High Performance Visualization

Enabling Extreme-Scale Scientific Insight

Edited by E. Wes Bethel, Hank Childs, Charles Hansen

© 2012 – Chapman and Hall/CRC

520 pages | 142 B/W Illus.

Purchasing Options:
Hardback: 9781439875728
pub: 2012-10-25
US Dollars$122.95

About the Book

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.


E. Wes Bethel, Hank Childs, and Chuck Hansen have developed an eminently readable and comprehensive book. It provides the very first in-depth introduction to the interaction of two highly important and relevant topics in computational science: high performance computing and scientific visualization. The book provides a broad background on both topics, but more importantly, for the first time in book form, they describe some of the most recent developments in scientific visualization as we move from the Petascale era to Exaflops computing. … It will provide a solid foundation for anyone who considers using the most recent tools for visualization in order to understand complex simulation data or to understand the ever increasing amount of experimental data. I highly recommend this timely book for scientists and engineers.

—From the Foreword by Horst Simon, Lawrence Berkeley National Laboratory and University of California, Berkeley

Table of Contents

Introduction, E. Wes Bethel

Historical Perspective

Moore's Law and the Data Tsunami

Focus of this Book

Book Organization and Themes


I Distributed Memory Parallel Concepts and Systems

Parallel Visualization Frameworks, Hank Childs



Parallelization Strategy


Advanced Processing Techniques


Remote and Distributed Visualization Architectures,E. Wes Bethel and Mark Miller


Visualization Performance Fundamentals and Networks

The Send-Images Partitioning

The Send-Data Partitioning

The Send-Geometry Partitioning

Hybrid and Adaptive Approaches

Which Pipeline Partitioning Works the Best?

Case Study: Visapult

Case Study: Chromium Renderserver

Case Study: VisIt and Dynamic Pipeline Reconfiguration


Rendering,Charles Hansen, E. Wes Bethel, Thiago Ize, and Carson Brownlee


Rendering Taxonomy

Rendering Geometry

Volume Rendering

Real-Time Ray Tracer for Visualization on a Cluster


Parallel Image Compositing Methods, Tom Peterka and Kwan-Liu Ma


Basic Concepts and Early Work in Compositing

Recent Advances


Discussion and Conclusion

Parallel Integral Curves,David Pugmire, Tom Peterka, and Christoph Garth


Challenges to Parallelization

Approaches to Parallelization


II Advanced Processing Techniques

Query-Driven Visualization and Analysis,Oliver Rübel, E. Wes Bethel, Prabhat, and Kesheng Wu


Data Subsetting and Performance

Formulating Multivariate Queries

Applications of Query-Driven Visualization


Progressive Data Access for Regular Grids,John Clyne



Z-Order Curves


Further Reading

In Situ Processing, Hank Childs,Kwan-Liu Ma and Hongfeng Yu, Brad Whitlock, Jeremy Meredith, and Jean Favre, Scott Klasky and Norbert Podhorszki, Karsten Schwan and Matthew Wolf, Manish Parashar, and Fan Zhang


Tailored Co-Processing at High Concurrency

Co-Processing with General Visualization Tools via Adaptors

Concurrent Processing

Service Oriented Architecture for data management in HPC

In Situ Analytics using Hybrid Staging


Streaming and Out-of-Core Methods,David E. DeMarle, Berk Geveci, Jon Woodring, and Jim Ahrens

External Memory Algorithms

Taxonomy of Streamed Visualization

Streamed Visualization Concepts

Survey of Current State-of-the-Art


III Advanced Architectural Challenges and Solutions

GPU-Accelerated Visualization,Marco Ament, Steffen Frey, Christoph Muller, Sebastian Grottel, Thomas Ertl, and Daniel Weiskopf


Programmable Graphics Hardware

GPU-Accelerated Volume Rendering

Particle-Based Rendering

GPGPU High Performance Environments

Large Display Visualization

Hybrid Parallelism,E. Wes Bethel, David Camp, Hank Childs, Chistoph Garth, Mark Howison, Kenneth I. Joy, and Dave Pugmire


Hybrid Parallelism and Volume Rendering

Hybrid Parallelism and Integral Curve Calculation

Conclusion and Future Work

Visualization at Extreme-Scale Concurrency,Hank Childs, David Pugmire, Sean Ahern, Brad Whitlock, Mark Howison, Prabhat, Gunther Weber, and E. Wes Bethel

Overview|Pure Parallelism

Massive Data Experiments

Scaling Experiments

Pitfalls at Scale


Performance Optimization and Autotuning,E. Wes Bethel and Mark Howison


Optimizing Performance of a Three-Dimensional Stencil Operator on the GPU

Optimizing Raycasting Volume Rendering on Multi-Core GPUs and Many-Core GPUs


The Path to Exascale,Sean Ahern


Future System Architectures

Science Understanding Needs at the Exascale

Research Directions

Conclusion and the Path Forward

IV High Performance Visualization Implementations

VisIt: An End-User Tool for Visualizing and Analyzing Very Large Data,Hank Childs, Eric Brugger, Brad Whitlock, Jeremy Meredith, Sean Ahern, David Pugmire, Kathleen Bonnell, Mark Miller, Cyrus Harrison, Gunther HWeber, Hari Krishnan, Thomas Fogal, Allen Sanderson, Christoph Garth, EWes Bethel, David Camp, Oliver Rubel, Marc Durant, Jean MFavre, and Paul Navrátil


Focal Points



Future Challenges


IceT,Kenneth Moreland




Application Programming Interface


The ParaView Visualization Application,Utkarsh Ayachit, Berk Geveci, Kenneth Moreland, John Patchett, and Jim Ahrens


Understanding the Need

The ParaView Framework

Parallel Data Processing

The ParaView Application

Customizing with Plug-ins and Custom Applications

Co-processing: In Situ Visualization and Data Analysis

ParaViewWeb: Interactive Visualization for the Web

ParaView In Use


The ViSUS Visualization Framework, Valerio Pascucci, Giorgio Scorzelli, Brian Summa, Peer-Timo Bremer, Attila Gyulassy, Cameron Christensen, Sujin Philip, and Sidharth Kumar


ViSUS Software Architecture


The VAPOR Visualization Application,Alan Norton and John Clyne


Progressive Data Access

Visualization-Guided Analysis

Progressive Access Examination



The EnSight Visualization Application,Randall Frank and Michael F. Krogh


EnSight Architectural Overview

Cluster Abstraction: CEIShell

Advanced Rendering




About the Originator

About the Series

Chapman & Hall/CRC Computational Science

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Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Computer Graphics
MATHEMATICS / Arithmetic