Exploring the DataFlow Supercomputing Paradigm

Example Algorithms for Selected Applications

Nonfiction, Computers, Networking & Communications, Hardware, Science & Nature, Technology, Telecommunications, General Computing
Cover of the book Exploring the DataFlow Supercomputing Paradigm by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783030138035
Publisher: Springer International Publishing Publication: May 27, 2019
Imprint: Springer Language: English
Author:
ISBN: 9783030138035
Publisher: Springer International Publishing
Publication: May 27, 2019
Imprint: Springer
Language: English

This useful text/reference describes the implementation of a varied selection of algorithms in the DataFlow paradigm, highlighting the exciting potential of DataFlow computing for applications in such areas as image understanding, biomedicine, physics simulation, and business.

The mapping of additional algorithms onto the DataFlow architecture is also covered in the following Springer titles from the same team: DataFlow Supercomputing Essentials: Research, Development and EducationDataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, and Guide to DataFlow Supercomputing.

Topics and Features: introduces a novel method of graph partitioning for large graphs involving the construction of a skeleton graph; describes a cloud-supported web-based integrated development environment that can develop and run programs without DataFlow hardware owned by the user; showcases a new approach for the calculation of the extrema of functions in one dimension, by implementing the Golden Section Search algorithm; reviews algorithms for a DataFlow architecture that uses matrices and vectors as the underlying data structure; presents an algorithm for spherical code design, based on the variable repulsion force method; discusses the implementation of a face recognition application, using the DataFlow paradigm; proposes a method for region of interest-based image segmentation of mammogram images on high-performance reconfigurable DataFlow computers; surveys a diverse range of DataFlow applications in physics simulations, and investigates a DataFlow implementation of a Bitcoin mining algorithm.

This unique volume will prove a valuable reference for researchers and programmers of DataFlow computing, and supercomputing in general. Graduate and advanced undergraduate students will also find that the book serves as an ideal supplementary text for courses on Data Mining, Microprocessor Systems, and VLSI Systems.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This useful text/reference describes the implementation of a varied selection of algorithms in the DataFlow paradigm, highlighting the exciting potential of DataFlow computing for applications in such areas as image understanding, biomedicine, physics simulation, and business.

The mapping of additional algorithms onto the DataFlow architecture is also covered in the following Springer titles from the same team: DataFlow Supercomputing Essentials: Research, Development and EducationDataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, and Guide to DataFlow Supercomputing.

Topics and Features: introduces a novel method of graph partitioning for large graphs involving the construction of a skeleton graph; describes a cloud-supported web-based integrated development environment that can develop and run programs without DataFlow hardware owned by the user; showcases a new approach for the calculation of the extrema of functions in one dimension, by implementing the Golden Section Search algorithm; reviews algorithms for a DataFlow architecture that uses matrices and vectors as the underlying data structure; presents an algorithm for spherical code design, based on the variable repulsion force method; discusses the implementation of a face recognition application, using the DataFlow paradigm; proposes a method for region of interest-based image segmentation of mammogram images on high-performance reconfigurable DataFlow computers; surveys a diverse range of DataFlow applications in physics simulations, and investigates a DataFlow implementation of a Bitcoin mining algorithm.

This unique volume will prove a valuable reference for researchers and programmers of DataFlow computing, and supercomputing in general. Graduate and advanced undergraduate students will also find that the book serves as an ideal supplementary text for courses on Data Mining, Microprocessor Systems, and VLSI Systems.

More books from Springer International Publishing

Cover of the book Corporate Financial Distress by
Cover of the book Dynamics Of Mediatization by
Cover of the book Fractional Derivatives with Mittag-Leffler Kernel by
Cover of the book Advances in Affective and Pleasurable Design by
Cover of the book Reframing Blackness and Black Solidarities through Anti-colonial and Decolonial Prisms by
Cover of the book Nordic-Iberian Cod Value Chains by
Cover of the book Social Ties in Online Networking by
Cover of the book Inflation Dynamics in South Africa by
Cover of the book Emerging Contaminants in River Ecosystems by
Cover of the book Exploring Spoken English Learner Language Using Corpora by
Cover of the book Geography of Small Islands by
Cover of the book Model-Driven Engineering and Software Development by
Cover of the book Hybrid Intelligent Systems by
Cover of the book Imaging of Male Breast Cancer by
Cover of the book Symbol Correspondences for Spin Systems by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy