SC Conference - Activity Details
Terascale Data Organization for Discovering Multivariate Climatic Trends
Authors:| Wesley Kendall (University of Tennessee, Knoxville) |
| Markus Glatter (University of Tennessee, Knoxville) |
| Jian Huang (University of Tennessee, Knoxville) |
| Tom Peterka (Argonne National Laboratory) |
| Robert Latham (Argonne National Laboratory) |
| Robert Ross (Argonne National Laboratory) |
| Large-Scale Applications |
| Tuesday, 10:30AM - 11:00AM |
| Room PB255 |
Current visualization tools lack the ability to perform full-range spatial and temporal analysis on terascale scientific datasets. Two key reasons exist for this shortcoming: I/O and postprocessing on these datasets are being performed in suboptimal manners, and the subsequent data extraction and analysis routines have not been studied in depth at large scales. We resolved these issues through advanced I/O techniques and improvements to current query-driven visualization methods. We show the efficiency of our approach by analyzing over a terabyte of multivariate satellite data and addressing two key issues in climate science: time-lag analysis and drought assessment. Our methods allowed us to reduce the end-to-end execution times on
these problems to one minute on a Cray XT4 machine.
The full paper can be found in the
ACM Digital Library and IEEE Computer Society
   |