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Autor: Sushil K. Prasad
ISBN-13: 9783319931081
Einband: Book
Seiten: 438
Format: 235x155x mm
Sprache: Englisch

Topics in Parallel and Distributed Computing

Enhancing the undergraduate curriculum: performance, concurrency, and programming on modern platforms
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Erstverkaufstag: 01.08.2018
58,84 €*
Effectively translates guidelines into curriculumIntroduces the inclusion of Parallel and Distributed Computing (PDC) topics into undergraduate courses
Offers additional learning and exercises for students
Provides support and guidance to instructors with insights in pedagogical strategies, and practical descriptions for dealing with teaching materials
1 Introduction. 2 What do we need to know about parallel algorithms and their efficient implementation?.- 3 Modules for Teaching Parallel Performance Concepts.- 4 Scalability in Parallel Processing.- 5 Energy Efficiency Issues in Computing Systems.- 6 Scheduling for fault-tolerance.- 7 MapReduce for Beginners - The Clustered Data Processing Solution.- 8 The Realm of Graphical Processing Unit (GPU) Computing.- 9 Managing Concurrency in Mobile User Interfaces with Examples in Android.- 10 Parallel Programming for Interactive GUI Applications.- Scheduling in Parallel and Distributed Computing Systems.
This book introduces beginning undergraduate students of computing and computational disciplines to modern parallel and distributed programming languages and environments, including map-reduce, general-purpose graphics processing units (GPUs), and graphical user interfaces (GUI) for mobile applications. The book also guides instructors via selected essays on what and how to introduce parallel and distributed computing topics into the undergraduate curricula, including quality criteria for parallel algorithms and programs, scalability, parallel performance, fault tolerance, and energy efficiency analysis. The chapters designed for students serve as supplemental textual material for early computing core courses, which students can use for learning and exercises. The illustrations, examples, and sequences of smaller steps to build larger concepts are also tools that could be inserted into existing instructor material. The chapters intended for instructors are written at a teaching level and serve as a rigorous reference to include learning goals, advice on presentation and use of the material, within early and advanced undergraduate courses.
Editiert von: Sushil K. Prasad, Anshul Gupta, Arnold Rosenberg, Alan Sussman, Charles Weems
Anshul Gupta is a Principal Research Staff Member in IBM Research AI at IBM T.J. Watson Research Center. His research interests include sparse matrix computations and their applications in optimization and computational sci- ences, parallel algorithms, and graph/combinatorial algo- rithms for scientific computing. He has coauthored several journal articles and conference papers on these topics and a textbook titled "Introduction to Parallel Computing." He is the primary author of Watson Sparse Matrix Package (WSMP), one of the most robust and scalable parallel direct solvers for large sparse systems of linear equations.

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Autor: Sushil K. Prasad
ISBN-13:: 9783319931081
ISBN: 3319931083
Erscheinungsjahr: 01.08.2018
Verlag: Springer-Verlag GmbH
Seiten: 438
Sprache: Englisch
Sonstiges: Buch, 235x155x mm, Bibliographie