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Data-intensive computing : architectures, algorithms, and applications / [edited by] Ian Gorton, Deborah K. Gracio.

Contributor(s): Material type: TextTextPublication details: Cambridge : Cambridge University Press, 2013.Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781139775625
  • 1139775626
  • 9780511844409
  • 0511844409
  • 9781139778664
  • 1139778668
  • 9781139781657
  • 1139781650
  • 1139793047
  • 9781139793049
  • 1316088677
  • 9781316088678
  • 1139783130
  • 9781139783132
  • 1139777149
  • 9781139777148
Subject(s): Genre/Form: Additional physical formats: Print version:: Data-intensive computing.DDC classification:
  • 004.5 23
LOC classification:
  • QA76.88 .D38 2013eb
Other classification:
  • COM021000
Online resources:
Contents:
Data-intensive computing : a challenge for the 21st century / Ian Gorton and Deborah K. Gracio -- Anatomy of data-intensive computing applications / Ian Gorton and Deborah K. Gracio -- Hardware architectures for data-intensive computing problems : a case study for string matching / Antonino Tumeo, Oreste Villa and Daniel Chavarría-Miranda -- Data management architectures / Terence Critchlow [and others] -- Large scale data management techniques in cloud computing platforms / Sherif Sakr and Anna Liu -- Dimension reduction for streaming data / Chandrika Kamath -- Binary classification with support vector machines / Patrick Nichols, Bobbie-Jo Webb-Robertson and Christopher Oehmen -- Beyond MapReduce : new requirements for scalable data processing / Bill Howe -- Let the data do the talking : hypothesis discovery from large-scale datasets in real time / Christopher Oehmen [and others] -- Data-intensive visual analysis for cybersecurity / William A. Pike [and others].
Summary: "A reference describing the general principles of the emerging field of data-intensive computing, along with methods for designing, managing and analyzing the big data sets of today"-- Provided by publisher.Summary: "A Challenge for the 21st Century Introduction In a world of rapid technological change such as the one we inhabit, it's occasionally instructive to contemplate how much things have changed in the last few years. For many, remembering life without the ability to view the World Wide Web (WWW) through the windows of a browser will be difficult (if not impossible for less 'mature' readers). And is it only seven years since YouTube, a Web site that is ingrained in so many facets of modern life, first came to life? How did we all really survive without FaceBook all those (actually, about 5) years ago? Various estimates put the amount of data stored by consumers and businesses around the world in 2010 in the vicinity of 13 exabytes, with a growth rate of 20--25% per annum. That's a lot of data. No wonder IBM is pursuing building a 120 petabyte storage array . There's obviously going to be a market for such devices in the future. As data volumes of all types, from video and photos to text documents and binary files for science, continue to grow in number and resolution, it's clear we have genuinely entered the realm of data intensive, or big data, computing."-- Provided by publisher.
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"A reference describing the general principles of the emerging field of data-intensive computing, along with methods for designing, managing and analyzing the big data sets of today"-- Provided by publisher.

"A Challenge for the 21st Century Introduction In a world of rapid technological change such as the one we inhabit, it's occasionally instructive to contemplate how much things have changed in the last few years. For many, remembering life without the ability to view the World Wide Web (WWW) through the windows of a browser will be difficult (if not impossible for less 'mature' readers). And is it only seven years since YouTube, a Web site that is ingrained in so many facets of modern life, first came to life? How did we all really survive without FaceBook all those (actually, about 5) years ago? Various estimates put the amount of data stored by consumers and businesses around the world in 2010 in the vicinity of 13 exabytes, with a growth rate of 20--25% per annum. That's a lot of data. No wonder IBM is pursuing building a 120 petabyte storage array . There's obviously going to be a market for such devices in the future. As data volumes of all types, from video and photos to text documents and binary files for science, continue to grow in number and resolution, it's clear we have genuinely entered the realm of data intensive, or big data, computing."-- Provided by publisher.

Includes bibliographical references and index.

Print version record.

Data-intensive computing : a challenge for the 21st century / Ian Gorton and Deborah K. Gracio -- Anatomy of data-intensive computing applications / Ian Gorton and Deborah K. Gracio -- Hardware architectures for data-intensive computing problems : a case study for string matching / Antonino Tumeo, Oreste Villa and Daniel Chavarría-Miranda -- Data management architectures / Terence Critchlow [and others] -- Large scale data management techniques in cloud computing platforms / Sherif Sakr and Anna Liu -- Dimension reduction for streaming data / Chandrika Kamath -- Binary classification with support vector machines / Patrick Nichols, Bobbie-Jo Webb-Robertson and Christopher Oehmen -- Beyond MapReduce : new requirements for scalable data processing / Bill Howe -- Let the data do the talking : hypothesis discovery from large-scale datasets in real time / Christopher Oehmen [and others] -- Data-intensive visual analysis for cybersecurity / William A. Pike [and others].

English.

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