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https://doi.org/10.2498/cit.1002361

Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors

Khedija Arour ; Computer Science Department, National Institute of Applied Sciences and Technology, Tunis
Amani Belkahla ; Computer Science Department, Faculty of Sciences of Tunis

Puni tekst: engleski, PDF (738 KB) str. 159-169 preuzimanja: 941* citiraj
APA 6th Edition
Arour, K. i Belkahla, A. (2014). Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors. Journal of computing and information technology, 22 (3), 159-169. https://doi.org/10.2498/cit.1002361
MLA 8th Edition
Arour, Khedija i Amani Belkahla. "Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors." Journal of computing and information technology, vol. 22, br. 3, 2014, str. 159-169. https://doi.org/10.2498/cit.1002361. Citirano 01.03.2021.
Chicago 17th Edition
Arour, Khedija i Amani Belkahla. "Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors." Journal of computing and information technology 22, br. 3 (2014): 159-169. https://doi.org/10.2498/cit.1002361
Harvard
Arour, K., i Belkahla, A. (2014). 'Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors', Journal of computing and information technology, 22(3), str. 159-169. https://doi.org/10.2498/cit.1002361
Vancouver
Arour K, Belkahla A. Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors. Journal of computing and information technology [Internet]. 2014 [pristupljeno 01.03.2021.];22(3):159-169. https://doi.org/10.2498/cit.1002361
IEEE
K. Arour i A. Belkahla, "Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors", Journal of computing and information technology, vol.22, br. 3, str. 159-169, 2014. [Online]. https://doi.org/10.2498/cit.1002361

Sažetak

Discovering association rules that identify relationships among sets of items is an important problem in data mining. It’s a two steps process, the first step finds all frequent itemsets and the second one constructs association rules from these frequent sets. Finding frequent itemsets is computationally the most expensive step in association rules discovery algorithms. Utilizing parallel architectures has been a viable means for improving FIM algorithms performance. We present two FP-growth implementations that take advantage of multi-core processors and utilize new generation Graphic Processing Units (GPU).

Ključne riječi
association rule mining; frequent itemset mining; GPU computing; parallel computing; GPGPU

Hrčak ID: 129192

URI
https://hrcak.srce.hr/129192

Posjeta: 1.139 *