Includes bibliographical references and index.

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.

Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. For this new edition, the authors are updating their coverage of CUDA, including the concept of unified memory, and expanding content in areas such as threads, while still retaining its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses.-- Source other than the Library of Congess.