Acceleration of multivariate analysis techniques in TMVA using GPUs
CERN, Switzerland
Journal of Physics: Conference Series Volume 396, Part 2, 2012
@article{1742-6596-396-2-022055,
author={A Hoecker and H McKendrick and J Therhaag and A Washbrook},
title={Acceleration of multivariate analysis techniques in TMVA using GPUs},
journal={Journal of Physics: Conference Series},
volume={396},
number={2},
pages={022055},
url={http://stacks.iop.org/1742-6596/396/i=2/a=022055},
year={2012}
}
A feasibility study into the acceleration of multivariate analysis techniques using Graphics Processing Units (GPUs) will be presented. The MLP-based Artificial Neural Network method contained in the TMVA framework has been chosen as a focus for investigation. It was found that the network training time on a GPU was lower than for CPU execution as the complexity of the network was increased. In addition, multiple neural networks can be trained simultaneously on a GPU within the same time taken for single network training on a CPU. This could be potentially leveraged to provide a qualitative performance gain in data classification.
December 16, 2012 by hgpu
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