Accelerated K-Means Algorithms for Low-Dimensional Data on Parallel Shared-Memory Systems

This paper considers the problem of exact accelerated algorithms for the K-means clustering of low-dimensional data on modern multi-core systems. A version of the filtering algorithm parallelized using the OpenMP (Open Multi-Processing) standard is proposed. The algorithm employs a kd-tree structure...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access 2021, Vol.9, p.74286-74301
Hauptverfasser:	Kwedlo, Wojciech, Lubowicz, Michal
Format:	Artikel
Sprache:	eng
Schlagworte:	<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">K -means clustering Acceleration of <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">K -means Algorithms Approximation algorithms Centroids Cluster analysis Clustering Clustering algorithms Datasets Filtration Graphics processing units Heuristic algorithms kd-trees OpenMP tasks Parallel processing parallelization Partitioning algorithms Signal processing algorithms Task analysis Vector quantization
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!