
Parallel MATLAB for Multicore and Multinode Computers
Jeremy Kepner(Author)
Society for Industrial & Applied Mathematics,U.S. (Publisher)
Will be published approx. on 30. July 2009
Book
Hardback
278 pages
978-0-89871-673-3 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 263 mm
Width: 184 mm
Thickness: 22 mm
Weight
687 gr
ISBN-13
978-0-89871-673-3 (9780898716733)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Jeremy Kepner is a senior technical staff member at MIT Lincoln Laboratory. His research focuses on the development of advanced libraries for the application of massively parallel computing to a variety of data intensive signal processing problems on which he has published many articles. Jeremy is most proud of the opportunity he has had to be the principal architect, principal investigator, or otherwise co-leader of several very talented teams. These teams have produced a number of innovative technologies that have broken new ground in parallel computing.
Content
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
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