Frameworks for visualization at the extreme scale

The challenges of visualization at the extreme scale involve issues of scale, complexity, temporal exploration and uncertainty. The Visualization and Analytics Center for Enabling Technologies (VACET) focuses on leveraging scientific visualization and analytics software technology as an enabling technology to increased scientific discovery and insight. In this paper, we introduce new uses of visualization frameworks through the introduction of Equivalence Class Functions (ECFs). These functions give a new class of derived quantities designed to greatly expand the ability of the end user to explore and visualize data. ECFs are defined over equivalence classes (i.e., groupings) of elements from an original mesh, and produce summary values for the classes as output. ECFs can be used in the visualization process to directly analyze data, or can be used to synthesize new derived quantities on the original mesh. The design of ECFs enable a parallel implementation that allows the use of these techniques on massive data sets that require parallel processing.