A parallel-processing approach to computing for the geographic sciences; applications and systems enhancements

Michael Crane; Dan Steinwand; Tim Beckmann; Greg Krpan; Shu-Guang Liu; Erin Nichols; Jim Haga; Brian Maddox; Chris Bilderback; Mark Feller; George Homer

doi:10.3133/ofr01465

A parallel-processing approach to computing for the geographic sciences; applications and systems enhancements

Open-File Report 2001-465

By: Michael Crane, Dan Steinwand, Tim Beckmann, Greg Krpan, Shu-Guang Liu, Erin Nichols, Jim Haga, Brian Maddox, Chris Bilderback, Mark Feller, and George Homer

https://doi.org/10.3133/ofr01465

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Abstract

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost, personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting information science research into parallel computing systems and applications.

Additional publication details
Publication type	Report
Publication Subtype	USGS Numbered Series
Title	A parallel-processing approach to computing for the geographic sciences; applications and systems enhancements
Series title	Open-File Report
Series number	2001-465
DOI	10.3133/ofr01465
Year Published	2001
Language	English
Publisher	U.S. Geological Survey
Publisher location	Reston, VA
Contributing office(s)	Earth Resources Observation and Science (EROS) Center
Description	89 p.
Google Analytic Metrics	Metrics page