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Viser: An Introduction to Parallel Programming
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An Introduction to Parallel Programming Vital Source e-bog
Peter Pacheco og Matthew Malensek
(2021)
Elsevier Science
521,00 kr.
468,90 kr.
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An Introduction to Parallel Programming
Peter Pacheco og Matthew Malensek
(2021)
Sprog: Engelsk
Elsevier Science & Technology
640,00 kr.
576,00 kr.
ikke på lager, Bestil nu og få den leveret
om ca. 10 hverdage
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Detaljer om varen
- 2. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: Elsevier Science (August 2021)
- Forfattere: Peter Pacheco og Matthew Malensek
- ISBN: 9780128046180
An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP.As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs while adding coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach students how to compile, run and modify example programs.
- Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples
- Explains how to develop parallel programs using MPI, Pthreads and OpenMP programming models
- A robust package of online ancillaries for instructors and students includes lecture slides, solutions manual, downloadable source code, and an image bank New to this edition:
- New chapters on GPU programming and heterogeneous programming
- New examples and exercises related to parallel algorithms
Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: -1 sider kan printes ad gangen
Copy: højest -1 sider i alt kan kopieres (copy/paste)
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: -1 sider kan printes ad gangen
Copy: højest -1 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Paperback: 450 sider
- Udgiver: Elsevier Science & Technology (November 2021)
- Forfattere: Peter Pacheco og Matthew Malensek
- ISBN: 9780128046050
An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP.
As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs.
In edition, this new edition includes coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach student how to compile, run and modify example programs.
- Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples
- Focuses on designing, debugging and evaluating the performance of distributed and shared-memory programs
- Explains how to develop parallel programs using MPI, Pthreads and OpenMP programming models
- Includes a robust package of online ancillaries for instructors and students
- Provides lecture slides, a solutions manual, downloadable source code and an image bank
1. Why parallel computing
2. Parallel hardware and parallel software
3. Distributed memory programming with MPI
4. Shared-memory programming with Pthreads
5. Shared-memory programming with OpenMP
6. GPU programming with CUDA
7. Parallel program development
8. Where to go from here
2. Parallel hardware and parallel software
3. Distributed memory programming with MPI
4. Shared-memory programming with Pthreads
5. Shared-memory programming with OpenMP
6. GPU programming with CUDA
7. Parallel program development
8. Where to go from here
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