High performance geospatial analysis on emerging parallel architectures

Authors:
Amy Apon;Seth Warn
Affiliations:
University of Arkansas;University of Arkansas
Venue:
High performance geospatial analysis on emerging parallel architectures
Year:
2011

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Accelerating SIFT on hybrid clusters

Proceedings of the ACM SIGSPATIAL Second International Workshop on High Performance and Distributed Geographic Information Systems

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Abstract

Geographic information systems (GIS) are performing increasingly sophisticated analyses on growing data sets. These analyses demand high performance. At the same time, modern computing platforms increasingly derive their performance from several forms of parallelism.This dissertation explores the available parallelism in several GIS-applied algorithms: view-shed calculation, image feature transform, and feature analysis. It presents implementations of these algorithms that exploit parallel processing to reduce execution time, and analyzes the effectiveness of the implementations in their use of parallel processing.