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Advances in Electrical and Computer Engineering
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Advances in Electrical and Computer Engineering
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High Performance Processing and Analysis of Geospatial Data Using CUDA on GPU

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2014 English Publisher:Universitatea Stefan cel Mare din SuceavaJournal:Advances in Electrical and Computer Engineering, volume 14, pages 109-114 (issn: 1582-7445, eissn: 1844-7600, Copyright policy )
Authors: STOJANOVIC, N.; STOJANOVIC, D.;

doi: 10.4316/aece.2014.04017

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

Abstract

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.

Keywords

high performance computing, geographic information systems, multiprocessing systems, TK7885-7895, Computer engineering. Computer hardware, parallel programming, Electrical engineering. Electronics. Nuclear engineering, performance analysis, TK1-9971

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    		 14
    popularity
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    		 Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Average
gold