LogGP: incorporating long messages into the LogP model for parallel computation
Journal of Parallel and Distributed Computing
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Parallel Computing - Special issue on cellular automata: from modeling to applications
OpenMP: An Industry-Standard API for Shared-Memory Programming
IEEE Computational Science & Engineering
GPFS: A Shared-Disk File System for Large Computing Clusters
FAST '02 Proceedings of the Conference on File and Storage Technologies
Data partitioning and load balancing in parallel disk systems
The VLDB Journal — The International Journal on Very Large Data Bases
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Guest editorial: high performance computing with geographical data
Parallel Computing - Special issue: High performance computing with geographical data
Geocomputation's future at the extremes: high performance computing and nanoclients
Parallel Computing - Special issue: High performance computing with geographical data
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Parallel algorithms for geographic processing
Parallel algorithms for geographic processing
International Journal of Geographical Information Science
Parallel cellular automata for large-scale urban simulation using load-balancing techniques
International Journal of Geographical Information Science
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Solving traditional spatial analysis problems benefits from high performance geo-computation powered by parallel computing. Digital Terrain Analysis (DTA) is a typical example of data and computationally intensive spatial analysis problems and can be improved by parallelization technologies. Previous work on this topic has mainly focused on applying optimization schemes for specific DTA case studies. The task addressed in this paper, in contrast, is to find optimization methods that are generally applicable to the parallelization of DTA. By modeling a complex DTA problem with Cellular Automata (CA), we developed a temporal model that can describe the time cost of the solution. Three methods for optimizing different components in the temporal model are proposed: (1) a parallel loading/writing method that can improve the IO efficiency; (2) a best cell division method that can minimize the communication time among processes; and (3) a communication evolution overlapping method that can reduce the total time of evolutions and communications. The feasibilities and practical efficiencies of the proposed methods have been verified by comparative experiments conducted on an elevation dataset from North America using the Slope of Aspect (SOA) as an example of a general DTA problem. The results showed that the parallel performance of the SOA can be improved by applying the proposed methods individually or in an integrated fashion.