GPU-Accelerated Similarity Self-Join for Multi-Dimensional Data-Reference-Cited by-同舟云学术

GPU-Accelerated Similarity Self-Join for Multi-Dimensional Data

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 15th International Workshop on Data Management on New Hardware - DaMoN'19
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Author:

Gowanlock Michael¹,Karsin Ben²

Affiliation:

1. School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, U.S.A.

2. Department of Computer Science, Université libre de Bruxelles, Brussels, Belgium

Funder

Fonds De La Recherche Scientifique - FNRS

National Science Foundation

Publisher

ACM Press

Reference46 articles.

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3. Rakesh Agrawal, Christos Faloutsos, and Arun Swami. 1993. Efficient similarity search in sequence databases. Foundations of data organization and algorithms (1993), 69--84.

4. Alexandr Andoni and Piotr Indyk. 2006. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In IEEE Symp. on Foundations of Computer Science. 459--468.

5. Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, and Jörg Sander. 1999. OPTICS: Ordering Points to Identify the Clustering Structure. In Proc. of the ACM SIGMOD Intl. Conf. on Management of Data. 49--60.

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