2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing最新文献

Distributed adaptive spanning tree for data gathering in Wireless Sensor Networks 无线传感器网络数据采集的分布式自适应生成树

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-06 DOI: 10.1109/PDGC.2012.6449869

H. Poostchi, M. Akbarzadeh-T., S. M. Taheri

引用次数: 0

Porting clondike to heterogeneous platforms 将clondike移植到异构平台

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449850

J. Gattermayer, P. Tvrdík

引用次数: 2

Computing aspects of monitoring walking disorder using body sensor network and neural network 用身体传感器网络和神经网络监测行走障碍的计算方面

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449837

D. Acharjee, A. Mukherjee, N. Mukherjee

{"title":"Computing aspects of monitoring walking disorder using body sensor network and neural network","authors":"D. Acharjee, A. Mukherjee, N. Mukherjee","doi":"10.1109/PDGC.2012.6449837","DOIUrl":"https://doi.org/10.1109/PDGC.2012.6449837","url":null,"abstract":"Here, it is proposed to monitor walking disorder of any patient with the help of wireless three dimensional (3D) accelerometer based body sensors and its networks. We gather Ground Truth Data from the sensors, filter it, boost up it when required, then collect some important features and compare with the features of run time data using different algorithms developed by us. Where, for matching the run time features, we use supervised learning method of back propagation neural network. After gathering data, a prototype model of computation is developed which may be used in any motion disorder of any subjects like: patients, athletes, pilots and astronauts. The contribution of this paper is focused on to develop a model of computational processes required to monitor activity recognition system. The computing model developed is validated working over different walking motion disorders of different subjects and then discussed how this model can be applied in an organization to provide internet based online patient's information services with the help of Feature Server and Local Server connected by wireless radio link of Personal Computing Devices like mobile phone, PDA, laptop etc.","PeriodicalId":166718,"journal":{"name":"2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115491459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Exploration of automatic optimization for CUDA programming CUDA编程的自动优化探索

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449791

M. Al-Mouhamed, A. ul Hassan Khan

{"title":"Exploration of automatic optimization for CUDA programming","authors":"M. Al-Mouhamed, A. ul Hassan Khan","doi":"10.1109/PDGC.2012.6449791","DOIUrl":"https://doi.org/10.1109/PDGC.2012.6449791","url":null,"abstract":"Graphic processing Units (GPUs) are gaining ground in high-performance computing. CUDA (an extension to C) is most widely used parallel programming framework for general purpose GPU computations. However, the task of writing optimized CUDA program is complex even for experts. We present a method for restructuring loops into an optimized CUDA kernels based on a 3-step algorithm which are loop tiling, coalesced memory access, and resource optimization. We also establish the relationships between the influencing parameters and propose a method for finding possible tiling solutions with coalesced memory access that best meets the identified constraints. We also present a simplified algorithm for restructuring loops and rewrite them as an efficient CUDA Kernel. The execution model of synthesized kernel consists of uniformly distributing the kernel threads to keep all cores busy while transferring a tailored data locality which is accessed using coalesced pattern to amortize the long latency of the secondary memory. In the evaluation, we implement some simple applications using the proposed restructuring strategy and evaluate the performance in terms of execution time and GPU throughput.","PeriodicalId":166718,"journal":{"name":"2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123123065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

A novel framework and policies for on-line block of cores allotment for multiple DAGs on NoC 一种新的NoC上多dag在线核块分配框架和策略

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449813

U. Boregowda, V. R. Chakaravarthy

引用次数: 0

Breast cancer detection using backpropagation neural network with comparison between different neuron 用反向传播神经网络检测乳腺癌，并对不同神经元进行比较

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449811

P. Pawar, D. Patil

引用次数: 4

Task scheduling through limited duplication with processor utilization in grid computing system 网格计算系统中基于处理器利用率的有限重复任务调度

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449947

N. Agarwal, C. Gupta, A. Khare

引用次数: 1

Combinatorial reliability analysis of Folded Crossed cube 折叠交叉立方体组合可靠性分析

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449901

S. Jena, P. Radhika, P. Reddy, G. Sowmya

引用次数: 2

A novel hybrid approach to enhance low resolution images using particle swarm optimization 基于粒子群优化的低分辨率图像增强混合方法

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449941

M. I. Quraishi, K. G. Dhal, J. P. Choudhury, K. Pattanayak, M. De

{"title":"A novel hybrid approach to enhance low resolution images using particle swarm optimization","authors":"M. I. Quraishi, K. G. Dhal, J. P. Choudhury, K. Pattanayak, M. De","doi":"10.1109/PDGC.2012.6449941","DOIUrl":"https://doi.org/10.1109/PDGC.2012.6449941","url":null,"abstract":"Enhancement of low resolution images is always a priority Enhancement of low resolution images is always a priority field of digital image processing. In this paper, we propose a novel hybrid approach based on discrete wavelet transform (DWT) and particle swarm optimization (PSO). To develop the proposed method we use spatial domain as well as frequency domain. To reduce the low frequencies from the input image we use the frequency domain. DWT is used to decompose the input low resolution image into different sub bands. Each of the interpolated high frequency sub band (LH, HL, HH) is then summed up with the interpolated output image of the frequency domain. In order to achieve high resolution image, the estimated high frequency sub bands of the intermediate stage and the interpolated low resolution input image have been combined by using inverse DWT. To generate a better high resolution image particle swarm optimization (PSO) technique has been used. The quantitative (root mean square error, normalized cross correlation, normalized absolute error) and visual outcome show the strength of this proposed method.","PeriodicalId":166718,"journal":{"name":"2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125105710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Identification of nonlinear systems from the knowledge around different operating conditions: A feed-forward multi-layer ANN based approach 基于不同运行条件的非线性系统识别:一种基于前馈多层神经网络的方法

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing Pub Date : 2012-12-01 DOI: 10.1109/PDGC.2012.6449856

Sayan Saha, Saptarshi Das, Anish Acharya, Abhishek Kumar, S. Mukherjee, Indranil Pan, Amitava Gupta

引用次数: 8