11137

Single Server Multi-GPU Training of ConvNets

Omry Yadan, Keith Adams, Yaniv Taigman, Marc’Aurelio Ranzato
Facebook AI Group
arXiv:1312.5853 [cs.LG], (20 Dec 2013)

@article{2013arXiv1312.5853Y,

   author={Yadan}, O. and {Adams}, K. and {Taigman}, Y. and {Ranzato}, M.},

   title={"{Single Server Multi-GPU Training of ConvNets}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1312.5853},

   primaryClass={"cs.LG"},

   keywords={Computer Science – Learning, Computer Science – Neural and Evolutionary Computing},

   year={2013},

   month={dec},

   adsurl={http://adsabs.harvard.edu/abs/2013arXiv1312.5853Y},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

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In this work we evaluate different approaches to parallelize computation of convolutional neural networks across several GPUs within the same server.
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