Abstract
Graphics Processing Units (GPUs) are designed to be parallel - having hundreds of cores versus traditional CPUs. Increasingly, you can leverage GPU power for any computationally-intense operation - not just for graphics. If you're facing the challenge of programming systems to effectively use these massively parallel processors to achieve efficiency and performance goals, GPU Computing Gems provides a wealth of tested, proven GPU techniques. Learn from the leading researchers in concurrent programming, who have gathered their insights and experience in one volume under the guidance of NVIDIA and GPU expert Wen-mei Hwu. Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and moreMany examples utilize NVIDIA's CUDA parallel computing architecture, the most widely-adopted GPU programming toolOffers insights and ideas as well as practical hands-on skills you can immediately put to use
Published Version
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