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Reseach Article

Parallelizing Apriori Algorithm on GPU

by K. Spandana, D. Sirisha, S. Shahida
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 10
Year of Publication: 2016
Authors: K. Spandana, D. Sirisha, S. Shahida
10.5120/ijca2016912449

K. Spandana, D. Sirisha, S. Shahida . Parallelizing Apriori Algorithm on GPU. International Journal of Computer Applications. 155, 10 ( Dec 2016), 22-27. DOI=10.5120/ijca2016912449

@article{ 10.5120/ijca2016912449,
author = { K. Spandana, D. Sirisha, S. Shahida },
title = { Parallelizing Apriori Algorithm on GPU },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 10 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume155/number10/26641-2016912449/ },
doi = { 10.5120/ijca2016912449 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:00:54.750824+05:30
%A K. Spandana
%A D. Sirisha
%A S. Shahida
%T Parallelizing Apriori Algorithm on GPU
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 10
%P 22-27
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Parallel computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently. Now Graphics Processing Unit (GPU) has taken a major role in high performance computing for generic applications. Compute Unified Device Architecture (CUDA) programming model provides the programmers adequate C-Language like API’s to better exploit the power of GPU. Data Mining has significant applications in various domains. Currently, these techniques cannot meet the requirement of applications with large scale databases in terms of computation and speed. Association Rules Mining (ARM) is one of the most widely used techniques in data mining and has tremendous applications. Apriori is the most influential ARM algorithm. It has been included in all the existing commercial and non-commercial data mining. This paper provides a parallel Apriori algorithm on GPU with CUDA and focuses on computation time compared with execution time of serial program in CPU.

References
  1. Parallel Optimized Algorithm for Apriori Association Rule Mining on Graphics Processing Unit with Compute Unified Device Architecture (CUDA) - By Abhaya Kumar Sahoo , Amardeep Das , Mayank Tiwary - Published in International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE) Volume 3, Issue 10, pp 121-1219, October 2013.
  2. Scalable Frequent Itemset Mining using Heterogeneous Computing: ParApriori Algorithm - By B. B. Meshram and V. B. Nikam - Published in International Journal of Distributed and Parallel Systems (IJDPS) Volume 5, Issue No.5, pp 13-26, September 2014.
  3. Parallel and distributed association mining: a survey. - By Zaki MJ - Published in IEEE Concurrency Volume 7, Issue 4, pp 14-25, October 1999.
  4. Parallel Data Mining on Graphics Processors - By Wenbin Fang, Ka Keung Lau, Mian Lu, Xiangye Xiao, Chi Kit Lam, Philip YangYang,Bingsheng He,Qiong Luo, Pedro V. Sander, and Ke Yang.
  5. GPApriori: GPU-Accelerated Frequent Itemset Mining - By Fan Zhang ,Yan Zhang,Jason Bakos - Published in IEEE International Conference on Cluster Computing,2011.
  6. High Speed Association Rule Mining using Apriori Based Algorithm for GPU - By D.William Albert,Dr.K.Fayaz and D.Veerabhadra Babu - Published in International Journal of Multidisciplinary and Current Research.
  7. Frequent Itemset Mining on Graphics Processors – By Wenbin Fang, Mian Lu, Xiao, Bingsheng He, Qiong Luo.
  8. Data mining: concepts and techniques, 2nd Edition. Morgan Kaufmann, SanMateo - By Han J, Kamber M (2005).
  9. Parallel Computing with CUDA - By Mark Harris (NVIDIA Developer Technology).
  10. Parallel Computing with CUDA - By Mark Harris (NVIDIA Developer Technology).
  11. Professional CUDA C Programming - By John Cheng,Max Grossman,Ty McKercher.
  12. CUDA by Example : An Introduction to General-Purpose GPU Programming - By Jason Sanders,Edward Kandrot.
  13. Parallel Programming with CUDA - By Ian Buck.
  14. Heterogeneous Parallel Programming (MOOC) - By University of Illinois https://www.coursera.org/course/hetero
  15. .Net Framework Programming
  16. Wikipedia, "Association Rule Learning", http://en.wikipedia.org/wiki/Association_rule_learning
  17. Wikipedia, "Apriori Algorithm", http://en.wikipedia.org/wiki/Apriori_algorithm
  18. Wikipedia, "Graphics Processing Unit", http://en.wikipedia.org/wiki/Graphics_processing_unit
  19. Wikipedia, "Parallel Computing", http://en.wikipedia.org/wiki/Parallel_computing
  20. Nvidia, "GEForce 210 Specifications", http://www.geforce.com/hardware/desktop-gpus/ geforce-210/specifications
  21. NVIDIA Developer Zone
  22. http://www.nvidia.com/object/what-is-gpu-computing.html
  23. CUDA Zone
  24. https://developer.nvidia.com/cuda-zone
  25. NVIDIA Parallel For All Blog
  26. http://devblogs.nvidia.com/parallelforall/
Index Terms

Computer Science
Information Sciences

Keywords

Parallel Computing GPGPU GPU CUDA Data Mining Parallel Apriori Algorithm