Contextual Compression of Large-Scale Wind Turbine Array
Simulations
Author/Presenter
Event Type
Workshop
TimeFriday, November 17th12:10pm -
12:30pm
Location302-303
DescriptionData sizes are becoming a critical issue particularly
for HPC applications. We have developed a user-driven
lossy wavelet-based storage model to facilitate the
analysis and visualization of large-scale wind turbine
array simulations. The model stores data as
heterogeneous blocks of wavelet coefficients, providing
high-fidelity access to user-defined data regions
believed the most salient, while providing
lower-fidelity access to less salient regions on a
block-by-block basis. In practice, by retaining the
wavelet coefficients as a function of feature saliency,
we have seen data reductions in excess of 94%, while
retaining lossless information in the turbine-wake
regions most critical to analysis and providing enough
(low-fidelity) contextual information in the upper
atmosphere to track incoming coherent turbulent
structures. Our contextual wavelet compression approach
has allowed us to deliver interactive visual anlaysis
while providing the user control over where data loss,
and thus reduction in accuracy, in the analysis occurs.
We argue this reduced but contexualized representation
is a valid approach and encourages contextual data
management.
Author/Presenter
