@inbook{711f12d21bf241cc93cbe7d19f1110ed,
title = "Bigger buffer k-d trees on multi-many-core systems",
abstract = "A buffer k -d{\^A} tree is a k -d{\^A} 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{\^A} 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.",
author = "Gieseke, {Fabian Cristian} and Oancea, {Cosmin Eugen} and Ashish Mahabal and Christian Igel and Tom Heskes",
year = "2019",
doi = "10.1007/978-3-030-15996-2_15",
language = "English",
isbn = "978-3-030-15995-5",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "202--214",
booktitle = "High Performance Computing for Computational Science – VECPAR 2018",
address = "Switzerland",
note = "13th International Conference on High Performance Computing in Computational Science, VECPAR 2018 ; Conference date: 17-09-2018 Through 19-09-2018",
}