High Performance Visualization

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Adaptor Layer
advanced visualisation for large datasets
algorithm design
algorithms
berkeley
Bitmap Index
casting
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Category=UG
Category=UKC
Category=UMB
Category=UYF
Category=UYZF
computational science methods
Data Blocks
Data Parallelization
Direct Volume Rendering
distributed memory parallel systems
distributed rendering systems
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eq_computing
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Exaflops computing
exascale class
exascale simulation workflows
Execution Time
GPU acceleration strategies
GPU-based visualization techniques
high performance computing and scientific visualization
High Performance Visualization
high performance visualization implementations
hybrid parallelism
laboratory
lawrence
Lawrence Berkeley National Laboratory
Los Alamos National Laboratory
many-core computational platforms
MPI Task
multi-core computational platforms
national
NERSC
parallel
parallel computing techniques
Parallel Coordinate Plots
Parallel Rendering
parallel visualization
ray
Ray Casting
rendering
scientific data analysis
scientific visualization and large computational platforms
Simulation Codes
Situ Processing
Thread Block
Tiled Displays
Tunable Algorithmic Parameters
understand complex simulation data
Visualization Algorithms
Visualization and analysis tools
Visualization Application
Visualization Pipeline
Visualization System
volume
Volume Rendering
Wavelet Transform

Product details

  • ISBN 9781138199613
  • Weight: 760g
  • Dimensions: 156 x 234mm
  • Publication Date: 16 Nov 2016
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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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, Charles Hansen