DiscFinder: A data-intensive scalable cluster finder for astrophysics

Bin Fu, Kai Ren, Julio Lopez, Eugene Fink, and Garth Gibson

In Proceedings of the ACM International Symposium on High Performance Distributed Computing, pages 348-351, 2010.


DiscFinder is a scalable approach for identifying large-scale astronomical structures, such as galaxy clusters, in massive observation and simulation astrophysics datasets. It is designed to operate on datasets with tens of billions of astronomical objects, even in the case when the dataset is much larger than the aggregate memory of compute cluster used for the processing.