GPU Computing Gems Emerald Edition (Applications of GPU Computing Series) Wen-mei W. Hwu

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.

Features

• 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