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Introduction to Parallel Computing: From Algorithms to Programming on State-of-the-Art Platforms: Undergraduate Topics in Computer Science

Autor Roman Trobec, Boštjan Slivnik, Patricio Bulić, Borut Robič
en Limba Engleză Paperback – 9 oct 2018
Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms.
This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters.

Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs’ run-times, and by engineering analysis of obtained results for improved parallel execution performances.
Many examples and exercises support the exposition.
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Specificații

ISBN-13: 9783319988320
ISBN-10: 3319988328
Pagini: 260
Ilustrații: XII, 256 p. 86 illus., 7 illus. in color.
Dimensiuni: 155 x 235 x 31 mm
Greutate: 0.45 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Undergraduate Topics in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Part I: Foundations.- Why Do We Need Parallel Programming.- Overview of Parallel Systems.- Part II: Programming.- Programming Multi-Core and Shared Memory Multiprocessors Using OpenMP.- MPI Processes and Messaging.- OpenCL for Massively Parallel Graphic Processors.- Part III: Engineering.- Engineering: Parallel Computation of the Number π.- Engineering: Parallel Solution of 1-D Heat Equation.- Engineering: Parallel Implementation of Seam Carving.- Final Remarks and Perspectives.- Appendix A: Hints for Making Your Computer a Parallel Machine.

Notă biografică

Roman Trobec is Head of the Parallel and Distributed Computing Laboratory at the Jožef Stefan Institute, Ljubljana, Slovenia, and an Associate Professor in the Faculty of Computer and Information Science at the University of Ljubljana. Boštjan Slivnik is an Assistant Professor in the Faculty of Computer and Information Science at the University of Ljubljana. Patricio Bulić is an Associate Professor, and Borut Robič is a Full Professor, at the same institution. Other Springer titles by the same authors include The Foundations of Computability TheoryApplication and Multidisciplinary Aspects of Wireless Sensor Networks: Concepts, Integration, and Case Studies, and Parallel Computing: Numerics, Applications, and Trends.

Textul de pe ultima copertă

Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms.
This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters.

Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs’ run-times, and by engineering analysis of obtained results for improved parallel execution performances.
Many examples and exercises support the exposition.

Caracteristici

Introduces the foundations and state of the art of parallel computing Suitable for a 15-week course for advanced undergraduate studies, and featuring exercises Covers the key aspects of parallel computing: parallel, distributed and embedded multicore computing, computer clusters, and GPU computing