Training Optimum-Path Forest on Graphics Processing Units

Adriana S. Iwashita, Marcos V. T. Romero, Alexandro Baldassin, Kelton A. P. Costa, Joao P. Papa

2014

Abstract

In this paper, we presented a Graphics Processing Unit (GPU)-based training algorithm for Optimum-Path Forest (OPF) classifier. The proposed approach employs the idea of a vector-matrix multiplication to speed up both traditional OPF training algorithm and a recently proposed Central Processing Unit (CPU)-based OPF training algorithm. Experiments in several public datasets have showed the efficiency of the proposed approach, which demonstrated to be up to 14 times faster for some datasets. To the best of our knowledge, this is the first GPU-based implementation for OPF training algorithm.

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Paper Citation


in Harvard Style

S. Iwashita A., V. T. Romero M., Baldassin A., A. P. Costa K. and P. Papa J. (2014). Training Optimum-Path Forest on Graphics Processing Units . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 581-588. DOI: 10.5220/0004737805810588


in Bibtex Style

@conference{visapp14,
author={Adriana S. Iwashita and Marcos V. T. Romero and Alexandro Baldassin and Kelton A. P. Costa and Joao P. Papa},
title={Training Optimum-Path Forest on Graphics Processing Units},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={581-588},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004737805810588},
isbn={978-989-758-004-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)
TI - Training Optimum-Path Forest on Graphics Processing Units
SN - 978-989-758-004-8
AU - S. Iwashita A.
AU - V. T. Romero M.
AU - Baldassin A.
AU - A. P. Costa K.
AU - P. Papa J.
PY - 2014
SP - 581
EP - 588
DO - 10.5220/0004737805810588