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检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing"

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A systemc TLM framework for distributed simulation of complex systems with unpredictable communication

A systemc TLM framework for distributed simulation of comple...

引用

conference on Design and Architectures for Signal and image processing

作者： Julien Peeters Nicolas Ventroux Tanguy Sassolas Lionel Lacassagne LIST Embedded Computing Laboratory CEA Gif-sur-Yvette France

Increasingly complex systems need parallelized simulation engines. In the context of SystemC simulation, existing proposals require predicting communication in the simulated system. However, this is often unpredictable. In order to deal with unpredictable systems, this paper presents a parallelization approach using asynchronous communication without modification of the SystemC simulation engine. Simulated system model is cut up and distributed across separate simulation engines, each part being evaluated in parallel of others. Functional consistency is preserved thanks to the simulated system write exclusive memory access policy while temporal consistency is guaranteed using explicit synchronization. Experimental results show up a speed-up up to 13× on 16 processors.

关键词： Synchronization Load modeling Adaptation models Hardware Context Engines Program processors

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Experimental study of a parallel wavelets compression system for medical applications

Experimental study of a parallel wavelets compression system...

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IEEE Pacific Rim conference on Communications, Computers and Signal processing

作者： E. Moyano P. Gonzalez L. Orozco-Barbosa F. Quiles Departamento de Informáica Escuela Politécnica Superior de Albacete Universidad de Castilla La Mancha Albacete Spain School of Information Technology and Engineering University of Ottawa Ottawa ONT Canada

In this paper, we undertake the development and performance evaluation of a parallel system for the compression of medical images. The system under study consists of a network of workstations running a parallel implementation of a wavelets compression software. Different data distribution and synchronization strategies are evaluated aiming to minimize the system response time. Numerical results of the different strategies under investigation are provided.

关键词： Medical services Biomedical equipment image coding Biomedical imaging image reconstruction Wavelet transforms Workstations Application software distributed computing Information technology

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Efficient parallelization of the Google Trigram Method for Document Relatedness Computation

Efficient Parallelization of the Google Trigram Method for D...

引用

International conference on parallel processing Workshops (ICPPW)

作者： Xinxin Kou Jie Mei Zhimin Yao Andrew Rau-Chaplin Aminul Islam Abidalrahman Moh'd Evangelos Milios Faculty of Computer Science Dalhousie University Halifax Canada

Finding pair wise document relatedness plays an important role in a variety of Natural Language processing problems. Google Trigram Method (GTM) is one of the corpus-based unsupervised method that can be used to capture word relatedness and document relatedness. It has been shown that it is possible to apply GTM to construct high quality document relatedness applications. However, there are challenges in implementing GTM for pair-wise document relatedness computation on a large volume of document set given its high computational complexity. This paper presents time and space efficient methods for the computation of pair-wise document relatedness using GTM. In order to improve the performance algorithmic engineering, data structure enhancement, and parallel computing methods are applied. Two parallel methods are discussed in this paper: shared memory multicore implementation and distributed memory Hadoop implementation. Both parallel methods provide an order of magnitude improvement in accelerating the pair-wise document relatedness computation using GTM.

关键词： Dictionaries Arrays Google Multicore processing parallel processing Acceleration

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Network Optimized by K-L Transform for Digital Modulation Identification

Network Optimized by K-L Transform for Digital Modulation Id...

引用

IEEE International conference on parallel and distributed Computing, Applications and Technologies (PDCAT)

作者： Yonghong Kuo Jian Chen Xiaohua Tan School of Communication Engineering Xidian University No.2 Taibai South Road Xi'an China

It is important for digital modulation identification based on neural network to determine a suitable size of a network. This paper proposes that the number of nodes in hidden layer which is the core for network optimizing can be confirmed by K-L transform. The validity and robustness are verified by simulation. The percentage of correct identification (PCI) is almost the same before and after the network optimizing.

关键词： Digital modulation Covariance matrix Network topology Neural networks Mean square error methods Robustness Digital communication Signal processing Optimization methods Redundancy

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A Power Sharing Method for Microgrid Consisting of HAPF and VSC

A Power Sharing Method for Microgrid Consisting of HAPF and ...

引用

image processing, Electronics and Computers (IPEC), Asia-Pacific conference on

作者： Mingming Zhang Ping Qin Yongjin Chen Hengjie Jia Wenyang Deng Shaoguan Power Supply Bureau of Guangdong Power Grid Co. Ltd Shaoguan Guangdong Guangzhou Power Electrical Technology Co. Ltd Guangzhou Guangdong

Converters play an imperative part in joining conveyed generators and directing control stream of microgrid and active distributed network (ADN). The hybrid active power filter is proposed to improve responsive control with a moo amplitude of operation's voltage. Its control extends and characteristics are distinctive based on a routine voltage source converter (VSC). Regulation of parallel-connected HAPF and VSC in active distributed networks is examined in this work. To completely utilize the control efficiency of every sort of converter, the power output allocation calculation among these two devices is considered for reduce add up to converter rating. A control reference assurance strategy is hence proposed and inserted in various leveled control system of the active distributed network. Comes about demonstrate that converter capacity is decreased by combining HAPF and VSC. Decoupling regulation method is utilized as the essential regulation strategy to every converter. Reenactment comes about are given to appear the legitimacy of the proposed strategy.

关键词： Simulation image processing Power control Microgrids Regulation Hybrid power systems Generators

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An alternative to data mapping for parallel PDE solvers: parallel grid generation

An alternative to data mapping for parallel PDE solvers: par...

引用

Scalable parallel Libraries conference

作者： N.P. Chrisochoides Northeast Parallel Architectures Center and Computer Science Department Syracuse University Syracuse NY USA

In this paper we identified and outlined the disadvantages of the traditional data mapping methods for the numerical solution of PDEs on distributed memory MIMD machines and we proposed a new approach that eliminates some of the disadvantages. Specifically, we presented a data-mapping approach based on parallel structured grid generation. The new approach is based on composite block structures to contract the size of the data-mapping problem. It is ten times faster than the fastest traditional data-mapping method, for relatively small problems, and approximately O(P) times faster, for very large problems (i.e., millions of grid points) that are processed on coarse-grain distributed memory MIMD machines with P processors.< >

关键词： Mesh generation Partitioning algorithms Clustering algorithms Optimization methods Bismuth parallel architectures Computer science Educational institutions Contracts parallel processing

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Segmentation of MR images by Using Grow and Learn Network on FPGAs

Segmentation of MR Images by Using Grow and Learn Network on...

引用

Annual International conference of the IEEE Engineering in Medicine and Biology Society

作者： Salim Cinar Mehmet Nadir Kurnaz Department of Electrical and Electronics Engineering Faculty of Engineering Nigde University

ISBN: (纸本)9781457702150

image segmentation is one of the mostly used procedures in the medical image processing applications. Due to the high resolution characteristics of the medical images and a large amount of computational load in mathematical methods, medical image segmentation process has an excessive computational complexity. Recently, FPGA implementation has been applied in many areas due to its parallel processing capability. In this study, neighbor-pixel-intensity based method for feature extraction and Grow and Learn (GAL) network for segmentation process are proposed. The proposed method is comparatively examined on both PC and FPGA platforms.

关键词： image segmentation Field programmable gate arrays parallel processing (COMPUTERS) Network Feature extraction images Personal computers Medical image processing computational methods GAL gene

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parallel global illumination method based on a nonuniform partitioning of the scene

Parallel global illumination method based on a nonuniform pa...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： J.R. Sanjurjo M. Amor M. Boo R. Doallo Departamento de Electrónica e Sistemas University of A Coruña Spain Department of Electronic and Computer Engineering University of Santiago de Compostela Spain

Achieving an efficient global illumination method is one of the more important current issues in computer graphics. The main problem is that the simulation for large scenes is a highly time-consuming process. In this paper we present a new nonuniform partitioning method in order to achieve a good load balance on a distributed memory system. This method is based on the minimization of a distribution function. Furthermore, we have developed a scheduling based on processor hierarchy which permits the utilization of a visibility mask with crossed frontiers. Finally, in order to evaluate the proposed method, we have used a progressive radiosity algorithm, running on a PC cluster with modern processor and network technology as a testbed. An efficient performance in terms of execution time and speedup has been obtained.

关键词： Lighting Layout Minimization methods Distribution functions Clustering algorithms Testing Proposals Concurrent computing Computer graphics Computational modeling

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Privacy-concerned parallel distributed Bayesian sequential detection

Privacy-concerned parallel distributed Bayesian sequential d...

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IEEE Global conference on Signal and Information processing (GlobalSIP)

作者： Zuxing Li Tobias J. Oechtering School of Electrical Engineering and the ACCESS Linnaeus Centre KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781479970896

In this paper, eavesdropping in parallel distributed sequential detections is considered. The privacy risk is evaluated by the minimal achievable Bayesian risk of a greedy and informed eavesdropper who is curious about the hypothesis realization. We propose a novel metric based on Bayesian risk to take the detection performance and privacy risk with different weights into account. We formulate and study the privacy-concerned parallel distributed Bayesian sequential detection problem under a finite time-horizon assumption. Solving this problem will lead to the optimal distributed sequential detection design which achieves the minimal privacy-concerned Bayesian risk. The study shows that it is not sufficient to consider a deterministic likelihood-ratio test for a remote decision maker at an active time index in the optimal privacy-concerned system design. However, properties of the optimal design indicate that the standard method can be extended to solve the proposed problem.

关键词： Bayes methods Privacy Indexes Optimization Measurement Standards Light rail systems

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Algorithmic Acceleration of parallel ALS for Collaborative Filtering: Speeding up distributed Big Data Recommendation in Spark

Algorithmic Acceleration of Parallel ALS for Collaborative F...

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International conference on parallel and distributed Systems (ICPADS)

作者： Manda Winlaw Michael B Hynes Anthony Caterini Hans De Sterck University of Waterloo ON Canada University of Waterloo Canada University of Waterloo Waterloo ON CA

Collaborative filtering algorithms are important building blocks in many practical recommendation systems. For example, many large-scale data processing environments include collaborative filtering models for which the Alternating Least Squares (ALS) algorithm is used to compute latent factor matrix decompositions. In this paper, we propose an approach to accelerate the convergence of parallel ALS-based optimization methods for collaborative filtering using a nonlinear conjugate gradient (NCG) wrapper around the ALS iterations. We also provide a parallel implementation of the accelerated ALS-NCG algorithm in the Apache Spark distributed data processing environment, and an efficient line search technique as part of the ALS-NCG implementation that requires only one pass over the data on distributed datasets. In serial numerical experiments on a linux workstation and parallel numerical experiments on a 16 node cluster with 256 computing cores, we demonstrate that the combined ALS-NCG method requires many fewer iterations and less time than standalone ALS to reach movie rankings with high accuracy on the MovieLens 20M dataset. In parallel, ALS-NCG can achieve an acceleration factor of 4 or greater in clock time when an accurate solution is desired; furthermore, the acceleration factor increases as greater numerical precision is required in the solution. Furthermore, the NCG acceleration mechanism is efficient in parallel and scales linearly with problem size on synthetic datasets with up to nearly 1 billion ratings. The acceleration mechanism is general and may also be applicable to other optimization methods for collaborative filtering.

关键词： Acceleration Motion pictures Collaboration Sparks Optimization Algorithm design and analysis Convergence

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