GPU Computing Gems Emerald Edition

Description

"...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.

* 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

CONTENTS:

* 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