Parallel Computing for Geocomputational Modeling

In the past decade, the emergence of cyberinfrastructure has rendered high-performance computing resources and parallel technologies increasingly open to domain-specific science discovery. The capability of these high-performance computing resources and associated parallel technologies has greatly stimulated researchers to utilize them for domain-specific problem-solving that requires considerable computational support. The objective of this paper is to investigate in detail the utility of parallel computing in geocomputational modeling. We discuss fundamentals in parallel computing and relevant technologies. To best leverage diverse high-performance computing resources often requires well-crafted parallel computing strategies or algorithms. We review the use of parallel computing for geocomputational modeling by focusing on four aspects: spatial statistics, spatial optimization, spatial simulation, and cartography and geovisualization. We design a case study of a spatial agent-based model to show how parallel computing can be exploited to empower advanced geocomputational modeling. Results demonstrate that the evolving parallel computing provides solid support for computationally intensive geocomputational modeling.

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