Acceleration of multivariate analysis techniques in TMVA using GPUs

A. Hoecker, H. McKendrick, J. Therhaag, A. Washbrook
CERN, Switzerland
Journal of Physics: Conference Series Volume 396, Part 2, 2012


   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},







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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.
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