Guide to DataFlow Supercomputing Basic Concepts, Case Studies, and a
This unique text/reference describes an exciting and novel approach to supercomputing in the DataFlow paradigm. The major advantages and applications of this approach are clearly described, and a detailed explanation of the programming model is provided u
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Veljko Milutinović Jakob Salom Nemanja Trifunovic Roberto Giorgi
Guide to DataFlow Supercomputing Basic Concepts, Case Studies, and a Detailed Example
Computer Communications and Networks Series editor A.J. Sammes Centre for Forensic Computing Cranfield University, Shrivenham campus Swindon, UK
The Computer Communications and Networks series is a range of textbooks, monographs and handbooks. It sets out to provide students, researchers, and nonspecialists alike with a sure grounding in current knowledge, together with comprehensible access to the latest developments in computer communications and networking. Emphasis is placed on clear and explanatory styles that support a tutorial approach, so that even the most complex of topics is presented in a lucid and intelligible manner.
More information about this series at http://www.springer.com/series/4198
Veljko Milutinovi´c • Jakob Salom Nemanja Trifunovic • Roberto Giorgi
Guide to DataFlow Supercomputing Basic Concepts, Case Studies, and a Detailed Example
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Veljko Milutinovi´c School of Electrical Engineering University of Belgrade Serbia Nemanja Trifunovic Maxeler Technologies Inc. Palo Alto, CA, USA
Jakob Salom MISANU Belgrade, Serbia Roberto Giorgi University of Siena Italy
ISSN 1617-7975 ISSN 2197-8433 (electronic) Computer Communications and Networks ISBN 978-3-319-16228-7 ISBN 978-3-319-16229-4 (eBook) DOI 10.1007/978-3-319-16229-4 Library of Congress Control Number: 2015939052 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www. springer.com)
Preface
This book is meant to support teaching of the DataFlow subject. University courses fully or partially dedicated to the DataFlow subject are important for the following reason: More and more Big Data are present in all kinds of researc
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