Programming Massively Parallel Processors: A Hands-on Approach
580Programming Massively Parallel Processors: A Hands-on Approach
580Paperback(4th ed.)
-
PICK UP IN STORECheck Availability at Nearby Stores
Available within 2 business hours
Related collections and offers
Overview
Product Details
ISBN-13: | 9780323912310 |
---|---|
Publisher: | Elsevier Science |
Publication date: | 08/04/2022 |
Edition description: | 4th ed. |
Pages: | 580 |
Sales rank: | 572,652 |
Product dimensions: | 7.50(w) x 9.25(h) x (d) |
About the Author
David B. Kirk is well recognized for his contributions to graphics hardware and algorithm research. By the time he began his studies at Caltech, he had already earned B.S. and M.S. degrees in mechanical engineering from MIT and worked as an engineer for Raster Technologies and Hewlett-Packard's Apollo Systems Division, and after receiving his doctorate, he joined Crystal Dynamics, a video-game manufacturing company, as chief scientist and head of technology. In 1997, he took the position of Chief Scientist at NVIDIA, a leader in visual computing technologies, and he is currently an NVIDIA Fellow.
At NVIDIA, Kirk led graphics-technology development for some of today's most popular consumer-entertainment platforms, playing a key role in providing mass-market graphics capabilities previously available only on workstations costing hundreds of thousands of dollars. For his role in bringing high-performance graphics to personal computers, Kirk received the 2002 Computer Graphics Achievement Award from the Association for Computing Machinery and the Special Interest Group on Graphics and Interactive Technology (ACM SIGGRAPH) and, in 2006, was elected to the National Academy of Engineering, one of the highest professional distinctions for engineers.
Kirk holds 50 patents and patent applications relating to graphics design and has published more than 50 articles on graphics technology, won several best-paper awards, and edited the book Graphics Gems III. A technological "evangelist" who cares deeply about education, he has supported new curriculum initiatives at Caltech and has been a frequent university lecturer and conference keynote speaker worldwide.
Izzat El Hajj is an Assistant Professor in the Department of Computer Science at the American University of Beirut. His research interests are in application acceleration and programming support for emerging parallel processors and memory technologies, with a particular interest in GPUs and processing-in-memory. He received his Ph.D. in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He is a recipient of the Dan Vivoli Endowed Fellowship at the University of Illinois at Urbana-Champaign, and the Distinguished Graduate Award at the American University of Beirut.
Table of Contents
1 IntroductionPart 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: An introduction to constant memory and caching
8 Stencil
9 Parallel histogram
10 Reduction And minimizing divergence
11 Prefix sum (scan)
12 Merge: An introduction to dynamic input data identification
Part III Advanced patterns and applications
13 Sorting
14 Sparse matrix computation
15 Graph traversal
16 Deep learning
17 Iterative magnetic resonance imaging reconstruction
18 Electrostatic potential map
19 Parallel programming and computational thinking
Part IV Advanced Practices
20 Programming a heterogeneous computing cluster: An introduction to CUDA streams
21 CUDA dynamic parallelism
22 Advanced practices and future evolution
23 Conclusion and outlook
Appendix A: Numerical considerations
What People are Saying About This
Learn how to program massively parallel processors with the new edition of the best-selling guide to CUDA and GPU parallel programming