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Free PDF Programming Massively Parallel Processors: A Hands-on Approach
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Programming Massively Parallel Processors: A Hands-on Approach
Free PDF Programming Massively Parallel Processors: A Hands-on Approach
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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.Wen-mei W. Hwu is a Professor and holds the Sanders-AMD Endowed Chair in the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign. His research interests are in the area of architecture, implementation, compilation, and algorithms for parallel computing. He is the chief scientist of Parallel Computing Institute and director of the IMPACT research group (www.impact.crhc.illinois.edu). He is a co-founder and CTO of MulticoreWare. For his contributions in research and teaching, he received the ACM SigArch Maurice Wilkes Award, the ACM Grace Murray Hopper Award, the Tau Beta Pi Daniel C. Drucker Eminent Faculty Award, the ISCA Influential Paper Award, the IEEE Computer Society B. R. Rau Award and the Distinguished Alumni Award in Computer Science of the University of California, Berkeley. He is a fellow of IEEE and ACM. He directs the UIUC CUDA Center of Excellence and serves as one of the principal investigators of the NSF Blue Waters Petascale computer project. Dr. Hwu received his Ph.D. degree in Computer Science from the University of California, Berkeley.
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Product details
Paperback: 576 pages
Publisher: Morgan Kaufmann; 3 edition (December 21, 2016)
Language: English
ISBN-10: 0128119861
ISBN-13: 978-0128119860
Product Dimensions:
7.5 x 1.2 x 9.2 inches
Shipping Weight: 2.6 pounds (View shipping rates and policies)
Average Customer Review:
4.7 out of 5 stars
5 customer reviews
Amazon Best Sellers Rank:
#336,673 in Books (See Top 100 in Books)
The new edition of the book is improved significantly related to the already superb previous edition.The technical writing and presentation is outstanding and a lot of CUDA programming examples are presented.Also, it covers thoroughly the recent advances in CUDA technology as the dynamic parallelism.I strongly recommend the book to the Amazon readers interested in GPU computing.
Thorough coverage of the hardware, data structures, and algorithms you need to effectively use Nvidia GPU devices. Missed one star, because the code examples are incomplete: kernels for GPU execution are well documented, but the host code is missing, so outside resources (books, websites, etc.) are required to write compilable programs. Please, open your source code!
This book is a lot better than others I have read.
Excellent product.
Only CUDA programming book that contains Pascal Arch. right now.
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