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Large datasets in astronomy and geoscience often require clustering and visualizations of phenomena at different densities and scales in order to generate scientific insight. We examine the problem of maximizing clustering throughput for concurrent dataset clustering in spatial dimensions. We introduce a novel hybrid approach that uses GPUs in conjunction with multicore CPUs for algorithmic throughput...
Analysis of transient deformation events in time series data observed via networks of continuous Global Positioning System (GPS) ground stations provide insight into the magmatic and tectonic processes that drive volcanic activity. Typical analyses of spatial positions originating from each station require careful tuning of algorithmic parameters and selection of time and spatial regions of interest...
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