Programming Massively Parallel Processors: A Hands-on Approach 3rd Edition by David B. Kirk (PDF)

Description

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending 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 have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices.

User’s Reviews

Editorial Reviews: Review Learn how to program massively parallel processors with this best-selling guide to CUDA and GPU parallel programming 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.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐Tough book to get through, but we used this in one of our classes and it was very good. I can’t remember how the print quality was but the content was excellent.

⭐Perfect condition, fast shipping!

⭐This book (third edition) pretends that you can go online for supplements, like any other programming book, but it’s just kidding. There’s a course page with nothing on it but a course description. There’s a lab page that actually lets you download a zip file with completely empty folders in it. There’s zero assistance in the book with setting up a development environment, even though it’s apparently difficult enough for the course description to dedicate a whole lab to it. And most problematic, there won’t be any files of data big enough to use as input to the programs to actually demonstrate massively parallel processing. I’m quite sure that the only programs you’ll be able to run using just the book, in every chapter, will barely rise above hello world.

⭐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!

⭐Well written and very useful, this is the best book to start learning CUDA programming from.

⭐Whatever its content are, this book (Kindle Edition) needs to be fully revised. Font-size and formatting for some code fragments are ridiculous. (eg. Its text-size is too big or several code lines are concatenated as one line.) Some other code examples added as images are somewhat unrecognizable in Kindle display so I have to zoom-in. And I found several typos in code fragments and code examples.

⭐This book is a lot better than others I have read.

⭐Having some C++ experience, I was looking for a comprehensive introduction to CUDA and its optimisations. This book is exactly what I was hoping for and gave me all the information I was struggling to find online. The parts about performance optimisation are so helpful and I was able to finish the project I was working on thanks to this book.I would say, as one other review noted, only the device code is given, meaning it’s sometimes not easy to intuit the host code which is left entirely to the reader. I understand constraints of space in the book, but I don’t think this was the best approach.For that reason, I don’t recommend this to complete beginners. I don’t think I would have been able to do this without some existing C/C++ experience.

⭐Para mí es uno de los mejores libros, y en el que me baso para ir dando mis primeros pasitos en CUDA. Como valor añadido puedo deciros que al haber conocido a los autores del libro en una conferencia, ambos han realizado un libro realmente impresionante y decir que tienen muy en cuenta las opiniones constructivas que se les dan.The text is great. Easy to understand, concise, illustrated with examples and execercises. However, the quality of the book itself is miserable. You must not bend it, neither open it further then 60 deg. Otherwise, the glue breaks and a hundred pages flip into you hands.

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