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Exploring the DataFlow Supercomputing Paradigm [electronic resource] : Example Algorithms for Selected Applications / edited by Veljko Milutinovic, Milos Kotlar.

Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
Format/Description:
Book
1 online resource (X, 315 pages) : 212 illustrations, 101 illustrations in color.
Edition:
1st ed. 2019.
Series:
Computer Science (Springer-11645)
Computer communications and networks 1617-7975
Computer Communications and Networks, 1617-7975
Contained In:
Springer eBooks
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Subjects:
Computer networks.
Electrical engineering.
Big data.
Computers.
Computer input-output equipment.
Local subjects:
Computer Communication Networks. (search)
Communications Engineering, Networks. (search)
Big Data. (search)
Computation by Abstract Devices. (search)
Input/Output and Data Communications. (search)
System Details:
text file PDF
Summary:
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 Education, DataFlow 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.
Contents:
Part I: Theoretical Issues
A Method for Big-Graph Partitioning Using a Skeleton Graph
On Cloud-Supported Web-Based Integrated Development Environments for Programming DataFlow Architectures
Part II: Applications in Mathematics
Minimization and Maximization of Functions: Golden Section Search in One Dimension
Matrix-Based Algorithms for DataFlow Computer Architecture: An Overview and Comparison
Application of Maxeler DataFlow Supercomputing to Spherical Code Design
Part III: Applications in Image Understanding, Biomedicine, Physics Simulation, and Business
Face Recognition Using Maxeler DataFlow
Biomedical Image Processing Using Maxeler DataFlow Engines
An Overview of Selected DataFlow Applications in Physics Simulations
Bitcoin Mining Using Maxeler DataFlow Computers.
Contributor:
Milutinović, Veljko, editor., Editor,
Kotlar, Milos, editor., Editor,
SpringerLink (Online service)
Other format:
Printed edition:
Printed edition:
Printed edition:
ISBN:
978-3-030-13803-5
9783030138035
9783030138028 (Printed edition)
9783030138042 (Printed edition)
9783030138059 (Printed edition)
Publisher Number:
10.1007/978-3-030-13803-5 doi
Access Restriction:
Restricted for use by site license.