Programming Massively Parallel Processors
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Programming Massively Parallel Processors: A Hands-on Approach

Programming Massively Parallel Processors: A Hands-on Approach


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About the Book

Programming Massively Parallel Processors: A Hands-on Approach, Fifth Edition 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 courses. Various techniques for constructing and optimizing parallel programs are explored in detail, while case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This new edition has been updated with an expanded repertoire of optimizations, new patterns and applications, ad more coverage of important CUDA features.

Table of Contents:
1. Introduction Part I. Fundamental Concepts 2. Heterogeneous data parallel computing 3. Multidimensional grids and data 4. Compute architecture and scheduling 5. Memory architecture and data locality 6. Performance considerations Part II. Parallel Patterns 7. Convolution 8. Stencil 9. Parallel histogram 10. Reduction 11. Prefix sum (scan) 12. Merge Part III. Advanced Patterns and Applications 13. Sorting 14. Filtering (new) 15. Sparse matrix computation 16. Wavefront Algorithms (new) 17. Graph traversal 18. Deep learning 19. Multi-GPU API (new) 20. Electrostatic potential map 21. Parallel programming and computational thinking Part IV. Advanced Practices 22. Programming a heterogeneous computing cluster 23. Advanced Optimizations for Matrix Multiplication (new) 24. Advanced practices and future evolution 25. Conclusion and outlook

About the Author :
Wen-mei W. Hwu is a Senior Director of Research of NVIDIA and the Sanders-AMD Endowed Chair Professor Emeritus of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His work focuses on parallel computing—covering architecture, implementation, compilers, and algorithms. Dr. Hwu has received numerous honors, including the ACM/ IEEE Eckert-Mauchly Award, ACM Grace Murray Hopper Award, IEEE B.R. Rau Award. He is an IEEE and ACM Fellow. He earned his Ph.D. in Computer Science from UC Berkele David B. Kirk is known for major contributions to graphics, hardware, and algorithms. Before pursuing his Ph.D. at Caltech, he earned B.S. and M.S. degrees in mechanical engineering from MIT and worked at Raster Technologies and Hewlett-Packard’s Apollo Systems Division. After completing his doctorate, he served as chief scientist and head of technology at Crystal Dynamics. In 1997, he became Chief Scientist at NVIDIA. Dr. Kirk has received numerous honors including the IEEE Seymour Cray Computer Engineering Award and ACM SIGGRAPH Computer Graphics Achievement Award. He is a member of the U.S. National Academy of Engineering. Izzat El Hajj is an Assistant Professor of Computer Science at the American University of Beirut. His research focuses on leveraging accelerator architectures to tackle challenging computations, with a focus on GPU computing, processing-in-memory, and performance modeling. He earned his Ph.D. in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He has received the Dan Vivoli Endowed Fellowship (UIUC) and the Distinguished Graduate Award from the American University of Beirut.


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Product Details
  • ISBN-13: 9780443439001
  • Publisher: Elsevier Science & Technology
  • Publisher Imprint: Morgan Kaufmann Publishers In
  • Height: 235 mm
  • No of Pages: 680
  • Weight: 450 gr
  • ISBN-10: 0443439001
  • Publisher Date: 19 Jun 2026
  • Binding: Paperback
  • Language: English
  • Sub Title: A Hands-on Approach
  • Width: 191 mm


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