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GPU Computing Gems

GPU Computing Gems

GPU Computing Gems
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GPU Computing Gems Papeback - - 1st Edition

by Wen-Mei W. Hwu (Editor in Chief)

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Elsevier , pp. 888 1st Edition . Papeback. New.
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Details

  • Title GPU Computing Gems
  • Author Wen-Mei W. Hwu (Editor in Chief)
  • Binding Papeback
  • Edition number 1st
  • Edition 1
  • Condition New
  • Pages 886
  • Volumes 1
  • Language ENG
  • Publisher Elsevier , U.S.A.
  • Publication date pp. 888 1st Edition
  • Illustrated Yes
  • Features Illustrated, Index, Table of Contents
  • Bookseller's Inventory # 61808728
  • ISBN 9780123849885 / 0123849888
  • Weight 3.3 lbs (1.50 kg)
  • Dimensions 9.3 x 7.6 x 1.5 in (23.62 x 19.30 x 3.81 cm)
  • Category Computers - General Information
  • Library of Congress subjects Computer graphics, Image processing - Digital techniques
  • Library of Congress Catalogue Number 2010047487
  • Dewey Decimal Code 006.6
  • Quantity available 3

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Reader reviews for GPU Computing Gems

From the publisher

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: ..."

Media reviews

Citations

  • Reference and Research Bk News, 04/01/2011, Page 374
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