Produktbild: Exploring the DataFlow Supercomputing Paradigm

Exploring the DataFlow Supercomputing Paradigm Example Algorithms for Selected Applications

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.08.2020

Abbildungen

X, 315 p. 212 illus., 101 illus. in color.

Herausgeber

Veljko Milutinovic + weitere

Verlag

Springer

Seitenzahl

315

Maße (L/B/H)

23,5/15,5/1,7 cm

Gewicht

568 g

Auflage

20001 Auflage 1st edition 2019

Sprache

Englisch

ISBN

978-3-030-13805-9

Beschreibung

Portrait


Dr. Veljko Milutinovic
teaches DataFlow supercomputing in the School of Informatics, Computing, and Engineering at Indiana University, Bloomington, IN, USA, and previously served for about a decade on the faculty of Purdue University in West Lafayette, IN, USA. He is a co-designer of DARPA’s first GaAs RISC microprocessor on 200MHz and a co-designer of the DARPA’s 4096-processor systolic array. He is a Life Fellow of the IEEE and a Life Member the ACM. He is a Member of The Academy of Europe, a Member of the Serbian National Academy of Engineering, and a Foreign Member of the Montenegrin Academy of Sciences and Arts. He serves as a Senior Advisor to Maxeler Technologies in London, UK.





Mr. Milos Kotlar
is a Software Engineer at the Swiss-Swedish company ABB (ASEA Brown Boveri) of Zurich, Switzerland and a Ph.D. student at the School of Electrical Engineering at the University of Belgrade, Serbia. He serves as a TA for DataFlow supercomputing courses and as an RA for DataFlow supercomputing research in the domain of tensor calculus.



Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.08.2020

Abbildungen

X, 315 p. 212 illus., 101 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

315

Maße (L/B/H)

23,5/15,5/1,7 cm

Gewicht

568 g

Auflage

20001 Auflage 1st edition 2019

Sprache

Englisch

ISBN

978-3-030-13805-9

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Exploring the DataFlow Supercomputing Paradigm

  • 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.