Interactive remote large-scale data visualization via prioritized multi-resolution streaming

Abstract

The simulations that run on petascale and future exascale supercomputers pose a difficult challenge for scientists to visualize and analyze their results remotely. They are limited in their ability to interactively visualize their data mainly due to limited network bandwidth associated with sending and reading large data at a distance. To tackle this issue, we provide a generalized distance visualization architecture for large remote data that aims to provide interactive analysis. We achieve this through a prioritized, multi-resolution, streaming architecture. Since the original data size is several orders of magnitude greater than the display and network technologies, we stream downsampled versions of representation data over time to complete a visualization using fast local rendering. This technique provides the necessary interactivity and full-resolution results dynamically on demand while maintaining a full-featured visualization framework.