GPU Computing Gems, Emerald Edition Wen-Mei W. Hwu

ISBN: 9780123849885

Published: February 7th 2011

Hardcover

865 pages


Description

GPU Computing Gems, Emerald Edition  by  Wen-Mei W. Hwu

GPU Computing Gems, Emerald Edition by Wen-Mei W. Hwu
February 7th 2011 | Hardcover | PDF, EPUB, FB2, DjVu, AUDIO, mp3, RTF | 865 pages | ISBN: 9780123849885 | 7.76 Mb

...the perfect companion to Programming Massively Parallel Processors by Hwu & Kirk. -Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010Graphics processing units (GPUs) can do much more than render graphics.More...the perfect companion to Programming Massively Parallel Processors by Hwu & Kirk.

-Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010Graphics processing units (GPUs) can do much more than render graphics. Scientists and researchers increasingly look to GPUs to improve the efficiency and performance of computationally-intensive experiments across a range of disciplines.GPU Computing Gems: Emerald Edition brings their techniques to you, showcasing GPU-based solutions including: Black hole simulations with CUDAGPU-accelerated computation and interactive display of molecular orbitalsTemporal data mining for neuroscienceGPU -based parallelization for fast circuit optimizationFast graph cuts for computer visionReal-time stereo on GPGPU using progressive multi-resolution adaptive windowsGPU image demosaicingTomographic image reconstruction from unordered lines with CUDAMedical image processing using GPU -accelerated ITK image filters41 more chapters of innovative GPU computing ideas, written to be accessible to researchers from any domainGPU Computing Gems: Emerald Edition is the first volume in Morgan Kaufmanns Applications 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, and video / image processing.Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and moreMany examples leverage NVIDIAs CUDA parallel computing architecture, the most widely-adopted massively parallel programming solutionOffers insights and ideas as well as practical hands-on skills you can immediately put to use



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