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High-performance parallel approaches for three-dimensional light detection and ranging point clouds gridding

Title
High-performance parallel approaches for three-dimensional light detection and ranging point clouds gridding
Authors
Rizki P.N.M.Lee H.Lee M.Oh S.
Ewha Authors
이민수
SCOPUS Author ID
이민수scopus
Issue Date
2017
Journal Title
Journal of Applied Remote Sensing
ISSN
1931-3195JCR Link
Citation
Journal of Applied Remote Sensing vol. 11, no. 1
Keywords
digital elevation modelGPGPUkriginglight detection and rangingMapReducemessage passing interface
Publisher
SPIE
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
With the rapid advance of remote sensing technology, the amount of three-dimensional point-cloud data has increased extraordinarily, requiring faster processing in the construction of digital elevation models. There have been several attempts to accelerate the computation using parallel methods; however, little attention has been given to investigating different approaches for selecting the most suited parallel programming model for a given computing environment. We present our findings and insights identified by implementing three popular high-performance parallel approaches (message passing interface, MapReduce, and GPGPU) on time demanding but accurate kriging interpolation. The performances of the approaches are compared by varying the size of the grid and input data. In our empirical experiment, we demonstrate the significant acceleration by all three approaches compared to a C-implemented sequential-processing method. In addition, we also discuss the pros and cons of each method in terms of usability, complexity infrastructure, and platform limitation to give readers a better understanding of utilizing those parallel approaches for gridding purposes. © 2017 Society of Photo-Optical Instrumentation Engineers (SPIE).
DOI
10.1117/1.JRS.11.016011
Appears in Collections:
인공지능대학 > 컴퓨터공학과 > Journal papers
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