ParallelNACluster: A parallel clustering strategy for matching multiple catalogs

• Vinícius Pires de Moura Freire Federal University of Ceará (UFC) / Federal Institute of Education, Science and Technology of Maranhão (IFMA)
• Fábio Porto National Laboratory for Scientific Computing (LNCC)
• José A. F. de Macêdo Federal University of Ceará (UFC)

DOI: https://doi.org/10.5753/sbbd.2017.171359

Abstract

The astronomical catalogs cross-matching aims to identify common celestial objects present in different astronomical surveys. Traditional approaches in astronomy do not provide solutions to the problem of matching in the context of large data volume. In this paper, we have improved the NACluster algorithm by creating the ParallelNACluster strategy, a parallel version of NACluster that takes advantage of input data partitioning, and accepts large volumes of data even using a small hardware set. In addition, we propose the SCIBoundary, a new strategy for matching neighboring stars placed in different data partitions. The strategy leads to equivalent solutions in both NACluster pand ParallelNACluster.

Keywords: Data Matching, Parallelism, Clustering

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