Fast Support Vector Machine Training and Classification (2008)
| Venue: | on Graphics Processors, Proc. 25th Int. Conf. Machine Learning |
| Citations: | 24 - 0 self |
BibTeX
@INPROCEEDINGS{Catanzaro08fastsupport,
author = {Bryan Catanzaro and Narayanan Sundaram and Kurt Keutzer},
title = {Fast Support Vector Machine Training and Classification},
booktitle = {on Graphics Processors, Proc. 25th Int. Conf. Machine Learning},
year = {2008},
pages = {104--111}
}
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Abstract
Recent developments in programmable, highly parallel Graphics Processing Units (GPUs) have enabled high performance implementations of machine learning algorithms. We describe a solver for Support Vector Machine training running on a GPU, using the Sequential Minimal Optimization algorithm and an adaptive first and second order working set selection heuristic, which achieves speedups of 9-35 × over LIBSVM running on a traditional processor. We also present a GPU-based system for SVM classification which achieves speedups of 81-138 × over LIBSVM (5-24 × over our own CPU based SVM classifier). 1.
