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检索条件"任意字段=10th International Conference on Algorithms and Architectures for Parallel Processing"

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A path-based equivalence checking method for Petri net based models of programs

A path-based equivalence checking method for Petri net based...

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international Joint conference on Software Technologies (ICSOFT)

作者： Soumyadip Bandyopadhyay Dipankar Sarkar Kunal Banerjee Chittaranjan Mandal Indian Institute of Technology Kharagpur India

ISBN: (纸本)9781467385312

Programs are often subjected to significant optimizing and parallelizing transformations. It is therefore important to model parallel behaviours and formally verify the equivalence of their functionalities. In this work, the untimed PRES+ model (Petri net based Representation of Embedded Systems) encompassing data processing is used to model parallel behaviours. Being value based with inherent scope of capturing parallelism, PRES+ models depict such data dependencies more directly; accordingly, they are likely to be more convenient as the intermediate representations (IRs) of both the source and the transformed codes for translation validation than strictly sequential variable-based IRs like Finite State Machines with Datapath (FSMDs) (which are essentially sequential control data-flow graphs (CDFGs)). In this work, a path based equivalence checking method for PRES+ models is presented.

关键词： Computational modeling Data models Petri nets Adaptation models Embedded systems parallel processing

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Nonbinary multi-parallel-concatenated single-parity-check (NB-MPCSPC) codes over partial-response channels

Nonbinary multi-parallel-concatenated single-parity-check (N...

引用

international conference on Information, Communications and Signal processing

作者： Zhiliang Qin Anmin Kong Xueqiang Wang Data Storage Institute Singapore

ISBN: (纸本)9781467372190

In this paper, we propose a high-rate nonbinary multi-parallel-concatenated single-parity-check (NB-MPCSPC) code as a low-complexity coding scheme for data storage channels. the proposed scheme is composed of parallel branches of nonbinary SPC codes over a Galois Field (GF) and can be flexibly designed to achieve a wide range of code rates and codeword lengths. the encoding can be directly implemented based on the parity-check matrix; while the decoding is simplified by using the first-order MacLaurin Series to approximate the check-node operation. Compared with its binary counterpart, the proposed nonbinary coding scheme significantly improves bit-error-rate (BER) performance in the error-floor region. Simulation results show that a noticeable performance gain is obtained over conventional binary low-density parity-check (LDPC) codes when used in turbo equalization for partial-response channels.

关键词： Decoding Iterative decoding Manganese Channel coding Detectors

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MR-COF: A genetic MapReduce configuration optimization framework 15th

MR-COF: A genetic MapReduce configuration optimization frame...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Liu, Chao Zeng, Deze Yao, Hong Hu, Chengyu Yan, Xuesong Fan, Yuanyuan Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan430074 China China Services Computing Technology and System Lab and Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319271392

Hadoop/MapReduce has emerged as a de facto programming framework to explore cloud-computing resources. Hadoop has many configuration parameters, some of which are crucial to the performance of MapReduce jobs. In practice, these parameters are usually set to default or inappropriate values. this severely limits system performance (e.g., execution time). therefore, it is essential but also challenging to investigate how to automatically tune these parameters to optimize MapReduce job performance. In this paper, we propose an automatic MapReduce configuration optimization framework named as MR-COF. By monitoring and analyzing the runtime behavior, the framework adopts a cost-based performance prediction model that predicts the MapReduce job performance. In addition, we design a genetic search algorithm which iteratively tunes parameters in order to find out the best one. Testbed-based experimental results show that the average MapReduce job performance is increased by 35% with MR-COF compared to the default configuration. © Springer international Publishing Switzerland 2015.

关键词： MapReduce

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Live Data Replication Approach from Relational Tables to Schema-Free Collections Using Stream processing Framework

Live Data Replication Approach from Relational Tables to Sch...

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international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Kun Ma Bo Yang Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China

ISBN: (纸本)9781467394741

Recent researches focus on the data replication issue from relational tables to schema-free collections in a batch processing way. However, there are few publications on live data replication in real time. In this paper, we attempt to address this legacy issue with new stream processing framework. the process of replication consists of log-based change data capture and stream-based data replication. Data replication mappings are present, and the proposed architecture of stream processing framework including column grouping, column merging and column versioning, is introduced to avoid data lost in case of failure. Finally, our experimental evaluation of live data replication approach with stream processing framework shows the higher effectiveness and efficiency than current methods.

关键词： Real-time systems Relational databases Data mining Big data Reliability Transforms

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Modeling and experimental investigations of the surface layer temperature of titanium alloys during AEDG processing 10th

Modeling and experimental investigations of the surface laye...

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10th international conference on Diffusion in Solids and Liquids, Mass Transfer - Heat Transfer - Microstructure and Properties - Nanodiffusion and Nanostructured Materials, DSL 2014

作者： Golabczak, Andrzej Golabczak, Marcin Konstantynowicz, Andrzej Swiecik, Robert Galant, Marcin Lodz University of Technology Department of Production Engineering Stefanowskiego 1/15 Str. Lodz90-924 Poland Lodz University of Technology Institute of Machine Tools and Production Engineering Stefanowskiego 1/15 Str. Lodz90-924 Poland

ISBN: (纸本)9783038355168

Observing the latest manufacturing processes, the following tendencies can be noted: the gain of the energetic efficiency and shortening of the processing time with parallel preservation of the dimensions tolerance, shape tolerance and outer layer quality of the processed workpiece. Also the possibilities of gaining efficiency by rising criteria for process parameters are limited. It is mainly observed in the processing of hard machinable materials like titanium alloys or sintered carbides. Problems related to poor machinability were revealed during the final manufacturing processes using abrasive grinding [1,2]. In this work the results which have been presented are related to the influence by selected electrical parameters of the Abrasive Electrodischarge Grinding (AEDG) on the surface layer temperature of machined samples, in comparison to conventional grinding. Also the change in temperature during the AEDG has been depicted. the basis of this work is similar to the investigations of the deep grinding of surfaces of the titanium alloy Ti6Al4V using CBN and a diamond grinding wheel. For the comparative evaluation of the conventional grinding and AEDG, measurements of the specific grinding energy, energy of the spark discharge and internal stresses in the surface layer have been used. © (2015) Trans Tech Publications, Switzerland.

关键词： Abrasives

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Performance Evaluation of a MapReduce Hadoop-Based Implementation for processing Large Virtual Campus Log Files

Performance Evaluation of a MapReduce Hadoop-Based Implement...

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international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Fatos Xhafa Daniel Garcia Daniel Ramirez Santi Caballé Universitat Politècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781467394741

Cloud computing technologies are bringing new scales of computational processing power and storage capacity to meet very demanding requirements of today's applications. One such family of applications is the one of analytics based on processing big data. More specifically, there is a large family of analytics applications from processing log data files. Indeed, log data files are commonplace in many Internet-based systems and applications, comprising system logs, server logs, application logs, databases logs, user activity logs, etc. these applications are analytics oriented applications based on processing the various types of log files. While log data file processing has been recently an issue of investigation by many researchers and developers, the new feature is that of scale: Cloud based systems can enable processing unlimited amount of data either off-line or online in streaming mode. In this work we evaluate the performance of a MapReduce Hadoop-based implementation for processing large log data files of a Virtual Campus. the study aims to reveal the potential of using such implementations as a basis for learning analytics for use by a variety of users in a Virtual Campus.

关键词： Big data Web servers Education Data mining Cloud computing Databases

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3D reconstruction of porous media using MPS based on GPU

3D reconstruction of porous media using MPS based on GPU

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international conference on Computer Science & Education

作者： Yi Du Xiaoxia Cao Ting Zhang Sch. of Comput. & Inf. Shanghai Second Polytech. Univ. Shanghai China

ISBN: (纸本)9781479966011

It is very important for the study of predicting fluids flowing mechanisms in porous media that the characteristics of porous media can be extracted in relatively smaller scales, and then are copied in a larger region to reconstruct 3D porous media. One of multiple-point statistics (MPS) method, the single normal equation simulation algorithm (SNESIM), has been widely used in reconstructing 3D porous media recently. However, owing to its large CPU cost and rigid memory demand, the application of SNESIM has been limited in some cases. To overcome this disadvantage, parallelization of SNESIM is performed on the compute unified device architecture (CUDA) kernels in the graphic processing unit (GPU) to acquire high-quality reconstruction with a low CPU cost. this parallel GPU-version 3D porous media reconstruction method only requires fixed and relatively small size memory and benefits from the tremendous calculating power given by CUDA kernels to shorten the CPU time, showing its high efficiency and a useful trend for the reconstruction of porous media compared with the former CPUversion reconstruction method.

关键词： Porous media Graphic processing unit parallel Multiple-point statistics

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Decentralized real-time power system analysis: A conceptual framework for the future grids

Decentralized real-time power system analysis: A conceptual ...

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10th international conference on Advances in Power System Control, Operation & Management (APSCOM 2015)

作者： S. M. Kouhsari K.W. Chan S. M. Mazhari Hong Kong Polytechnic University Kowloon HK Amirkabir University of Technology Tehran Tehran IR

ISBN: (纸本)9781510830059

this short note tries to propose a somewhat different structure of the prevalent power system analysis approaches as a research idea for the near future power grids. It proposes a change in attitude to deal with power system basic analysis such as load flow, fault analysis, transient stability, harmonic analysis, and so on; the new attitude seem more suitable than prevalent frameworks for the coming power grids in which privatization, restructuring and data security accompanied by advanced communication and measuring facilities are all came to each other. the letter emphasis on a customer-by-customer decentralized approach which leads us to have real-time analysis of a n-million busbar system on million computers somehow communication transactions are substantially limited, measurements are reduced, restructuring policies are met, and the entire previously research advancements such as parallel processing and optimization based features are applicable in the new platform.

关键词： power system analysis Power grids real-time analysis Data Security parallel processing (COMPUTERS) power systems conceptual framework Decentralized Attitude grids Grates

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Efficient Lava Flows Simulations with OpenCL: A Preliminary Application for Civil Defence Purposes

Efficient Lava Flows Simulations with OpenCL: A Preliminary ...

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international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Maurizio Macri Alessio De Rango Davide Spataro Donato D'Ambrosio William Spataro University of Calabria Italy Univ. of Calabria Arcavacata di Rende Calabria IT CNR-IRPI Sezione di Cosenza Italy

ISBN: (纸本)9781467394741

GPGPU (General Purpose computing on Graphics processing Units) has marked a revolution in the field of parallel Computing allowing to achieve computational performance unimaginable until a few years ago. this hardware has proven to be extremely reliable and suitable to simulate Cellular Automata (CA) models for modeling complex systems whose evolution can be described in terms of local interactions. Starting from previous GPGPU implementations of CA models with CUDA, this paper presents an effective implementation of a well-known numerical model for simulating lava flows on Graphical processing Units (GPU) based on the OpenCL (Open Computing Language) standard. In addition, a preliminary Civil Defence application related Hazard maps of an area located at Mt. Etna volcano (South Italy), confirms the validity of OpenCL and both low-cost and high-end graphics hardware as an alternative to expensive solutions for the simulation of CA models.

关键词： Computational modeling Graphics processing units Kernel Numerical models Automata Performance evaluation Mathematical model

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DOA Estimation Method Based on Neural Network

DOA Estimation Method Based on Neural Network

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international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Zhang Ping Department of Electronic Technology Engineering University of CAPF Xi'an China

Traditional signal direction of arrival (DOA) estimation algorithm has exist some problems, such as a large amount of calculation and slow convergence speed. In this paper, neural network method is used to improve the performance of DOA estimation. Due to the fact that BP neural network is inclined to be trapped in local minimum point, particle swarm optimization (PSO) algorithm is applied to optimization the weights and threshold. the model of DOA estimation based on PSO-BP neural network is constructed and trained. Simulation results show that, compared with classical RBFNN method and traditional MUSIC algorithm, the optimized BP neural network method has higher estimation accuracy and real-time performance.

关键词： Estimation Direction-of-arrival estimation Biological neural networks Covariance matrices Arrays Array signal processing

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