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I present a new way to parallelize the training of convolutional neural networks across multiple GPUs.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Hogwild!: A lock-free approach to parallelizing stochastic gradient descent
Feng Niu, Benjamin Recht, Christopher Ré, and Stephen J Wright · 2011
Earlier work this paper cites.
Large scale distributed deep networks
Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V Le, Mark Z Mao, Marc’Aurelio Ranzato, Andrew W Senior, Paul A Tucker, et al · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Deep learning with cots hpc systems
Adam Coates, Brody Huval, Tao Wang, David Wu, Bryan Catanzaro, and Ng Andrew · 2013
Cited alongside, same era.
Gpu asynchronous stochastic gradient descent to speed up neural network training
Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin, and Thomas Huang · 2013
Later among the works it cites.
Multi-gpu training of convnets
Omry Yadan, Keith Adams, Yaniv Taigman, and Marc’Aurelio Ranzato · 2013
Later among the works it cites.
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