We present a systematic approach for direct volume rendering terascale-sized data that are time-varying, and possibly non-uniformly sampled, using only a single commodity graphics PC. Our method employs a data reduction ...

An important challenge in the application of direct volume rendering to time-varying data is the specification of transfer functions for all time steps. Very little research has been devoted to this problem, however. To ...

The proper usage and creation of transfer functions for time-varying data sets is an often ignored problem in volume visualization. Although methods and guidelines exist for time-invariant data, little formal study for the ...

Successful in-situ and remote visualization solutions must have minimal storage requirements and account for only a small percentage of supercomputing time. One solution that meets these requirements is to store a compact ...

Geodesic grids are commonly used to model the surface of a sphere and are widely applied in numerical simulations of geoscience applications. These applications range from biodiversity, to climate change and to ocean ...

The growing power of supercomputers continues to improve scientists' ability to model larger, more sophisticated problems in science with higher accuracy. An equally important ability is to make full use of the data output ...

Word clouds are proliferating on the Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a document collection quickly, their ability to visually ...

Large-scale time-varying volume data sets can take terabytes to petabytes of storage space to store and process. One promising approach is to process the data in parallel, and then extract and analyze only features of ...

We present a novel graph-based data-driven technique for cost-effective fire modeling. This technique allows composing long animation sequences using a small number of short simulations. While traditional techniques such ...