Hybrid (CPU/GPU) Exact Nearest Neighbors Search in High-Dimensional Spaces

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

In this paper, we propose a hybrid algorithm for exact nearest neighbors queries in high-dimensional spaces. Indexing structures typically used for exact nearest neighbors search become less efficient in high-dimensional spaces, effectively requiring brute-force search. Our method uses a massively-parallel approach to brute-force search that efficiently splits the computational load between CPU and GPU. We show that the performance of our algorithm scales linearly with the dimensionality of the data, improving upon previous approaches for high-dimensional datasets. The algorithm is implemented in Julia, a high-level programming language for numerical and scientific computing. It is openly available at https://github.com/davnn/ParallelNeighbors.jl.

OriginalspracheEnglisch
TitelArtificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference, AIAI 2022, Proceedings
Redakteure/-innenIlias Maglogiannis, Lazaros Iliadis, John Macintyre, Paulo Cortez
Herausgeber (Verlag)Springer
Seiten112-123
Seitenumfang12
ISBN (Print)9783031083365
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022 - Hersonissos, Griechenland
Dauer: 17 Juni 202220 Juni 2022

Publikationsreihe

NameIFIP Advances in Information and Communication Technology
Band647 IFIP
ISSN (Print)1868-4238
ISSN (elektronisch)1868-422X

Konferenz

Konferenz18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022
Land/GebietGriechenland
OrtHersonissos
Zeitraum17.06.202220.06.2022

Fingerprint

Untersuchen Sie die Forschungsthemen von „Hybrid (CPU/GPU) Exact Nearest Neighbors Search in High-Dimensional Spaces“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren