Efficiency of Uniform Grids for Intersection Detection on Serial and Parallel Machines

Franklin, W. Randolph; Chandrasekhar, N.; Kankanhalli, Mohan; Seshan, M.; Akman, Varol

doi:10.1007/978-3-642-83492-9_25

Cited by 26 publications

(29 citation statements)

References 12 publications

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“…Edge intersection detection is a subproblem of computing polygon overlay and most of the research aims to parallelize edge intersection detection phase only. Franklin et al [4] presented the uniform grid technique for parallel edge intersection detection. Their implementation was done using Sun 4/280 workstation and 16 processor Sequent Balance 21000.…”

Section: Overlay and Miscellaneous Approachesmentioning

confidence: 99%

MapReduce Algorithms for GIS Polygonal Overlay Processing

Puri

Agarwal

et al. 2013

2013 IEEE International Symposium on Parallel &Amp; Distributed Processing, Workshops and PHD Forum

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Polygon overlay is one of the complex operations in computational geometry. It is applied in many fields such as Geographic Information Systems (GIS), computer graphics and VLSI CAD. Sequential algorithms for this problem are in abundance in literature but there is a lack of distributed algorithms especially for MapReduce platform. In GIS, spatial data files tend to be large in size (in GBs) and the underlying overlay computation is highly irregular and compute intensive. The MapReduce paradigm is now standard in industry and academia for processing large-scale data. Motivated by the MapReduce programming model, we revisit the distributed polygon overlay problem and its implementation on MapReduce platform. Our algorithms are geared towards maximizing local processing and minimizing the communication overhead inherent with shuffle and sort phases in MapReduce. We have experimented with two data sets and achieved up to 22x speedup with dataset 1 using 64 CPU cores.

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Section: Overlay and Miscellaneous Approachesmentioning

confidence: 99%

MapReduce Algorithms for GIS Polygonal Overlay Processing

Puri

Agarwal

et al. 2013

2013 IEEE International Symposium on Parallel &Amp; Distributed Processing, Workshops and PHD Forum

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“…Database Management Systems for GIS Healey et al 1998 Line simplification Mower 1996 Line intersection Franklin et al 1989Network analysis, shortest paths Ding et al 1992Lanthier et al 2003 Network analysis, traffic flows Xiong and Marble 1996 Polygon aggregation Openshaw and Schmidt 1996 Polygon classification Openshaw and Turton 1996 Polygonization Hoel and Samet 2003 Polygon overlay Harding et al 1998 Spatial interaction models Birkin et al 1995 Remotely sensed image analysis Plaza et al 2007, Wilkinson 1998 Spatial interpolation, gridding Armstrong and Marciano 1997, Cramer and Armstrong 1999, Hodgson et al 1995, Luh et al 1997, Wang and Armstrong 2003Spatial statistics Armstrong et al 2005, Armstrong et al 1994, Armstrong and Marciano 1995, Rokos and Armstrong 1996, Wang et al 2004, Yan et al 2007 Surface feature extraction Rokos and Armstrong 1998 Vector topology creation Dowers et al 2000, Mineter 2003, Mineter et al 1998Visualization De Floriani et al 1994, Magillo and Puppo 1998, Mustafa et al 2006, Shekhar et al 1996 applications is bound to specific conventional parallel computer architectures, such as SIMD (single instruction stream and multiple data streams) and MIMD (multiple instruction streams and multiple data streams) systems (Flynn 1966). This tightcoupling approach is problematic in three important respects:…”

Section: Geographical Applications Citationsmentioning

confidence: 99%

A theoretical approach to the use of cyberinfrastructure in geographical analysis

Wang

Armstrong

2009

International Journal of Geographical Information Science

105

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This paper presents a theoretical approach that has been developed to capture the computational intensity and computing resource requirements of geographical data and analysis methods. These requirements are then transformed into a common framework, a grid-based representation of a spatial computational domain, which supports the efficient use of emerging cyberinfrastructure environments. Two key types of transformational functions (data-centric and operation-centric) are identified and their relationships are explained. The application of the approach is illustrated using two geographical analysis methods: inverse distance weighted interpolation and the G* i (d) spatial statistic. We describe the underpinnings of these two methods, present their conventional sequential algorithms, and then address their latent parallelism based on a spatial computational domain representation. Through the application of this theoretical approach, the development of domain decomposition methods is decoupled from specific high-performance computer architectures and task scheduling implementations, which makes the design of generic parallel processing solutions feasible for geographical analyses.

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“…The by means of a uniform grid data structure [11]. A hardware-accelerated z-buffer solution could also be used.…”

Section: Vertex-to-image Bindingmentioning

confidence: 99%

Acquiring, stitching and blending diffuse appearance attributes on 3D models

Rocchini¹,

Cignoni²,

Montani³

et al. 2002

Vis Comput

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A new system for the construction of highly realistic models of real free-form 3D objects is proposed, based on the integration of several techniques (automatic 3D scanning, inverse illumination, inverse texture-mapping and textured 3D graphics). Our system improves the quality of a 3D model (e.g. acquired with a range scanning device) by adding color detail and, if required, high frequency shape detail. Detail is obtained by processing a set of digital photographs of the object. This is carried out by performing several subtasks: to compute camera calibration and position, to remove illumination effects obtaining both illumination-invariant reflectance properties and a high resolution surface normal field, and finally to blend and stitch the acquired detail on the triangle mesh via standard texture mapping. In particular, the smooth join between different images that map on adjacent sections of the surface is obtained by applying an accurate piecewise local registration of the original images and by blending textures. For each mesh face which is on the adjacency border between different observed images, a corresponding triangular texture patch can also be resampled as a weighted blend of the corresponding adjacent image sections. Examples of the results obtained with sample works of art are presented and discussed.

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Efficiency of Uniform Grids for Intersection Detection on Serial and Parallel Machines

Cited by 26 publications

References 12 publications

MapReduce Algorithms for GIS Polygonal Overlay Processing

MapReduce Algorithms for GIS Polygonal Overlay Processing

A theoretical approach to the use of cyberinfrastructure in geographical analysis

Acquiring, stitching and blending diffuse appearance attributes on 3D models

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