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 scientifi
Introduction. I Distributed Memory Parallel Concepts and Systems: Parallel Visualization Frameworks. Remote and Distributed Visualization Architectures. Rendering. Parallel Image Compositing Methods. Parallel Integral Curves. II Advanced Processing Techniques: Query-Driven Visualization and Analysis. Progressive Data Access for Regular Grids: In Situ Processing. Streaming and Out-of-Core Methods. III Advanced Architectural Challenges and Solutions: GPU-Accelerated Visualization. Hybrid Parallelism. Visualization at Extreme Scale Concurrency. Performance Optimization and Auto-tuning. The Path to Exascale. IV High Performance Visualization Implementations: VisIt: An End-User Tool for Visualizing and Analyzing Very Large Data. IceT. The ParaView Visualization Application. The ViSUS Visualization Framework. The VAPOR Visualization Application. The EnSight Visualization Application. Index.