The Research of MapReduce on the Cloud Computing

2012 ◽  
Vol 182-183 ◽  
pp. 2127-2130
Author(s):  
Tie Liang Gao ◽  
Jiao Li ◽  
Jun Peng Zhang ◽  
Bing Jie Shi
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Large Scale ◽  
Parallel Program ◽  
Large Scale Data ◽  
Distribute System ◽  
Scale Data

MapReduce is a kind of model of program that is use in the parallel computing about large scale data muster in the Cloud Computing[1] , it mainly consist of map and reduce . MapReduce is tremendously convenient for the programmer who can’t familiar with the parallel program .These people use the MapReduce to run their program on the distribute system. This paper mainly research the model and process and theory of MapReduce .

GPU enhanced parallel computing for large scale data clustering

2013 ◽  
Vol 29 (7) ◽  
pp. 1736-1741 ◽  
Author(s):  
Xiaohui Cui ◽  
Jesse St. Charles ◽  
Thomas Potok
Keyword(s):  
Parallel Computing ◽  
Data Clustering ◽  
Large Scale ◽  
Large Scale Data ◽  
Scale Data

scholarly journals EON OF IMPLEMENTING A MULTIFACETED CLOUD BASED OCR IN APPLE’S COMPASSIONATE APP STORE MILIEU

2016 ◽  
pp. 235-239
Author(s):  
C. Infant Louis Richards ◽  
T. Yuva ◽  
J.SYLVESTER BRITTO
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Character Recognition ◽  
Large Scale ◽  
Scale Up ◽  
App Store ◽  
Large Scale Data ◽  
One Machine ◽  
Scale Data ◽  
Cursive Scripts

Cloud Architectures discourse key hitches surrounding large-scale data dispensation. In customary data processing it is grim to get as many machines as an application needs. Second, it is difficult to get the machines when one needs them. Third, it is difficult to dispense and harmonize a large-scale job on different machines, run processes on them, and provision another machine to recover if one machine fails. Fourth, it is difficult to auto scale up and down based on dynamic workloads. Fifth, it is difficult to get rid of all those machines when the job is done. Cloud Architectures solve such difficulties.Optical character recognition of cursive scripts present a number of thought-provokingsnags in both segmentation and recognition processes and this entices many researches in the arena of contraption learning. This paper presents the best approach based on a mishmash of OCR and Cloud Computing to handle with the Apple’s prerequisite, to make it available in the app store to design a splendid OCR for outdoor portable documents. The enactment results on a comprehensive database show a high notch of accuracy which meets the requirements of viable use.

Fourier Transform Based GPU Acceleration

2013 ◽  
Vol 347-350 ◽  
pp. 2926-2929
Author(s):  
Jing Shen Li
Keyword(s):  
Fourier Transform ◽  
Parallel Computing ◽  
Large Scale ◽  
Gpu Acceleration ◽  
Image Transformation ◽  
Gpu Parallel Computing ◽  
Large Scale Data ◽  
Relationship Of ◽  
The Relationship ◽  
Scale Data

In digital image processing, Fourier transform is an important algorithm of image transformation. In order to improve the speed of Fourier transform, the paper proposes to deal with the image with GPU parallel computing through the method of GPU accelerating MATLB. The relationship of data scale and calculation speed is analyzed through the traditional CPU serial operation and GPU parallel computing. Computer simulations verify that the calculation speed can be improved by GPU about large scale data.

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