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
From the Back Cover
Practical techniques straight from the leading minds in general purpose GPU research.
"...the perfect companion to Programming Massively Parallel Processors by Hwu & Kirk."--Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010
Graphics Processing Units (GPUs) are designed to be parallel having hundreds of cores versus traditional CPUs. Increasingly, you can leverage GPU power for many computationally-intense applications not just for graphics. If you're facing the challenge of programming systems to effectively use these massively parallel processors to achieve efficiencyandperformance goals,GPU Computing Gemsprovides a wealth of tested, proven GPU techniques.
Different application domains often pose similar algorithm problems, and researchers from diverse application domains often develop similar algorithmic strategies.GPU Computing Gemsoffers 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.
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.
GPU Computing Gems: Emerald Editionis the first volume in Morgan Kaufmann'sApplications of GPU Computing Series, offering the latest insights and research in computer vision, electronic design automation, emerging data-intensive applications, life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing.
- A snapshot of the state of GPU computing in ten critical domains, edited by Wen-mei W. Hwu with experts from NVIDIA Corporation and instructors from leading GPU programs worldwide
- Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted GPU programming tool
- Offers insights and ideas as well as practical "hands-on" skills you can immediately put to use
About the Editor-in-Chief
Wen-Mei W. Hwu is the co-author ofProgramming Massively Parallel Processorsand Jerry Sanders III-Advanced Micro Devices Endowed Chair in Electrical and Computer Engineering in the Coordinated Science Laboratory of the University of Illinois at Urbana-Champaign.
Applications of GPU Computing Series