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Fast estimation of gaussian mixture model parameters on GPU using CUDA

Fast estimation of gaussian mixture model parameters on GPU ...

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2011 12th International conference on parallel and distributed Computing, Applications and Technologies, PDCAT 2011

作者： Machlica, Lukáš Vaněk, Jan Zajíc, Zbyněk Department of Cybernetics University of West Bohemia Pilsen Czech Republic

ISBN: (纸本)9780769545646

Gaussian Mixture Models (GMMs) are widely used among scientists e.g. in statistic toolkits and data mining procedures. In order to estimate parameters of a GMM the Maximum Likelihood (ML) training is often utilized, more precisely the Expectation-Maximization (EM) algorithm. Nowadays, a lot of tasks works with huge datasets, what makes the estimation process time consuming (mainly for complex mixture models containing hundreds of components). The paper presents an efficient and robust implementation of the estimation of GMM statistics used in the EM algorithm on GPU using NVIDIA's Compute Unified Device Architecture (CUDA). Also an augmentation of the standard CPU version is proposed utilizing SSE instructions. Time consumptions of presented methods are tested on a large dataset of real speech data from the NIST Speaker Recognition Evaluation (SRE) 2008. Estimation on GPU proves to be more than 400 times faster than the standard CPU version and 130 times faster than the SSE version, thus a huge speed up was achieved without any approximations made in the estimation formulas. Proposed implementation was also compared to other implementations developed by other departments over the world and proved to be the fastest (at least 5 times faster than the best implementation published recently). © 2011 IEEE.

关键词： Graphics processing unit

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Advances in Computer Science, Environment, Ecoinformatics, and Education - International conference, CSEE 2011, Proceedings

Advances in Computer Science, Environment, Ecoinformatics, a...

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International conference on Advances in Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011

ISBN: (纸本)9783642233562

The proceedings contain 525 papers. The topics discussed include: convergence of the stochastic age-structured population system with diffusion;parallel computer processing systems are better than serial computer processing systems;the traits of dual multiple ternary fuzzy frames of translates with ternary scaling functions;the implementation of NPKI system based LDAP;research on backstepping integral control of two order nonlinear systems with input nonlinearity;research on high order sliding mode control of three order systems with input nonlinearity;research on teaching methods of motor drive technology based on information technology;on relativity of probability and information;pattern synthesis of antennas based on particle swarm optimization algorithm;critical condition for parametric resonance of axially mass-loaded string;research on medieval english literature teaching based on data analysis;and research of the distributed heterogeneous database conversion mechanism.

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Experimental results on multiple pattern matching algorithms for biological sequences

Experimental results on multiple pattern matching algorithms...

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作者： Kouzinopoulos, Charalampos S. Michailidis, Panagiotis D. Margaritis, Konstantinos G. Parallel and Distributed Processing Laboratory Department of Applied Informatics University of Macedonia 156 Egnatia str. 54006 Thessaloniki Greece

ISBN: (纸本)9789898425362

With the remarkable increase in the number of DNA and proteins sequences, it is very important to study the performance of multiple pattern matching algorithms when querying sequence patterns in biological sequence databases. In this paper, we present a performance study of the running time of well known multiple pattern matching algorithms on widely used biological sequence databases containing the building blocks of nucleotides (in the case of nucleic acid sequence databases) and amino acids (in the case of protein sequence databases).

关键词： Proteins

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Scheduling in MapReduce-like Systems for Fast Completion Time

Scheduling in MapReduce-like Systems for Fast Completion Tim...

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IEEE INFOCOM conference

作者： Chang, Hyunseok Kodialam, Murali Kompella, Ramana Rao Lakshman, T. V. Lee, Myungjin Mukherjee, Sarit Bell Labs Alcatel Lucent Murray Hill NJ 07974 USA Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9781424499212

Large-scale data processing needs of enterprises today are primarily met with distributed and parallel computing in data centers. MapReduce has emerged as an important programming model for these environments. Since today's data centers run many MapReduce jobs in parallel, it is important to find a good scheduling algorithm that can optimize the completion times of these jobs. While several recent papers focused on optimizing the scheduler, there exists very little theoretical understanding of the scheduling problem in the context of MapReduce. In this paper, we seek to address this problem by first presenting a simplified abstraction of the MapReduce scheduling problem, and then formulate the scheduling problem as an optimization problem. We devise various online and offline algorithms to arrive at a good ordering of jobs to minimize the overall job completion times. Since optimal solutions are hard to compute (NP-hard), we propose approximation algorithms that work within a factor of 3 of the optimal. Using simulations, we also compare our online algorithm with standard scheduling strategies such as FIFO, Shortest Job First and show that our algorithm consistently outperforms these across different job distributions.

关键词： Approximation algorithms Approximation methods Equations Optimal scheduling Optimized production technology Processor scheduling Program processors

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Advances in Computer Science, Environment, Ecoinformatics, and Education - International conference, CSEE 2011, Proceedings

Advances in Computer Science, Environment, Ecoinformatics, a...

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International conference on Advances in Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011

ISBN: (纸本)9783642233234

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Advances in Computer Science, Environment, Ecoinformatics, and Education - International conference, CSEE 2011, Proceedings

Advances in Computer Science, Environment, Ecoinformatics, a...

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International conference on Advances in Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011

ISBN: (纸本)9783642233449

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Advances in Computer Science, Environment, Ecoinformatics, and Education - International conference, CSEE 2011, Proceedings

Advances in Computer Science, Environment, Ecoinformatics, a...

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International conference on Advances in Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011

ISBN: (纸本)9783642233203

The proceedings contain 525 papers. The topics discussed include: convergence of the stochastic age-structured population system with diffusion;parallel computer processing systems are better than serial computer processing systems;the traits of dual multiple ternary fuzzy frames of translates with ternary scaling functions;the implementation of NPKI system based LDAP;research on backstepping integral control of two order nonlinear systems with input nonlinearity;research on high order sliding mode control of three order systems with input nonlinearity;research on teaching methods of motor drive technology based on information technology;on relativity of probability and information;pattern synthesis of antennas based on particle swarm optimization algorithm;critical condition for parametric resonance of axially mass-loaded string;research on medieval English literature teaching based on data analysis;and research of the distributed heterogeneous database conversion mechanism.

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AREA BASED STEREO image MATCHING TECHNIQUE USING HAUSDORFF DISTANCE AND TEXTURE ANALYSIS

AREA BASED STEREO IMAGE MATCHING TECHNIQUE USING HAUSDORFF D...

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International-Society-for-Photogrammetry-and-Remote-Sensing conference on Photogrammetric image Analysis (PIA)

作者： Joglekar, Jyoti Gedam, Shirish S. Indian Inst Technol CSRE Bombay Maharashtra India Indian Inst Technol Ctr Studies Resources Engn Bombay Maharashtra India

A conventional image matching techniques may be classified as either area based or feature based methods. In this paper an area based image matching method is proposed for dense disparity map. The method is a composite technique where first the similarity measure between template window and search window is found by normalized cross correlation technique. Few best matches are selected for the template window from the search sub windows, considering the largest normalized cross correlation coefficient. Further edge map is obtained for stereo image pair using canny edge detector. The matches for the template window are filtered using Hausdorff distance technique. Further texture analysis of the same template window and selected search windows is the third measure to decide the accurate match. Texture analysis is done with the co-occurrence matrices which is a two dimensional histogram of the occurrence of pair of intensity value in a given spatial relationship. With this composite method dense point to point correspondence can be achieved with greater accuracy. This method is tolerant to radiometric distortions and parallel processing of the three techniques will improve the speed.

关键词： Area image Matching Texture Hausdorff distance Reconstruction

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Advances in Computer Science, Environment, Ecoinformatics, and Education - International conference, CSEE 2011, Proceedings

Advances in Computer Science, Environment, Ecoinformatics, a...

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International conference on Advances in Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011

ISBN: (纸本)9783642233388

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Simultaneous Investigation of Local and distributed Functional Brain Connectivity from fMRI Data

Simultaneous Investigation of Local and Distributed Function...

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5th International IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) conference on Neural Engineering (NER)

作者： Deshpande, Gopikrishna Kerssens, Chantal Huo, Xiaoming Hu, Xiaoping Auburn Univ AU MRI Res Ctr Dept Elect & Comp Engn Auburn AL 36849 USA Emory Univ Dept Anesthesia Atlanta GA 30322 USA Georgia Tech Dept Ind & Syst Engn Atlanta GA 30332 USA Georgia Inst Technol WHC Dept Biomed Engn Atlanta GA 30332 USA

ISBN: (纸本)9781424441419

In this paper we propose a new method for simultaneous assessment of local and distributed functional brain connectivity from functional magnetic resonance imaging (fMRI) data. Our method maps fMRI time series from brain voxels into a high dimensional feature space where in clustering and vector quantization are performed in order to aggregate voxels with similar temporal evolution and segregate those with low temporal correlation. An iterative algorithm is proposed based on the Eigen structure of the geodesic distance matrix of the high dimensional manifold for selecting the number of clusters. The choice is then verified by unfolding the manifold using ISOMAP. A combined connectivity index (CCI) is then defined for every brain region based on the percentage of its voxels connected to each other and to voxels from other regions. The CCI maps local and distributed connectivity on a continuum from 0 to 1. This method was applied to resting state fMRI data obtained from humans in one of the two states: normal awake state and a sedated state induced by propofol anesthesia. Our results demonstrate that propofol anesthesia makes the connectivity in the brain become more local and less distributed as compared to awake state. In addition, our results show that the distributed connectivity between the thalamus and the cortex is greatly impacted by anesthesia, lending support to the thalamo-cortical disconnection hypothesis. However, our results indicate the thalamus was still connected to the cortex via the amygdala, providing a pathway for sensory information to reach the cortex during sedation. In the cortex, the connectivity also tended to become more local than distributed, supporting the cortico-cortical disconnection hypothesis. Therefore, our conclusions reconcile both the hypotheses of anesthetic action and altered states of consciousness, and demonstrate the utility of our approach for addressing important neuroscientific questions.

关键词： Anesthesia Drugs IP networks ISOMAP Magnetic resonance imaging Manifolds Time series analysis Vector quantization amygdala biomedical MRI brain brain voxels clustering combined connectivity index cortex cortico-cortical disconnection data acquisition distributed functional brain connectivity fMRI functional magnetic resonance imaging geodesic distance matrix high dimensional feature space iterative algorithm iterative methods local functional brain connectivity medical image processing neurophysiology pattern clustering propofol anesthesia thalamus time series vector quantisation vector quantization

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