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ARTICLES

Using a Computational Grid for Geographic Information Analysis: A Reconnaissance

Pages 365-375 | Received 01 Oct 2003, Accepted 01 Aug 2004, Published online: 29 Feb 2008
 

Abstract

High performance computing has undergone a radical transformation during the past decade. Though monolithic supercomputers continue to be built with significantly increased computing power, geographically distributed computing resources are now routinely linked using high-speed networks to address a broad range of computationally complex problems. These confederated resources are referred to collectively as a computational Grid. Many geographical problems exhibit characteristics that make them candidates for this new model of computing. As an illustration, we describe a spatial statistics problem and demonstrate how it can be addressed using Grid computing strategies. A key element of this application is the development of middleware that handles domain decomposition and coordinates computational functions. We also discuss the development of Grid portals that are designed to help researchers and decision makers access and use geographic information analysis tools.

Notes

1A terabyte is a measure of computer storage capacity and is 240 bytes or approximately a thousand billion bytes (a thousand gigabytes). A petabyte is 250 bytes or, approximately a thousand terabytes.

Additional information

Notes on contributors

Marc P. Armstrong

A Professor

Mary Kathryn Cowles

An Associate Professor

Shaowen Wang

An Associate Research Scientist

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