Theano-based Large-Scale Visual Recognition with Multiple GPUs
作者： Weiguang Ding , Graham Taylor , Fei Mao , Ruoyan Wang
DOI:
关键词: Computer science 、 Visual recognition 、 Theano 、 Parallel computing 、 Data parallelism 、 Computational science 、 Python (programming language)
摘要: In this report, we describe a Theano-based AlexNet (Krizhevsky et al., 2012) implementation and its naive data parallelism on multiple GPUs. Our performance 2 GPUs is comparable with the state-of-art Caffe library (Jia 2014) run 1 GPU. To best of our knowledge, first open-source Python-based to-date.
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128.84.21.199参考文章(11)
Ronan Collobert, Clément Farabet, Koray Kavukcuoglu, Torch7: A Matlab-like Environment for Machine Learning neural information processing systems. ,(2011)
Alex Krizhevsky, One weird trick for parallelizing convolutional neural networks arXiv: Neural and Evolutionary Computing. ,(2014)
Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian Goodfellow, Arnaud Bergeron, Nicolas Bouchard, David Warde-Farley, Yoshua Bengio, None, Theano: new features and speed improvements arXiv: Symbolic Computation. ,(2012)
Evan Shelhamer, John Tran, Jonathan Cohen, Sharan Chetlur, Philippe Vandermersch, Cliff Woolley, Bryan Catanzaro, cuDNN: Efficient Primitives for Deep Learning arXiv: Neural and Evolutionary Computing. ,(2014)
Ian J Goodfellow, David Warde-Farley, Pascal Lamblin, Vincent Dumoulin, Mehdi Mirza, Razvan Pascanu, James Bergstra, Frédéric Bastien, Yoshua Bengio, None, Pylearn2: a machine learning research library arXiv: Machine Learning. ,(2013)
Andreas Klöckner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih, PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation parallel computing. ,vol. 38, pp. 157- 174 ,(2012) , 10.1016/J.PARCO.2011.09.001
Y. Lecun, L. Bottou, Y. Bengio, P. Haffner, Gradient-based learning applied to document recognition Proceedings of the IEEE. ,vol. 86, pp. 2278- 2324 ,(1998) , 10.1109/5.726791
Jianchao Yang, Hailin Jin, Zhe Lin, Thomas Paine, Thomas Huang, GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training arXiv: Computer Vision and Pattern Recognition. ,(2013)
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, Li Fei-Fei, ImageNet Large Scale Visual Recognition Challenge International Journal of Computer Vision. ,vol. 115, pp. 211- 252 ,(2015) , 10.1007/S11263-015-0816-Y
José María Canal Sánchez-Pagín, Mariana Proceedings of the VLDB Endowment. ,vol. 7, pp. 1772- 1777 ,(2014) , 10.14778/2733004.2733082