An In Situ Approach for Explorative Visualization using Temporal Intervals

Date and time: 
Tuesday, February 28, 2017 - 11:30
220 Deschutes
Nicole Marsaglia
University of Oregon
  • Hank Childs (Chair)
  • Michal Young
  • Allen Malony


We explore a technique for saving full spatio-temporal simulation data for visualization and analysis. While such data is typically prohibitively large to store, we consider an in situ reduction approach that takes advantage of temporal coherence to make storage sizes tractable in some cases. As I/O constraints continuously increase and hamper the ability of simulations to write full-resolution data to disk, our work presents an in situ data reduction technique with an accuracy guarantee. Rather than limiting our data reduction to individual time slices or time windows, our algorithms act on individual locations and saves data to disk as temporal intervals. Our results show that the efficacy of piecewise approximations, as compared to full spatio-temporal resolution, varies based on the desired error bound guarantee and tumultuousness of the time-varying data.