Programming massively parallel processors : a hands-on approach /

"Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel computing course...

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Bibliographic Details
Main Authors:	Hwu, Wen-mei (Author), Kirk, David, 1960- (Author), El Hajj, Izzat (Author)
Corporate Author:	ScienceDirect (Online service)
Format:	eBook
Language:	English
Published:	Cambridge, MA : Morgan Kaufmann, an imprint of Elsevier, [2022]
Edition:	Fourth edition /
Subjects:	Multiprocessors. Parallel processing (Electronic computers) Parallel programming (Computer science) Computer architecture. Multiprocesseurs. Parallélisme (Informatique) Programmation parallèle (Informatique) Ordinateurs > Architecture. Multiprocessors Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Chapter 1. Introduction
Part I: Fundamental Concepts
Chapter 2. Heterogeneous data parallel computing
Chapter 3. Multidimensional grids and data
Chapter 4. Compute architecture and scheduling
Chapter 5. Memory architecture and data locality
Chapter 6. Performance considerations
Part II: Parallel Patterns
Chapter 7. Convolution: An introduction to constant memory and caching
Chapter 8. Stencil
Chapter 9. Parallel histogram: An introduction to atomic operations and privatization
Chapter 10. Reduction: And minimizing divergence
Chapter 11. Prefix sum (scan): An introduction to work efficiency in parallel algorithms
Chapter 12. Merge: An introduction to dynamic input data identification
Part III: Advanced Patterns and Applications
Chapter 13. Sorting
Chapter 14. Sparse matrix computation
Chapter 15. Graph traversal
Chapter 16. Deep learning
Chapter 17. Iterative magnetic resonance imaging reconstruction
Chapter 18. Electrostatic potential map
Chapter 19. Parallel programming and computational thinking
Chapter 20. Programming a heterogeneous computing cluster: An introduction to CUDA streams
Chapter 21. CUDA dynamic parallelism
Chapter 22. Advanced practices and future evolution
Chapter 23. Conclusion and outlook.