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JCR Impact Factor: 0.800
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Current issue: Feb 2024
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2014 - 17
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 HIGH-IMPACT PAPER 

High Performance Processing and Analysis of Geospatial Data Using CUDA on GPU

STOJANOVIC, N. See more information about STOJANOVIC, N. on SCOPUS See more information about STOJANOVIC, N. on IEEExplore See more information about STOJANOVIC, N. on Web of Science, STOJANOVIC, D. See more information about STOJANOVIC, D. on SCOPUS See more information about STOJANOVIC, D. on SCOPUS See more information about STOJANOVIC, D. on Web of Science
 
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Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (810 KB) | Citation | Downloads: 882 | Views: 971

Author keywords
high performance computing, geographic information systems, multiprocessing systems, parallel programming, performance analysis

References keywords
parallel(6), data(6), graphics(5), cuda(5), analysis(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-11-30
Volume 14, Issue 4, Year 2014, On page(s): 109 - 114
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.04017
Web of Science Accession Number: 000348772500017
SCOPUS ID: 84921662038

Abstract
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In this paper, the high-performance processing of massive geospatial data on many-core GPU (Graphic Processing Unit) is presented. We use CUDA (Compute Unified Device Architecture) programming framework to implement parallel processing of common Geographic Information Systems (GIS) algorithms, such as viewshed analysis and map-matching. Experimental evaluation indicates the improvement in performance with respect to CPU-based solutions and shows feasibility of using GPU and CUDA for parallel implementation of GIS algorithms over large-scale geospatial datasets.


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Cited-By Clarivate Web of Science

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SCOPUS® Times Cited: 14
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Cited-By CrossRef

[1] Speeding Up VM Image Distribution for Cloud Data Centers, LEE, C., LEE, H., KIM, E., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 16, 2016.
Digital Object Identifier: 10.4316/AECE.2016.04002
[CrossRef] [Full text]

[2] Parallelizing Multiple Flow Accumulation Algorithm using CUDA and OpenACC, Stojanovic, Natalija, Stojanovic, Dragan, ISPRS International Journal of Geo-Information, ISSN 2220-9964, Issue 9, Volume 8, 2019.
Digital Object Identifier: 10.3390/ijgi8090386
[CrossRef]

[3] Challenges of a GIS-based physical-geographical regionalization of Poland, Piniarski, Witold, Environmental Monitoring and Assessment, ISSN 0167-6369, Issue 9, Volume 195, 2023.
Digital Object Identifier: 10.1007/s10661-023-11734-4
[CrossRef]

[4] Accelerating adaptive inverse distance weighting interpolation algorithm on a graphics processing unit, Mei, Gang, Xu, Liangliang, Xu, Nengxiong, Royal Society Open Science, ISSN 2054-5703, Issue 9, Volume 4, 2017.
Digital Object Identifier: 10.1098/rsos.170436
[CrossRef]

[5] Fast Gap-Filling of Massive Data by Local-Equilibrium Conditional Simulations on GPU, Lach, M., Žukovič, M., Mathematical Geosciences, ISSN 1874-8961, 2023.
Digital Object Identifier: 10.1007/s11004-023-10092-8
[CrossRef]

[6] Implementation and evaluation of two parallel computational models for the simulation of a long‐haul DWDM system limited by FWM, Sánchez‐Lara, Rafael, López‐Martínez, José L., Trejo‐Sánchez, Joel A., Offerhaus, Herman L., Álvarez‐Chávez, José A., Concurrency and Computation: Practice and Experience, ISSN 1532-0626, Issue 7, Volume 36, 2024.
Digital Object Identifier: 10.1002/cpe.7964
[CrossRef]

[7] Simulation of an inelastic dispersive phenomenon: stimulated Brillouin scattering in a single-mode fiber segment through parallelism, Sanchez-Lara, R., Trejo-Sanchez, J. A., Lopez-Martinez, J. L., Alvarez-Chavez, J. A., The Journal of Supercomputing, ISSN 0920-8542, Issue 7, Volume 74, 2018.
Digital Object Identifier: 10.1007/s11227-018-2379-5
[CrossRef]

[8] A General-Purpose Graphics Processing Unit (GPGPU)-Accelerated Robotic Controller Using a Low Power Mobile Platform, Rizvi, Syed, Cabodi, Gianpiero, Patti, Denis, Gulzar, Muhammad, Journal of Low Power Electronics and Applications, ISSN 2079-9268, Issue 2, Volume 7, 2017.
Digital Object Identifier: 10.3390/jlpea7020010
[CrossRef]

[9] Combining Reused Frequency, Most Recently Used and Program Counter Predictor as Last Level Cache Replacement Policy, Chung, Yee Ming, Halim, Zaini Abdul, 2018 IEEE Student Conference on Research and Development (SCOReD), ISBN 978-1-5386-9175-5, 2018.
Digital Object Identifier: 10.1109/SCORED.2018.8711066
[CrossRef]

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