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The past few years have witnessed growth in the computational requirements for training deep convolutional neural networks.
Face recognition: A convolutional neural-network approach
Lawrence, S., Giles, C. L., Tsoi, A. C., and Back, A. D · 1997
Earlier work this paper cites.
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Legion: Expressing locality and independence with logical regions
Bauer, M., Treichler, S., Slaughter, E., and Aiken, A · 2012
Earlier work this paper cites.
Large scale distributed deep networks
Dean, J., Corrado, G. S., Monga, R., Chen, K., Devin, M., Le, Q. V., Mao, M. Z., Ranzato, M., Senior, A., Tucker, P., Yang, K., and Ng, A. Y · 2012
Earlier work this paper cites.
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., and Hinton, G. E · 2012
Earlier work this paper cites.
End-to-end text recognition with convolutional neural networks
Wang, T., Wu, D. J., Coates, A., and Ng, A. Y · 2012
Earlier work this paper cites.
cudnn: Efficient primitives for deep learning
Chetlur, S., Woolley, C., Vandermersch, P., Cohen, J., Tran, J., Catanzaro, B., and Shelhamer, E · 2014
Earlier work this paper cites.
One weird trick for parallelizing convolutional neural networks
Krizhevsky, A · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Simonyan, K. and Zisserman, A · 2014
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Realm: An event-based low-level runtime for distributed memory architectures
Treichler, S., Bauer, M., and Aiken, A · 2014
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Visualizing and understanding convolutional networks
Zeiler, M. D. and Fergus, R · 2014
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Learning both weights and connections for efficient neural networks
Han, S., Pool, J., Tran, J., and Dally, W. J · 2015
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https://developer.nvidia.com/cublas , 2016
Dense Linear Algebra on GPUs · 2016
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Tensorflow: A system for large-scale machine learning
Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D. G., Steiner, B., Tucker, P., Vasudevan, V., Warden, P., Wicke, M., Yu, Y., and Zheng, X · 2016
Mastering the game of go with deep neural networks and tree search
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al · 2016
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Rethinking the inception architecture for computer vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., and Wojna, Z · 2016
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Accurate, large minibatch SGD: training imagenet in 1 hour
Goyal, P., Dollár, P., Girshick, R. B., Noordhuis, P., Wesolowski, L., Kyrola, A., Tulloch, A., Jia, Y., and He, K · 2017
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A distributed multi-gpu system for fast graph processing
Jia, Z., Kwon, Y., Shipman, G., McCormick, P., Erez, M., and Aiken, A · 2017
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SplitNet: Learning to semantically split deep networks for parameter reduction and model parallelization
Kim, J., Park, Y., Kim, G., and Hwang, S. J · 2017
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Learning the number of neurons in deep networks
Alvarez, J. M. and Salzmann, M · 2016
Cited alongside, same era.
Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
Cited alongside, same era.
Device placement optimization with reinforcement learning
Mirhoseini, A., Pham, H., Le, Q. V., Steiner, B., Larsen, R., Zhou, Y., Kumar, N., Norouzi, M., Bengio, S., and Dean, J · 2017
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Poseidon: An efficient communication architecture for distributed deep learning on GPU clusters
Zhang, H., Zheng, Z., Xu, S., Dai, W., Ho, Q., Liang, X., Hu, Z., Wei, J., Xie, P., and Xing, E. P · 2017
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Isometry: A path-based distributed data transfer system
Jia, Z., Treichler, S., Shipman, G., McCormick, P., and Aiken, A · 2018
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