DocumentCode :
2028764
Title :
Real-time signal identification in big data streams Bragg-Spot localization in photon science
Author :
Becker, Daniel ; Streit, Achim
Author_Institution :
HTW, Univ. of Appl. Sci., Berlin, Germany
fYear :
2015
fDate :
20-24 July 2015
Firstpage :
611
Lastpage :
616
Abstract :
The next generation of photon science experiments will be able to produce thousands of images per second. However, many of them will not be useful for further analysis. Due to this large amount of data, it is not feasible to store all data offline for later analysis. Instead, this analysis has to be shifted as close to the data sources as possible. In addition, due to the large volume and velocity of the data, this analysis has to be done highly parallel. In this article we recapitulate our previous work on algorithms on data analysis in photon science as well as the potentially relevant BM3D algorithm. These algorithms are discussed with a focus on their parallel processing capabilities.
Keywords :
Big Data; data analysis; parallel processing; physics computing; BM3D algorithm; Bragg-Spot localization; big data streams; data analysis; parallel processing; photon science; real-time signal identification; Algorithm design and analysis; Clustering algorithms; Detectors; Image edge detection; Noise; Noise reduction; Photonics; big data; image processing; nanocrystallography; online processing; parallel processing; photon science;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing & Simulation (HPCS), 2015 International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
978-1-4673-7812-3
Type :
conf
DOI :
10.1109/HPCSim.2015.7237101
Filename :
7237101
Link To Document :
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