Programming Massively Parallel Processors: A Hands-on Approach 4th Edition
Author(s): Wen-mei W. Hwu (Author), David B. Kirk (Author), Izzat El Hajj (Author)
Publisher: Morgan Kaufmann
Publication Date: 27 Sept. 2022
Edition: 4th
Language: English
Print length: 580 pages
ISBN-10: 0323912311
ISBN-13: 9780323912310
Book Description
Programming Massively Parallel Processors: A Hands-on Approach 4th 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. The new edition includes updated coverage of CUDA, including the newer libraries such as CuDNN. New chapters on frequently used parallel patterns have been added, and case studies have been updated to reflect current industry practices.
Parallel Patterns Introduces new chapters on frequently used parallel patterns (stencil, reduction, sorting) and major improvements to previous chapters (convolution, histogram, sparse matrices, graph traversal, deep learning)
Ampere Includes a new chapter focused on GPU architecture and draws examples from recent architecture generations, including Ampere
Systematic Approach Incorporates major improvements to abstract discussions of problem decomposition strategies and performance considerations, with a new optimization checklist
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 4th Edition 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.
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.
Wow! eBook
