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Assessment of various GPU acceleration strategies in text categorization processing flow

Lukasz Kordula, Maciej Wielgosz, Michal Karwatowski, Marcin Pietron, Dominik Zurek, Kazimierz Wiatr
AGH University of Science and Technology
Measurement Automation Monitoring, Vol. 63, No. 6, 2017

@article{kordula2017assessment,

   title={Assessment of various GPU acceleration strategies in text categorization processing flow},

   author={Kordu{l}a, {L}ukasz and Wielgosz, M and Karwatowski, M and Pietro{‘n}, M and {.Z}urek, D and Wiatr, K},

   journal={Measurement Automation Monitoring},

   volume={63},

   year={2017}

}

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Automatic text categorization presents many difficulties. Modern algorithms are getting better in extracting meaningful information from human language. However, they often significantly increase complexity of computations. This increased demand for computational capabilities can be facilitated by the usage of hardware accelerators like general purpose graphic cards. In this paper we present a full processing flow for document categorization system. Gram-Schmidt process signatures calculation up to 12 fold decrease in computing time of system components.
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