognition accuracy in noisy and bad recording conditions, such as too high or low recording volume, we introduce a novel weighted DTW method. This method defines a feature index for each time frame of training data, and then applies it to the core DTW process to tune the final alignment score. With extensive experiments on one representative SD dataset of three speakers' recordings, our method achieves better accuracy than DTW, where 0.5% relative reduction of error rate (RRER) on clean speech data and 7.5% RRER on noisy and bad recording speech data. To the best of our knowledge, our new weighted DTW is the first weighted DTW method specially designed for speech data in noisy and bad recording conditions.

关键词： Computing Methodologies Weighted DTW Natural Language processing Speech Recognition and Feature Index

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An Efficient Algorithm for Solving Eigenproblem

An Efficient Algorithm for Solving Eigenproblem

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The 13th international symposium on distributed Computing and applications to Business,Engineering and Science(DCABES 2014)(第十三届分布式计算及其应用国际学术研讨会)

作者： Huirong Zhang Jianwen Cao Laboratory of Parallel Software and Computational Science of Software Institute of Software Chinese Laboratory of Parallel Software and Computational Science of Software Institute of Software Chinese

ISBN: (纸本)9781479941681

In this paper,we consider second order elliptic ODE eigenproblems on general *** construct an efficient algorithm for computing the eigenvalue by using weighted mean combination of the linear finite element method and corresponding 2nd-order finite difference *** first take the arithmetic mean of the two *** we compute the quasi-optimal combined parameters for different eigenvalues to improve our efficient *** algorithm we construct convergence faster and have higher accuracy than the linear finite element method and corresponding 2nd-order finite difference *** numerical examples tested on both uniform meshes and nonuniform meshes are given to illustrate the computational cost of different numerical methods for solving eigenvalue *** efficiency,all the matrices use sparse storage in our algorithm.

关键词： Keywords-Efficient algorithm combinatorial quasioptimal eigenproblem

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RACB: Resource aware cache bypass on GPUs 26

RACB: Resource aware cache bypass on GPUs

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26th IEEE international symposium on Computer Architecture and High Performance Computing Workshops, SBAC-PADW 2014

作者： Dai, Hongwen Kartsaklis, Christos Li, Chao Janjusic, Tomislav Zhou, Huiyang Department of Electrical and Computer Engineering North Carolina State University Raleigh United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge United States

ISBN: (纸本)9781479970148

Caches are universally used in computing systems to hide long off-chip memory access latencies. Unlike CPUs, massive threads running simultaneously on GPUs bring a tremendous pressure on memory hierarchy. As a result, the limitation of cache resources becomes a bottleneck for a GPU to exploit thread-level parallelism (TLP) and memory-level parallelism (MLP) and achieve high performance. In this paper, we propose a mechanism to bypass L1D and L2 cache based on the availability of cache resources. Our proposed mechanism is based on the observation that a huge number of stalls coming from limited cache resources prohibit GPUs from providing a higher throughput. So we propose Resource Aware Cache Bypass (RACB) with minor hardware changes to eliminate such stalls to improve performance. We examine the effectiveness of this approach when applied to L1D and L2 cache separately as well as together. Evaluation results with NVIDIA Computing SDK show that RACB generally improves performance the most when applied to both L1D and L2 cache, which is up to 88.05% and on an average of 16.73%;additionally, energy is saved up to 22.35% and on an average of 5.88% with minor hardware overheads. © 2014 IEEE.

关键词： Graphics processing unit

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Efficient pseudorecursive evaluation schemes for non-adaptive sparse grids 1

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2nd Workshop on Sparse Grids and applications, SGA 2012

作者： Buse, Gerrit Pflüger, Dirk Jacob, Riko TU München München Germany Institute for Parallel and Distributed Systems Universität Stuttgart Stuttgart Germany ETH Zurich Zurich Switzerland

ISBN: (数字)9783319045375

ISBN: (纸本)9783319045368

In this work we propose novel algorithms for storing and evaluating sparse grid functions, operating on regular (not spatially adaptive), yet potentially dimensionally adaptive grid types. Besides regular sparse grids our approach includes truncated grids, both with and without boundary grid points. Similar to the implicit data structures proposed in Feuersänger (Dünngitterverfahren für hochdimensionale elliptische partielle Differntialgleichungen. Diploma Thesis, Institut für Numerische Simulation, Universität Bonn, 2005) and Murarasu et al. (Proceedings of the 16th ACM symposium on Principles and Practice of parallel Programming. Cambridge University Press, New York, 2011, pp. 25–34) we also define a bijective mapping from the multi-dimensional space of grid points to a contiguous index, such that the grid data can be stored in a simple array without overhead. Our approach is especially well-suited to exploit all levels of current commodity hardware, including cache-levels and vector extensions. Furthermore, this kind of data structure is extremely attractive for today’s real-time applications, as it gives direct access to the hierarchical structure of the grids, while outperforming other common sparse grid structures (hash maps, etc.) which do not match with modern compute platforms that well. For dimensionality d ≤10 we achieve good speedups on a 12 core Intel Westmere-EP NUMA platform compared to the results presented in Murarasu et al. (Proceedings of the international Conference on Computational Science—ICCS 2012. Procedia Computer Science, 2012). As we show, this also holds for the results obtained on Nvidia Fermi GPUs, for which we observe speedups over our own CPU implementation of up to 4.5 when dealing with moderate dimensionality. In high-dimensional settings, in the order of tens to hundreds of dimensions, our sparse grid evaluation kernels on the CPU outperform any other known implementation. © Springer international Publishing Switzerland 2014.

关键词： parallel programming

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HPC applications Deployment on distributed Heterogeneous Computing Platforms via OMF, OML and P2PDC

HPC Applications Deployment on Distributed Heterogeneous Com...

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Euromicro Conference on parallel, distributed and Network-Based processing

作者： Didier El Baz The Tung Nguyen Guillaume Jourjon Thierry Rakotoarivelo Universite de Toulouse Toulouse France NICTA Eveleigh NSW Australia

A new tool and web portal are presented for deployment of High Performance Computing applications on distributed heterogeneous computing platforms. This tool relies on the decentralized environment P2PDC and the OMF and OML multithreaded control, instrumentation and measurement libraries. Deployment on PlanetLab of a numerical simulation application is studied. A first series of computational results is displayed and analyzed.

关键词： Portals Peer-to-peer computing Servers Extraterrestrial measurements Computer architecture Volume measurement Libraries

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ABC2: Adaptively Balancing Computation and Communication in a DSM Cluster of Multicores for Irregular applications

ABC2: Adaptively Balancing Computation and Communication in ...

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IEEE international symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Sai Charan Koduru Keval Vora Rajiv Gupta Department of Computer Science and Engineering University of California Riverside

Graph-based applications have become increasingly important in many application domains. The large graph sizes offer data level parallelism at a scale that makes it attractive to run such applications on distributed shared memory (DSM) based modern clusters composed of multicore machines. Our analysis of several graph applications that rely on speculative parallelism or asynchronous parallelism shows that the balance between computation and communication differs between applications. In this paper, we study this balance in the context of DSMs and exploit the multiple cores present in modern multicore machines by creating three kinds of threads which allows us to dynamically balance computation and communication: compute threads to exploit data level parallelism in the computation, fetch threads that replicate data into object-stores before it is accessed by compute threads, and update threads that make results computed by compute threads visible to all compute threads by writing them to DSM. We observe that the best configuration for above mechanisms varies across different inputs in addition to the variation across different applications. To this end, we design ABC2: a runtime algorithm that automatically configures the DSM using simple runtime information such as: observed object prefetch and update queue lengths. This runtime algorithm achieves speedups close to that of the best hand-optimized configurations.

关键词： Prefetching parallel processing Runtime Multicore processing Adaptation models Computational modeling

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OpenCL Application Auto-tuning and Run-Time Resource Management for Multi-core Platforms

OpenCL Application Auto-tuning and Run-Time Resource Managem...

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international symposium on parallel and distributed processing with applications, ISPA

作者： Davide Gadioli Simone Libutti Giuseppe Massari Edoardo Paone Michele Scandale Patrick Bellasi Gianluca Palermo Vittorio Zaccaria Giovanni Agosta William Fornaciari Cristina Silvano Politecnico di Milano Milano Lombardia IT Politecnico di Milano - Dipartimento di Elettronica Informazione e Bioingegneria

To support adaptivity of data parallel applications on multi-core platforms, we propose a framework based on the combination of OpenCL application auto-tuning and run-time resource management. The framework addresses computationally intensive multimedia OpenCL applications. For these target applications, we show that application auto-tuning, based on design-time analysis, can become synergistic with run-time resource management. In the proposed framework, run-time decisions are taken by each application, autonomously, to achieve system adaptivity. This paper describes the methodology and related toolchain, defined during the 2PARMA European project, based on the integration of independent tools to provide effective compilation of OpenCL code, multi-objective design space exploration, application monitoring and tuning and system-wide run-time resource management. Experimental results are reported for design optimization of an OpenCL stereo-matching application and then for a resource contention scenario where multiple stereo-matching applications are executed on the same platform with different run-time requirements.

关键词： Optimization Runtime Resource management Space exploration Throughput Monitoring parallel processing

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MobiStreams: A Reliable distributed Stream processing System for Mobile Devices

MobiStreams: A Reliable Distributed Stream Processing System...

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international symposium on parallel and distributed processing (IPDPS)

作者： Huayong Wang Li-Shiuan Peh

Multi-core phones are now pervasive. Yet, existing applications rely predominantly on a client-server computing paradigm, using phones only as thin clients, sending sensed information via the cellular network to servers for processing. This makes the cellular network the bottleneck, limiting overall application performance. In this paper, we propose Mobi Streams, a distributed Stream processing System (DSPS) that runs directly on smartphones. Mobi Streams can offload computing from remote servers to local phones and thus alleviate the pressure on the cellular network. Implementing DSPS on smartphones faces significant challenges: 1) multiple phones can readily fail simultaneously, and 2) the phones' ad-hoc WiFi network has low bandwidth. Mobi Streams tackles these challenges through two new techniques: 1) token-triggered check pointing, and 2) broadcast-based check pointing. Our evaluations driven by two real world applications deployed in the US and Singapore show that migrating from a server platform to a smartphone platform eliminates the cellular network bottleneck, leading to 0.78~42.6X throughput increase and 10%~94.8% latency decrease. Also, Mobi Streams' fault tolerance scheme increases throughput by 230% and reduces latency by 40% vs. prior state-of-the-art fault-tolerant DSPSs.

关键词： Smart phones Digital signal processing Checkpointing Servers IEEE 802.11 Standards Fault tolerance Fault tolerant systems

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Classification with probability density estimation on sparse grids 1

引用

2nd Workshop on Sparse Grids and applications, SGA 2012

作者： Peherstorfer, Benjamin Franzelin, Fabian Pflüger, Dirk Bungartz, Hans-Joachim Department of Informatics Technische Universität München Boltzmannstr. 3 Garching85748 Germany Institute for Parallel and Distributed Systems University of Stuttgart Universitätsstr. 38 Stuttgart70569 Germany

ISBN: (数字)9783319045375

ISBN: (纸本)9783319045368

We present a novel method to tackle the multi-class classification problem with sparse grids and show how the computational procedure can be split into an Offline phase (pre-processing) and a very rapid Online phase. For each class of the training data the underlying probability density function is estimated on a sparse grid. The class of a new data point is determined by the values of the density functions at this point. Our classification method can deal with more than two classes in a natural way and it provides a stochastically motivated confidence value which indicates how to rate the respond to a new point. Furthermore, the underlying density estimation method allows us to pre-compute the system matrix and store it in an appropriate format. This so-called Offline/Online splitting of the computational procedure allows an Online phase where only a few matrix vector products are necessary to learn a new, previously unseen training data set. In particular, we do not have to solve a system of linear equations anymore. We show that speed ups by a factor of several hundred are possible. A typical application for such an Offline/Online splitting is cross validation. We present the algorithm and the computational procedure for our classification method, report on the employed density estimation method on sparse grids and show by means of artificial and real world data sets that we obtain competitive results compared to the classical sparse grid classification method based on regression. © Springer international Publishing Switzerland 2014.

关键词： Probability density function

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CyGraph: A Reconfigurable Architecture for parallel Breadth-First Search

CyGraph: A Reconfigurable Architecture for Parallel Breadth-...

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IEEE international symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Osama G. Attia Tyler Johnson Kevin Townsend Philip Jones Joseph Zambreno Department Electrical and Computer Engineering Iowa State University Ames IA USA

ISBN: (纸本)9781479941155

Large-scale graph structures are considered as a keystone for many emerging high-performance computing applications in which Breadth-First Search (BFS) is an important building block. For such graph structures, BFS operations tends to be memory-bound rather than compute-bound. In this paper, we present an efficient reconfigurable architecture for parallel BFS that adopts new optimizations for utilizing memory bandwidth. Our architecture adopts a custom graph representation based on compressed-sparse raw format (CSR), as well as a restructuring of the conventional BFS algorithm. By taking maximum advantage of available memory bandwidth, our architecture continuously keeps our processing elements active. Using a commercial high-performance reconfigurable computing system (the Convey HC-2), our results demonstrate a 5× speedup over previously published FPGA-based implementations.

关键词： Kernel Optimization Arrays Bandwidth Algorithm design and analysis Indexes

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