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GPUSVM: a comprehensive CUDA based support vector machine package

Qi Li
  • Virginia Commonwealth University, Richmond, VA, 23284, USA
  • Email:
/ Raied Salman
  • Virginia Commonwealth University, Richmond, VA, 23284, USA
  • Email:
/ Erik Test
  • Virginia Commonwealth University, Richmond, VA, 23284, USA
  • Email:
/ Robert Strack
  • Virginia Commonwealth University, Richmond, VA, 23284, USA
  • Email:
/ Vojislav Kecman
  • Virginia Commonwealth University, Richmond, VA, 23284, USA
  • Email:
Published Online: 2011-12-27 | DOI: https://doi.org/10.2478/s13537-011-0028-7

Abstract

GPUSVM (Graphic Processing Unit Support Vector Machine) is a Computing Unified Device Architecture (CUDA) based Support Vector Machine (SVM) package. It is designed to offer an end-user a fully functional and user friendly SVM tool which utilizes the power of GPUs. The core package includes an efficient cross validation tool, a fast training tool and a predicting tool. In this article, we first introduce the background theory of how we build our parallel SVM solver using CUDA programming model. Then we compare our GPUSVM package with the popular state of the art Libsvm package on several well known datasets. The preliminary results have shown one to two orders of magnitude speed improvement in both training and predicting phases compared to Libsvm using our Tesla server.

Keywords: parallel support vector machine; CUDA; GPU; cross validation

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About the article

Published Online: 2011-12-27

Published in Print: 2011-12-01



Citation Information: Open Computer Science, ISSN (Online) 2299-1093, DOI: https://doi.org/10.2478/s13537-011-0028-7. Export Citation

© 2011 Versita Warsaw. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)

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