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Data-Intensive Computing : Architectures, Algorithms, and Applications - Ian Gorton

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Data-Intensive Computing

Architectures, Algorithms, and Applications

By: Ian Gorton (Editor), Deborah K. Gracio (Editor)

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Hardcover | 29 October 2012

At a Glance

Hardcover
300 Pages

Dimensions(cm)
23.6 x 15.3 x 2.1

Hardcover

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The world is awash with digital data from social networks, blogs, business, science, and engineering. Data-intensive computing facilitates understanding of complex problems that must process massive amounts of data. Through the development of new classes of software, algorithms, and hardware, data-intensive applications can provide timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements. This emerging area brings many challenges that are different from traditional high-performance computing. This reference for computing professionals and researchers describes the dimensions of the field, the key challenges, the state of the art, and the characteristics of likely approaches that future data-intensive problems will require. Chapters cover general principles and methods for designing such systems and for managing and analyzing the big data sets of today that live in the cloud, and describe example applications in bioinformatics and cybersecurity that illustrate these principles in practice.

Industry Reviews

"Overall, I recommend this book for researchers and advanced graduate students. The collection presents different essays for a very rich and diversified overview of one of the most recent and fast-paced revolutions in computer science." Radu State, Computing Reviews

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You Can Find This Book In

Non-Fiction Science Science in General Computing & I.T.Databases

Data-intensive computing: a challenge for the twenty-first century
The anatomy of data-intensive computing applications Ian Gorton
Hardware architectures for data-intensive computing problems: a case study for string matching Antonino Tumeo
Data management architectures Terence Critchlow
Large-scale data management techniques in cloud computing platforms
Dimension reduction for streaming data
Binary classification with support vector machines
Beyond MapReduce: new requirements for scalable data processing
Letting the data do the talking: hypothesis discovery from large-scale data sets in real time Christopher Oehmen
Data-intensive visual analysis for cybersecurity
Table of Contents provided by Publisher. All Rights Reserved.

Data-Intensive Computing

Architectures, Algorithms, and Applications

At a Glance

Hardcover

Industry Reviews

Shipping

How to return your order

Defective items

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