Enabling Knowledge Discovery in a Virtual Universe

Virtual observatories will give astronomers easy access to an unprecedented amount of data. Extracting scientific knowledge from these data will increasingly demand both efficient algorithms as well as the power of parallel computers. Such machines will range in size from small Beowulf clusters to large Massively Parallel Platforms (MPPs) to collections of MPPs distributed across a Grid, such as the NSF TeraGrid facility. Nearly all efficient analyses of large astronomical datasets use trees as their fundamental data structure. Writing efficient tree-based techniques, a task that is time-consuming even on single-processor computers, is exceedingly cumbersome on parallel or grid-distributed resources.

Provided by: Pittsburgh Supercomputing Center Topic: Data Management Date Added: Jan 2011 Format: PDF

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