High Performance Visualization: Enabling Extreme-Scale Scientific Insight

E. Wes Bethel, Hank Childs, Charles Hansen

October 25, 2012 by Chapman and Hall/CRC
Reference - 520 Pages - 142 B/W Illustrations
ISBN 9781439875728 - CAT# K13513
Series: Chapman & Hall/CRC Computational Science

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  • Covers the framework of distributed memory parallel systems
  • Presents advanced approaches for achieving high performance visualization
  • Explores emerging platforms and architectures, including GPU-based visualization techniques, hybrid parallelism, and exascale class computational platforms
  • Surveys several open source packages, such as VisIt, ParaView, and VAPOR, for implementing high performance visualization
  • Includes a 32-page color insert


Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms. High Performance Visualization: Enabling Extreme-Scale Scientific Insight focuses on the subset of scientific visualization concerned with algorithm design, implementation, and optimization for use on today’s largest computational platforms.

The book collects some of the most seminal work in the field, including algorithms and implementations running at the highest levels of concurrency and used by scientific researchers worldwide. After introducing the fundamental concepts of parallel visualization, the book explores approaches to accelerate visualization and analysis operations on high performance computing platforms. Looking to the future and anticipating changes to computational platforms in the transition from the petascale to exascale regime, it presents the main research challenges and describes several contemporary, high performance visualization implementations.

Reflecting major concepts in high performance visualization, this book unifies a large and diverse body of computer science research, development, and practical applications. It describes the state of the art at the intersection of scientific visualization, large data, and high performance computing trends, giving readers the foundation to apply the concepts and carry out future research in this area.