Programming Massively Parallel Processors: A Hands-on Approach 5th Edition
Author(s): Wen-mei W. Hwu (Author), David B. Kirk (Author), Izzat El Hajj (Author)
Publisher: Morgan Kaufmann
Publication Date: 6 Jun. 2026
Edition: 5th
Language: English
Print length: 680 pages
ISBN-10: 0443439001
ISBN-13: 9780443439001
Book Description
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.
Expanded optimization checklist with a more comprehensive demonstration of essential optimizations across patterns
New pattern and application chapters including: filtering, wavefront parallelism, advanced optimizations for matrix multiplication, and large language models (LLMs)
More coverage of important CUDA features including warp-level programming, cooperative groups, CUDA C++ atomics, and multi-GPU programming with NCCL and NVSHMEM
Editorial Reviews
Review
Learn how to program massively parallel processors with the new edition of the best-selling guide to CUDA and GPU parallel programming
From the Back Cover
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.
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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