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Distributed and parallel computing

Sharker, MH and Karimi, HA (2014) Distributed and parallel computing. UNSPECIFIED. ISBN 9781466586512

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Abstract

© 2014 by Taylor & Francis Group, LLC. Geoinformatics researchers and practitioners have been facing challenges of geospatial data processing ever since the debut of digital mapping, the predecessor term for today’s geospatial information systems. Over time, due to the advancement in data collection technologies (such as satellite imagery and GPS), challenges of geospatial data processing have become widespread. Today, every individual or organization that either routinely or sporadically must handle geospatial data has a better understanding and much appreciation for the complex nature of geospatial data processing. Of several characteristics of geospatial phenomena that make geospatial data to be complex for processing, data-intensive computing, one of the main characteristics of geospatial big data that can be addressed by employing special computing hardware and advanced computing techniques, is discussed in this chapter. To that end, since geospatial big data is defined and different approaches for addressing challenges of this emergent paradigm are discussed in all other chapters of this book, in this chapter high-performance computing (HPC), commonly considered as one main approach for handling data-intensive problems, is focused.


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Details

Item Type: Book
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Sharker, MH
Karimi, HAhkarimi@pitt.eduHKARIMI0000-0001-5331-5004
Date: 1 January 2014
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
DOI or Unique Handle: 10.1201/b16524
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781466586512
Related URLs:
Date Deposited: 30 Jun 2014 17:53
Last Modified: 15 Apr 2020 13:55
URI: http://d-scholarship.pitt.edu/id/eprint/22048

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