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Title: Evaluating the Efficacy of Wavelet Configurations on Turbulent-Flow Data

I/O is increasingly becoming a significant constraint for simulation codes and visualization tools on modern supercomputers. Data compression is an attractive workaround, and, in particular, wavelets provide a promising solution. However, wavelets can be applied in multiple configurations, and the variations in configuration impact accuracy, storage cost, and execution time. While the variation in these factors over wavelet configurations have been explored in image processing, they are not well understood for visualization and analysis of scientific data. To illuminate this issue, we evaluate multiple wavelet configurations on turbulent-flow data. Our approach is to repeat established analysis routines on uncompressed and lossy-compressed versions of a data set, and then quantitatively compare their outcomes. Our findings show that accuracy varies greatly based on wavelet configuration, while storage cost and execution time vary less. Overall, our study provides new insights for simulation analysts and visualization experts, who need to make tradeoffs between accuracy, storage cost, and execution time.
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Conference: Presented at the 2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV), 25-26 October 2015, Chicago, Illinois; Related Information: Proceedings of the 2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV), 25-26 October 2015, Chicago, Illinois
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE)
Research Org:
NREL (National Renewable Energy Laboratory (NREL), Golden, CO (United States))
Sponsoring Org:
NREL Laboratory Directed Research and Development (LDRD)
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING data analysis; data compression; data visualisation; image coding; parallel machines; wavelet transforms; data compression; data visualization; image processing