Memory-efficient implementation of a graphics processor-based cluster detection algorithm for large spatial databases

2010 IEEE International Conference on Electro/Information Technology, EIT2010

Volumn , Issue , 2010, Pages

  Thapa, Rajeev J ^a   Trefftz, Christian ^a   Wolffe, Greg ^a  

^a GRAND VALLEY STATE UNIVERSITY   (United States)

Author keywords

Data mining; DBSCAN; GPU; Parallel computing; Spatial databases

Indexed keywords

ALGORITHM PERFORMANCE; CLUSTER DETECTION; DBSCAN; DENSITY-BASED SPATIAL CLUSTERING OF APPLICATIONS WITH NOISE; EFFICIENT IMPLEMENTATION; GENERAL PURPOSE; GPU; GPU IMPLEMENTATION; GRAPHICAL PROCESSING UNITS; GRAPHICS PROCESSOR; HIGH INTENSITY; PARALLEL COMPUTING; PARALLEL COMPUTING PLATFORM; SEQUENTIAL PROGRAMS; SPATIAL DATABASE; VERY LARGE DATABASE;

COMPUTER GRAPHICS EQUIPMENT; DATA MINING; DATABASE SYSTEMS; DISTRIBUTED COMPUTER SYSTEMS; PARALLEL ARCHITECTURES; PROGRAM PROCESSORS;

CLUSTERING ALGORITHMS;

EID: 78649289030     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EIT.2010.5612134     Document Type: Conference Paper

References (7)

1. nd ACM International Conference on Knowledge Discovery and Data Mining, KDD 1996, pp. 226-331.
2. X. Xu, J. Jager, and H-P. Kriegel, "A Fast Parallel Clustering Algorithm for Large Spatial Databases," Data Mining and KnowledgeDiscovery, 3, 3 (1999), pp263-290.
3. D. Arlia, and M. Coppola, "Experiments in parallel clustering with DBSCAN," Proc. of the 7th International Euro-Par Conference on Parallel Processing (London, UK, 2001), pp. 326-331.
4. A. Guttman, "R-Trees: A Dynamic Index structure for Spatial Searching," Proc. ACM SIGMOD International Conference on Management of Data, 1984, pp. 47-57.
5. NVIDIA CUDA Installation and Verification on Microsoft Windows XP and Windows Vista, DU-04165-001 Volume 1, NVIDIA Corporation, August 2008.
6. NVIDIA CUDA Programming Guide, Version 2.0, NVIDIA Corporation, June 2008.
7. C. Trefftz, I. Majdandzic, J. Szakas, and G. Wolffe, "Parallelized Implementation and Analysis of the DBSCAN Spatial Clustering Algorithm on Graphical Processing Units", submitted for publication.