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Algorithm Engineering Bridging Gap (5 results)
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Algorithm Engineering: Bridging the Gap Between Algorithm Theory and Practice (Lecture Notes in Computer Science, 5971)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
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Taschenbuch. Condition: Neu. Algorithm Engineering | Bridging the Gap Between Algorithm Theory and Practice | Matthias Müller-Hannemann (u. a.) | Taschenbuch | xvi | Englisch | 2010 | Springer | EAN 9783642148651 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Algorithm Engineering: Bridging the Gap Between Algorithm Theory and Practice
Language: English
Published by Springer-Verlag New York Inc, 2010
ISBN 10: 3642148654 ISBN 13: 9783642148651
Paperback. Condition: Brand New. 513 pages. 9.13x6.06x1.10 inches. In Stock.
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Algorithm Engineering : Bridging the Gap Between Algorithm Theory and Practice
Language: English
Published by Springer, Berlin, Springer, 2010
ISBN 10: 3642148654 ISBN 13: 9783642148651
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to arising gap between classical algorithm theory and algorithmics in practice.The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments.This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects andalgorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.
