Exploring the Dataflow Supercomputing Paradigm: Example Algorithms for Selected Applications

Name: Exploring the Dataflow Supercomputing Paradigm: Example Algorithms for Selected Applications
Brand: Springer
SKU: 9783030138059
Price: 20764 HUF
Availability: InStock

Szerző: Veljko Milutinovic, Milos Kotlar

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Kötés: Puha kötésű

Kiadó: Springer

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This useful text/reference describes the implementation of a varied selection of algorithms in the D...

Információk a könyvről

Szerző

Veljko Milutinovic, Milos Kotlar

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2020

oldal

315

EAN

9783030138059

ISBN

3030138054

Enbook ID

37627096

Kiadó

Springer

Súly

568

Méretek

155 x 235 x 17

Teljes leírás

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.

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Exploring the Dataflow Supercomputing Paradigm: Example Algorithms for Selected Applications

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