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Parallel MATLAB for multicore and multinode computers



Autor: Kepner, Jeremy V.
Rok: c2009
ISBN: 9780898716733
OCLC Number: (OCoLC)317574167
OKCZID: 110623196

Citace (dle ČSN ISO 690):
KEPNER, Jeremy V. Parallel MATLAB for multicore and multinode computers. Philadelphia: Society for Industrial and Applied Mathematics, c2009. xxv, 253 s. Software, environments, tools.


Anotace

 

This is the first book on parallel MATLAB and the first parallel computing book focused on the design, code, debug, and test techniques required to quickly produce well-performing parallel programs. MATLAB is currently the dominant language of technical computing with one million users worldwide, many of whom can benefit from the increased power offered by inexpensive multicore and multinode parallel computers. MATLAB is an ideal environment for learning about parallel computing, allowing the user to focus on parallel algorithms instead of the details of implementation. Parallel MATLAB for Multicore and Multinode Computers covers more parallel algorithms and parallel programming models than any other parallel programming book due to the succinctness of MATLAB. It presents a hands-on approach with numerous example programs; wherever possible, the examples are drawn from widely known and well-documented parallel benchmark codes that are representative of many real applications across the field of technical computing. Audience: Intended for professional scientists and engineers, as well as undergraduate or graduate students, who use MATLAB. It is suitable as either the primary book in a parallel computing class or as a supplementary text in a numerical computing class or a computer science algorithms class. Contents: List of Figures; List of Tables; List of Algorithms; Preface; Acknowledgments; Part I: Fundamentals: Chapter 1: Primer: Notation and Interfaces; Chapter 2: Introduction to pMatlab; Chapter 3: Interacting with Distributed Arrays; Part II: Advanced Techniques: Chapter 4: Parallel Programming Models; Chapter 5: Advanced Distributed Array Programming; Chapter 6: Performance Metrics and Software Architecture; Part III: Case Studies: Chapter 7: Parallel Application Analysis; Chapter 8: Stream; Chapter 9: RandomAccess; Chapter 10: Fast Fourier Transform; Chapter 11: High Performance Linpack; Appendix: Notation for Hierarchical Parallel Multicore Algorithms; Index


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