DataFlow supercomputing essentials : algorithms, applications and implementations / Veljko Milutinovic, Milos Kotlar, Marko Stojanovic, Igor Dundic, Nemanja Trifunovic, Zoran Babovic.
Milutinović, Veljko, author.; Kotlar, Milos, author.; Stojanovic, Marko, author.; Dundic, Igor, author.; Trifunovic, Nemanja, author.; Babovic, Zoran, author.
2017
QA76.9.D338
Available Online

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Title DataFlow supercomputing essentials : algorithms, applications and implementations / Veljko Milutinovic, Milos Kotlar, Marko Stojanovic, Igor Dundic, Nemanja Trifunovic, Zoran Babovic.
ISBN 9783319661254 (electronic book)
3319661256 (electronic book)
9783319661247
3319661248
Published Cham, Switzerland : Springer, 2017.
Language English
Description 1 online resource.
Call Number QA76.9.D338
Dewey Decimal Classification 004
Summary This illuminating text/reference reviews the fundamentals of programming for effective DataFlow computing. The DataFlow paradigm enables considerable increases in speed and reductions in power consumption for supercomputing processes, yet the programming model requires a distinctly different approach. The algorithms and examples showcased in this book will help the reader to develop their understanding of the advantages and unique features of this methodology. This work serves as a companion title to DataFlow Supercomputing Essentials: Research, Development and Education, which analyzes the latest research in this area, and the training resources available. Topics and features: Presents an implementation of Neural Networks using the DataFlow paradigm, as an alternative to the traditional ControlFlow approach Discusses a solution to the three-dimensional Poisson equation, using the Fourier method and DataFlow technology Examines how the performance of the Binary Search algorithm can be improved through implementation on a DataFlow architecture Reviews the different way of thinking required to best configure the DataFlow engines for the processing of data in space flowing through the devices Highlights how the DataFlow approach can efficiently support applications in big data analytics, deep learning, and the Internet of Things This indispensable volume will benefit all researchers interested in supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be an invaluable resource.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (viewed December 21, 2017).
Added Author Milutinović, Veljko, author.
Kotlar, Milos, author.
Stojanovic, Marko, author.
Dundic, Igor, author.
Trifunovic, Nemanja, author.
Babovic, Zoran, author.
Series Computer communications and networks.
Available in Other Form Print version: 9783319661247
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Part I: Algorithms
Implementing Neural Networks by Using the DataFlow Paradigm
Part II: Applications
Solving the Poisson Equation by Using Dataflow Technology
Binary Search in the DataFlow Paradigm
Part III: Implementations
Introductory Overview on Implementation Tools
DataFlow Systems: From Their Origins to Future Applications in Data Analytics, Deep Learning, and the Internet of Things.

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