Communications of the ACM - Special issue on parallelism
Applications of spatial data structures: Computer graphics, image processing, and GIS
Applications of spatial data structures: Computer graphics, image processing, and GIS
Parallel processing of spatial statistics
Computers & Geosciences
Using Linda to compute spatial autocorrelation in parallel
Computers & Geosciences
A parallel Kohonen algorithm for the classification of large spatial datasets
Computers & Geosciences - Special issue: neural network applications in the geosciences
Multidimensional access methods
ACM Computing Surveys (CSUR)
Massively parallel strategies for local spatial interpolation
Computers & Geosciences
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Maximum-Likelihood Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis of Multi-Dimensional Space-Filling Curves
Geoinformatica
A decoupled scheduling approach for Grid application development environments
Journal of Parallel and Distributed Computing - Special issue on computational grids
Sourcebook of parallel computing
Sourcebook of parallel computing
Parallel Computing - Special issue: High performance computing with geographical data
Parallel implementation of geometric shortest path algorithms
Parallel Computing - Special issue: High performance computing with geographical data
A quadtree approach to domain decomposition for spatial interpolation in grid computing environments
Parallel Computing - Special issue: High performance computing with geographical data
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Parallelizing MCMC for Bayesian spatiotemporal geostatistical models
Statistics and Computing
GISolve toolkit: advancing GIS through cyberinfrastructure
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
TeraGrid GIScience Gateway: Bridging cyberinfrastructure and GIScience
International Journal of Geographical Information Science - Distributed Geographic Information Processing Research
A MapReduce approach to Gi*(d) spatial statistic
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
A distributed resource broker for spatial middleware using adaptive space-filling curve
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
Parallel ordinary kriging interpolation incorporating automatic variogram fitting
Computers & Geosciences
Computers & Geosciences
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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 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.