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Published March 26, 2019 | Submitted
Book Section - Chapter Open

Bigger Buffer k-d Trees on Multi-Many-Core Systems


A buffer k-d tree is a k-d tree variant for massively-parallel nearest neighbor search. While providing valuable speed-ups on modern many-core devices in case both a large number of reference and query points are given, buffer k-d trees are limited by the amount of points that can fit on a single device. In this work, we show how to modify the original data structure and the associated workflow to make the overall approach capable of dealing with massive data sets. We further provide a simple yet efficient way of using multiple devices given in a single workstation. The applicability of the modified framework is demonstrated in the context of astronomy, a field that is faced with huge amounts of data.

Additional Information

© 2019 Springer Nature Switzerland AG. First Online: 26 March 2019. The authors would like to thank the Radboud Excellence Initiative of the Radboud University Nijmegen (FG), NVIDIA for generous hardware donations (FG), the Danish Industry Foundation through the Industrial Data Analysis Service (FG, CI, CO), the The Danish Council for Independent Research | Natural Sciences through the project Surveying the sky using machine learning (CI), and ACP, IUCAA, IUSSTF, and NSF (AM).

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