DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations (Computer Communications and Networks) - Hardcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About this title" may belong to another edition of this title.
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DataFlow Supercomputing Essentials. Algorithms, Applications and Implementations.
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DataFlow Supercomputing Essentials
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ISBN 10: 3319661248
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 toDataFlow 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. 164 pp. Englisch. Seller Inventory # 9783319661247
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DataFlow Supercomputing Essentials
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Reviews the advantages of the DataFlow paradigm for supercomputingIntroduces the DataFlow programming model Provides a selection of algorithm examples that illuminate the DataFlow paradigmThis illuminating text/reference revi. Seller Inventory # 155784500
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DataFlow Supercomputing Essentials
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Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 164 pp. Englisch. Seller Inventory # 9783319661247
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DataFlow Supercomputing Essentials : Algorithms, Applications and Implementations
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 toDataFlow 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. Seller Inventory # 9783319661247
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DataFlow Supercomputing Essentials | Algorithms, Applications and Implementations
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Buch. Condition: Neu. DataFlow Supercomputing Essentials | Algorithms, Applications and Implementations | Veljko Milutinovic (u. a.) | Buch | xi | Englisch | 2017 | Springer International Publishing | EAN 9783319661247 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 110988986
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