New Book Series Showcases Scientific Breakthroughs Enabled with Parallel Computing

Morgan Kaufmann and NVIDIA Collaborate on the "GPU Computing Gems" Series

Feb 14, 2011, 10:18 ET from Elsevier

BURLINGTON, Mass., Feb. 14, 2011 /PRNewswire/ -- Data computation has been called the "third pillar of science," alongside the ancient pillars of logic and observation, and upon which future scientific breakthroughs will rest.  Morgan Kaufmann, a global leader in cutting-edge computing content, today announced the availability of the first volume in a new book series that will showcase how advanced parallel computing techniques are revolutionizing scientific research.  

The GPU Computing Gems series was developed in collaboration with NVIDIA, the world leader in visual and parallel computing.  Graphics processing units (GPUs), which were invented by NVIDIA, have revolutionized data computation and are playing a key role in enabling leading researchers and academics to drive the next wave of scientific discovery.  The GPU Computing Gems series will provide practical techniques and real-world examples straight from the leading minds in GPU-based research, demonstrating how new parallel computing techniques can be harnessed within different domains to enable new scientific breakthroughs.

GPU Computing Gems: Emerald Edition is the first volume in the series, and is available today from key book retailers and e-tailers.  Visit for more information.

Computational scientists increasingly utilize GPUs for computational-intensive applications to achieve dramatic improvements in processing power, efficiency and power consumption.  The challenge for developers in the new arena of scientific research is learning how to program systems that effectively use these concurrent processors to achieve these goals, and GPU Computing Gems was created to provide real-world tips and guidance to assist researchers.  Each chapter presents techniques used in leading research, designed to be accessible to others in multiple fields and disciplines, allowing knowledge to cross-pollinate across the GPU spectrum.

GPU Computing Gems: Emerald Edition will focus on how GPU computing can be applied to:

  • Scientific Simulation
  • Life Sciences
  • Statistical Modeling
  • Emerging Data-Intensive Applications
  • Electronic Design Automation
  • Ray Tracing and Rendering
  • Computer Vision
  • Video and Image Processing
  • Signal and Audio Processing
  • Medical Imaging

Editor-in-Chief Wen-mei W. Hwu, the Walter J. ("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, has assembled the leading researchers in parallel programming and gathered their solutions and experiences in one volume under the guidance of expert editors.

The second volume, titled GPU Computing Gems: Jade Edition, will also be edited by Wen-mei W. Hwu, and will gather experts from eight critical GPU computing domains:

  • Programming Tools and Libraries
  • Financial Modeling
  • Engineering Simulation
  • Environment Methodology
  • Interactive Physics Simulation and AI for Games and Entertainment
  • Numerical Algorithms
  • Parallel Algorithms
  • Data Structures

The Jade Edition will be published in June 2011. Both titles are part of Morgan Kaufmann's Applications of GPU Computing series. Additional books will follow in 2011 and beyond to help researchers and developers leverage GPUs to improve application speed and efficiency.

About the Editor-in-Chief

Wen-mei W. Hwu is the Walter J. ("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. From 1997 to 1999, Dr. Hwu served as the chairman of the Computer Engineering Program at the University of Illinois. Dr. Hwu received his Ph.D. degree in Computer Science from the University of California, Berkeley. His research interests are in the areas of architecture, implementation, and software for high-performance computer systems. He is the director of the OpenIMPACT project, which has delivered new compiler and computer architecture technologies to the computer industry since 1987. He also serves as the Soft Systems Theme leader of the MARCO/DARPA Gigascale Silicon Research Center (GSRC) and on the Executive Committees of both the GSRC and the MARCO/DARPA Center for Circuit and System Solutions.

Now Available

GPU Computing Gems: Emerald Edition

Wen-mei W. Hwu, Editor-in-Chief

ISBN: 9780123849885; e-ISBN: 9780123849892

February 14th, 2011 | Hardcover | 900 pp

EUR 53.95/USD 74.95/GBP 45.99

Coming in June 2011

GPU Computing Gems: Jade Edition

Wen-mei W. Hwu, Editor-in-Chief

ISBN: 9780123859631; e-ISBN: 9780123859648

June 21st, 2011 | Hardcover | Pages 900

EUR 53.95/USD 74.95/GBP 45.99

Additional information, including sample content and online webinars:


Morgan Kaufmann has been bringing the knowledge of experts to the computing community since 1984.  Our goal is to provide timely yet timeless content to research and development professionals, business leaders and IT managers, everyday practitioners, and academia.  We publish textbooks and references in Artificial Intelligence, Computer Networking, Computer Architecture, Computer Graphics & Game Development, Data Management & Business Intelligence, Software Engineering, and User Experience & Human Computer Interaction.  For more information, visit


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NVIDIA (Nasdaq: NVDA) awakened the world to the power of computer graphics when it invented the GPU in 1999. Since then, it has consistently set new standards in visual computing with breathtaking, interactive graphics available on devices ranging from tablets and portable media players to notebooks and workstations. NVIDIA's expertise in programmable GPUs has led to breakthroughs in parallel processing which make supercomputing inexpensive and widely accessible. The Company holds more than 1,700 patents worldwide, including ones covering designs and insights that are essential to modern computing. For more information, see

SOURCE Elsevier