%0 Generic %1 yadan2013multigpu %A Yadan, Omry %A Adams, Keith %A Taigman, Yaniv %A Ranzato, Marc'Aurelio %D 2013 %K deep dl large-scale networks neural %T Multi-GPU Training of ConvNets %U http://arxiv.org/abs/1312.5853 %X In this work we evaluate different approaches to parallelize computation of convolutional neural networks across several GPUs.

@misc{yadan2013multigpu, abstract = {In this work we evaluate different approaches to parallelize computation of convolutional neural networks across several GPUs.}, added-at = {2019-06-04T16:16:21.000+0200}, author = {Yadan, Omry and Adams, Keith and Taigman, Yaniv and Ranzato, Marc'Aurelio}, biburl = {https://www.bibsonomy.org/bibtex/22f9972b0a764829452c9c1d41a4b1f1f/alrigazzi}, description = {Multi-GPU Training of ConvNets}, interhash = {cab1c6892fff4b7adc5a1a2cdf041610}, intrahash = {2f9972b0a764829452c9c1d41a4b1f1f}, keywords = {deep dl large-scale networks neural}, note = {cite arxiv:1312.5853Comment: Machine Learning, Deep Learning, Convolutional Networks, Computer Vision, GPU, CUDA}, timestamp = {2019-06-04T16:16:21.000+0200}, title = {Multi-GPU Training of ConvNets}, url = {http://arxiv.org/abs/1312.5853}, year = 2013 }