Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Processing Large Remote Sensing Image Data Sets on Beowulf Clusters: Open-File Report 2003-216

Processing Large Remote Sensing Image Data Sets on Beowulf Clusters: Open-File Report 2003-216

Steinwand, Daniel R.
U. S. Department of the Interior, United
Et Al

Paperback

General Political Science

ISBN10: 1288745885
ISBN13: 9781288745883
Publisher: Bibliogov
Published: Feb 11 2013
Pages: 30
Weight: 0.16
Height: 0.06 Width: 7.44 Depth: 9.69
Language: English
High-performance computing is often concerned with the speed at which floating- point calculations can be performed. The architectures of many parallel computers and/or their network topologies are based on these investigations. Often, benchmarks resulting from these investigations are compiled with little regard to how a large dataset would move about in these systems. This part of the Beowulf study addresses that concern by looking at specific applications software and system-level modifications. Applications include an implementation of a smoothing filter for time-series data, a parallel implementation of the decision tree algorithm used in the Landcover Characterization project, a parallel Kriging algorithm used to fit point data collected in the field on invasive species to a regular grid, and modifications to the Beowulf project's resampling algorithm to handle larger, higher resolution datasets at a national scale. Systems-level investigations include a feasibility study on Flat Neighborhood Networks and modifications of that concept with Parallel File Systems.

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