GPU Computing Gems Emerald Edition
Morgan Kaufmann (Publisher)
Published on 21. March 2011
Book
Hardback
886 pages
978-0-12-384988-5 (ISBN)
Description
GPU Computing Gems Emerald Edition offers practical techniques in parallel computing using graphics processing units (GPUs) to enhance scientific research. The first volume in Morgan Kaufmann's Applications of GPU Computing Series, this book offers the latest insights and research in computer vision, electronic design automation, and emerging data-intensive applications. It also covers life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing.
This book is intended to help those who are facing the challenge of programming systems to effectively use GPUs to achieve efficiency and performance goals. It offers developers a window into diverse application areas, and the opportunity to gain insights from others' algorithm work that they may apply to their own projects. Readers will learn from the leading researchers in parallel programming, who have gathered their solutions and experience in one volume under the guidance of expert area editors. Each chapter is written to be accessible to researchers from other domains, allowing knowledge to cross-pollinate across the GPU spectrum. Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution. The insights and ideas as well as practical hands-on skills in the book can be immediately put to use.
Computer programmers, software engineers, hardware engineers, and computer science students will find this volume a helpful resource. For useful source codes discussed throughout the book, the editors invite readers to the following website:
This book is intended to help those who are facing the challenge of programming systems to effectively use GPUs to achieve efficiency and performance goals. It offers developers a window into diverse application areas, and the opportunity to gain insights from others' algorithm work that they may apply to their own projects. Readers will learn from the leading researchers in parallel programming, who have gathered their solutions and experience in one volume under the guidance of expert area editors. Each chapter is written to be accessible to researchers from other domains, allowing knowledge to cross-pollinate across the GPU spectrum. Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution. The insights and ideas as well as practical hands-on skills in the book can be immediately put to use.
Computer programmers, software engineers, hardware engineers, and computer science students will find this volume a helpful resource. For useful source codes discussed throughout the book, the editors invite readers to the following website:
Reviews / Votes
Praise for GPU Computing Gems: Emerald Edition:"GPU computing is becoming an outstanding field in high performance computing. Due to its easiness, the CUDA approach enables programmers to take advantage of GPU-acceleration very quickly... My research in complex science as well as applications in high frequency trading benefited significantly from GPU computing." --Dr. Tobias Preis, ETH Zurich, Switzerland
"This book is an important reference for everyone working on GPU/CUDA, and contains definitive work in a selection of fields. The patterns of CUDA parallelization it describes can often be adapted to applications in other fields." --Dr. Ming Ouyang, Assistant Professor - Director Visualization and Intensive Graphics Lab, University of Louisville
"Diving into the world of GPU computing has never been more important these days. GPU Computing Gems: Emerald Edition takes you through the looking glass into this fascinating world." --Martin Eisemann, Computer Graphics Lab, TU Braunschweig
"...an outstanding collection of vignettes of how to program GPUs for a breathtaking range of applications." --Dr. Amitabh Varshney, Director, Institute for Advanced Computer Studies, University of Maryland
"The book features a useful index that might help readers mine the gems in search of a solution to a specific algorithmic problem. The index is accompanied by online resources containing source code samples-and further information-for some of the chapters. A second volume with another 30 chapters of GPGPU application reports, somewhat more focused on generic algorithms and programming techniques, is currently in the pipeline and scheduled to appear as the "Jade Edition" sometime this month." --Computing in Science and Engineering
"The book is an excellent selection of important papers describing various applications of GPUs. As such, I believe it would be a valuable addition to the bookshelf of any researcher in modeling and simulation...This is not a substitute for a more detailed text on massively parallel programming...Instead, it is a nice practical addition to that text." --Computing Reviews, August 2012
"...the perfect companion to Programming Massively Parallel Processors by Hwu & Kirk." -Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010
More details
Series
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
computer programmers, software engineers, hardware engineers, computer science students
Product notice
Unsewn / adhesive bound
Paper over boards
Illustrations
437 illustrations
Dimensions
Height: 244 mm
Width: 200 mm
Thickness: 40 mm
Weight
1506 gr
ISBN-13
978-0-12-384988-5 (9780123849885)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
10/2018
Morgan Kaufmann
€59.41
The article will not be published
Person
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.
Content
1. Scientific Simulation
2. Life Sciences
3. Statistical Modeling
4. Emerging Data-Intensive Applications
5. Electronic Design Automation
6. Ray Tracing and Rendering
7. Computer Vision
8. Video and Image Processing
9. Signal and Audio Processing
10. Medical Imaging
2. Life Sciences
3. Statistical Modeling
4. Emerging Data-Intensive Applications
5. Electronic Design Automation
6. Ray Tracing and Rendering
7. Computer Vision
8. Video and Image Processing
9. Signal and Audio Processing
10. Medical Imaging