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Authors: Amila De Silva and Shehan Perera

Affiliation: Department of Computer Science & Engineering, University of Moratuwa, Katubedda and Sri Lanka

Keyword(s): Data Mining, Classification, Bitmaps, Bit-Slices, GPU.

Related Ontology Subjects/Areas/Topics: Architectural Concepts ; Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Analytics ; Data Engineering ; Data Management and Quality ; Data Mining ; Database Architecture and Performance ; Databases and Data Security ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: Bitmaps are gaining popularity with Data Mining Applications that use GPUs, since Memory organisation and the design of a GPU demands for regular & simple structures. However, absence of a common framework has limited the benefits of Bitmaps & GPUs mostly to Frequent Itemset Mining (FIM) algorithms. We in this paper, present a framework based on Bitmap techniques, that speeds up Classification Algorithms on GPUs. The proposed framework which uses both CPU and GPU for Algorithm execution, delegates compute intensive operations to GPU. We implement two Classification Algorithms Naíve Bayes and Decision Trees, using the framework, both which outperform CPU counterparts by several orders of magnitude.

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Paper citation in several formats:
De Silva, A. and Perera, S. (2019). A Parallel Bit-map based Framework for Classification Algorithms. In Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-377-3; ISSN 2184-285X, SciTePress, pages 259-266. DOI: 10.5220/0007931202590266

@conference{data19,
author={Amila {De Silva}. and Shehan Perera.},
title={A Parallel Bit-map based Framework for Classification Algorithms},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA},
year={2019},
pages={259-266},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007931202590266},
isbn={978-989-758-377-3},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA
TI - A Parallel Bit-map based Framework for Classification Algorithms
SN - 978-989-758-377-3
IS - 2184-285X
AU - De Silva, A.
AU - Perera, S.
PY - 2019
SP - 259
EP - 266
DO - 10.5220/0007931202590266
PB - SciTePress