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Tuesday, July 19 • 11:30am - 12:00pm
AD: Accelerating TauDEM for Extracting Hydrology Information from National-Scale High Resolution Topographic Dataset

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With the advent of DEMs with finer resolution and higher accuracy to represent surface elevation, we face an enormous need to have optimized parallel hydrology algorithms that are imminent to be able to process big DEM data efficiently. TauDEM (Terrain Analysis Using Digital Elevation Models) is a suite of Digital Elevation Model (DEM) tools for the extraction and analysis of hydrologic information from topography. We present performance improvements on parallel hydrology algorithms in TauDEM suite that allowed us to process very big DEM data. The parallel algorithms are improved by applying block-wise data decomposition technique, improving communication model and parallel I/O enhancements to obtain maximum performance from available computational and storage resources at supercomputer systems. After the improvements, as a case study, we successfully filled the depressions of entire US 10-meter DEM data (667GB, 180 billion raster cells) within 2 hours that shows a significant improvement compared to the previous parallel algorithm that was unable to do the same task within 2 days using 4,096 processor cores on Stampede supercomputer. We report the methodology and make the performance analysis of the algorithm improvements.

Tuesday July 19, 2016 11:30am - 12:00pm EDT
Chopin Ballroom