Fast 1-itemset frequency count using CUDA

College

College of Computer Studies

Department/Unit

Computer Technology

Document Type

Conference Proceeding

Source Title

IEEE Region 10 Annual International Conference, Proceedings/TENCON

First Page

210

Last Page

213

Publication Date

2-9-2017

Abstract

Frequent itemset mining is one of the main and compute-intensive operations in the field of data mining. The said algorithm is use in finding frequent patterns in transactional databases. The 1-itemset frequent count is used as basis for finding succeeding k-itemset mining. Thus there is a need to speed-up this process. One of the techniques to speed-up the process is using the Single Instruction Multiple Thread (SIMT) architecture. This architecture allows a single instruction to be applied to multiple threads at the same time. Current graphics processing unit (GPU), which contains multiple streaming processing units, uses SIMT architecture. In order to abstract the GPU hardware from the programming model, NVIDIA introduces the compute unified device architecture (CUDA) as an extension to existing programming languages in order to support SIMT. This paper discusses how 1-itemset frequent count is implemented in SIMT using CUDA.

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Digitial Object Identifier (DOI)

10.1109/TENCON.2016.7847991

Disciplines

Computer Sciences

Keywords

Data mining; Big data; CUDA (Computer architecture)

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