S tudying dynamic aspects of physical and chemical processes is critical to the advances of many sciences. State-of-the-art scientific computing technologies allow accurate numerical modeling of many physical and chemical processes in their spatial and temporal domains. However, an increasingly challenging problem scientists must face is how to effectively explore and understand the resulting time-varying volume data that is large in space (from 100 million to a billion voxels), time (hundreds to thousands of time steps), and variable domain (from five to over 100 variables). Scientists' ability to visualize time-varying phenomena is absolutely essential to ensure correct interpretation and analysis, provoke insights, and communicate those insights to others. For instance, by appropriately rendering a time-varying data set, scientists can produce an animation sequence that illustrates how selected underlying structures in the data evolve over time. In particular, interactive visualization lets scientists freely explore the spatial and temporal domains in both the variable space and visualization parameter space. Figure 1 presents selected time steps from the visualization of a turbulent jet data set. The figure demonstrates scientists' ability to interactively explore the data and derive visualizations that clearly separate vortices with positive and negative values. To achieve the needed interactivity, a visualization solution's design must account for hardware constraints. How fast can a sequence of time steps be transferred to the rendering engine, and how can we accelerate the rendering calculations? The availability of texture hardware support for volume rendering enables real-time volume visualization. 1 However, the sheer size of a data set from a contemporary scientific application can easily overwhelm the texture memory space of a typical graphics-acceleration card designed for video games.
Our work focuses on the visualization of time-varying volume data, a topic which has been intensively studied in the context of science and engineering data REF .
VISUALIZING TIME-VARYING VOLUME DATA
Comput. Sci. Eng.
Comput. Sci. Eng.
Computer Science