"...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) 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 CUDA
  • GPU-accelerated computation and interactive display of molecular orbitals
  • Temporal data mining for neuroscience
  • GPU -based parallelization for fast circuit optimization
  • Fast graph cuts for computer vision
  • Real-time stereo on GPGPU using progressive multi-resolution adaptive windows
  • GPU image demosaicing
  • Tomographic image reconstruction from unordered lines with CUDA
  • Medical image processing using GPU -accelerated ITK image filters
  • 41 more chapters of innovative GPU computing ideas, written to be accessible to researchers from any domain

GPU Computing Gems: Emerald Edition is the first volume in Morgan Kaufmann's 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.

Key Features

  • Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and more
  • Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution
  • Offers insights and ideas as well as practical "hands-on" skills you can immediately put to use


computer programmers, software engineers, hardware engineers, computer science students

Table of Contents

Editor’s Introduction: State of GPU Computing

Section 1: Scientific Simulation

State of GPU Computing in Scientific Simulation

1: GPU-Accelerated Computation and Interactive Display of Molecular Orbitals

2: Large-Scale Chemical Informatics on GPUs

3: Dynamical Quadrature Grids: Applications in Density Functional Calculations

4: Fast Molecular Electrostatics Algorithms on GPUs

5: Quantum Chemistry: Propagation of Electronic Structure on GPU

6: An Efficient CUDA Implementation of the Tree-based Barnes

Hut n-Body Algorithm

7: Leveraging the Untapped Computation Power of GPUs: Fast Spectral Synthesis Using Texture Interpolation

8: Black Hole Simulations with CUDA

9: Treecode and Fast Multipole Method for N-body Simulation with CUDA

10: Wavelet-based Density Functional Theory Calculation on Massively Parallel Hybrid Architectures

Section 2: Life Sciences

State of GPU Computing in Life Sciences

11: Accurate Scanning of Sequence Databases with the Smith-Waterman Algorithm

12: Massive Parallel Computing to Accelerate Genome-Matching

13: GPU-Supercomputer Acceleration of Pattern Matching

14: GPU Accelerated RNA Folding Algorithm

15: Temporal Data Mining for Neuroscience

Section 3: Statistical Modeling

State of GPU Computing in Statistical Modeling

16: Parallelization Techniques for Random Number Generations

17: Monte Carlo Photon Transport on the GPU

18: High Performance Iterated Function Systems

Section 4: Emerging Data-intensive Applications

State of GPU Computing in Data-intensive Applications

19: Large Scale Machine Learning

20: Multiclass Support Vector Machine

21: Template Driven Agent Based Modeling and Simulation with CUDA

22: GPU-Accelerated Ant Colony Optimization

Section 5: Electronic Design Automation


No. of pages:
© 2011
Morgan Kaufmann
Print ISBN:
Electronic ISBN:


Praise for GPU Computing Gems: Emerald Edition:

“GPU computing is becoming an outstanding field in high performance computing. Due to its easiness, the CUDA approach enables programmers to take advantage of GPU-acceleration very quickly… My research in complex science as well as applications in high frequency trading benefited significantly from GPU computing.”--Dr. Tobias Preis, ETH Zurich, Switzerland
“This book is an important reference for everyone working on GPU/CUDA, and contains definitive work in a selection of fields. The patterns of CUDA parallelization it describes can often be adapted to applications in other fields.”--
Dr. Ming Ouyang, Assistant Professor – Director Visualization and Intensive Graphics Lab, University of Louisville
“Diving into the world of GPU computing has never been more important these days. GPU Computing Gems: Emerald Edition takes you through the looking glass into this fascinating world.”--
Martin Eisemann, Computer Graphics Lab, TU Braunschweig
“…an outstanding collection of vignettes of how to program GPUs for a breathtaking range of applications.”--
Dr. Amitabh Varshney, Director, Institute for Advanced Computer Studies, University of Maryland
"The book features a useful index that might help readers mine the gems in search of a solution to a specific algorithmic problem. The index is accompanied by online resources containing source code samples—and further information—for some of the chapters. A second volume with another 30 chapters of GPGPU application reports, somewhat more focused on generic algorithms and programming techniques, is currently in the pipeline and scheduled to appear as the "Jade Edition" sometime this month."--
Computing in Science and Engineering
"The book is an excellent selection of important paper