Scalable Parallel Computing

Scalable Parallel Computing
Author: Kai Hwang
Publisher: McGraw-Hill Science, Engineering & Mathematics
Total Pages: 840
Release: 1998
Genre: Computers
ISBN:


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This book covers four areas of parallel computing: principles, technology, architecture, and programming. It is suitable for professionals and undergraduates taking courses in computer engineering, parallel processing, computer architecture, scaleable computers or distributed computing.


Scalable Parallel Computing
Language: en
Pages: 840
Authors: Kai Hwang
Categories: Computers
Type: BOOK - Published: 1998 - Publisher: McGraw-Hill Science, Engineering & Mathematics

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This book covers four areas of parallel computing: principles, technology, architecture, and programming. It is suitable for professionals and undergraduates ta
Scaling Up Machine Learning
Language: en
Pages: 493
Authors: Ron Bekkerman
Categories: Computers
Type: BOOK - Published: 2012 - Publisher: Cambridge University Press

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This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.
Handbook of Research on Scalable Computing Technologies
Language: en
Pages: 1086
Authors: Li, Kuan-Ching
Categories: Computers
Type: BOOK - Published: 2009-07-31 - Publisher: IGI Global

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"This book presents, discusses, shares ideas, results and experiences on the recent important advances and future challenges on enabling technologies for achiev
Structured Parallel Programming
Language: en
Pages: 434
Authors: Michael McCool
Categories: Computers
Type: BOOK - Published: 2012-06-25 - Publisher: Elsevier

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Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured prog
Scalable Parallel Programming Applied to H.264/AVC Decoding
Language: en
Pages: 112
Authors: Ben Juurlink
Categories: Technology & Engineering
Type: BOOK - Published: 2012-06-01 - Publisher: Springer Science & Business Media

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Existing software applications should be redesigned if programmers want to benefit from the performance offered by multi- and many-core architectures. Performan