ImageNet Training in Minutes
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James Demmel | Kurt Keutzer | Zhao Zhang | Cho-Jui Hsieh | Yang You | Yang You | J. Demmel | Cho-Jui Hsieh | K. Keutzer | Zhao Zhang
[1] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[2] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[3] Rolf Rabenseifner,et al. Optimization of Collective Reduction Operations , 2004, International Conference on Computational Science.
[4] Kaiming He,et al. Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour , 2017, ArXiv.
[5] Chong Wang,et al. Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin , 2015, ICML.
[6] Nicholas G. Polson,et al. Deep Learning in Finance , 2016, ArXiv.
[7] Ioannis Mitliagkas,et al. Asynchrony begets momentum, with an application to deep learning , 2016, 2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[8] Jesper Larsson Träff,et al. More Efficient Reduction Algorithms for Non-Power-of-Two Number of Processors in Message-Passing Parallel Systems , 2004, PVM/MPI.
[9] Jorge Nocedal,et al. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima , 2016, ICLR.
[10] Samy Bengio,et al. Revisiting Distributed Synchronous SGD , 2016, ArXiv.
[11] Stephen J. Wright,et al. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent , 2011, NIPS.
[12] Avinash Wesley,et al. Sequence Mining and Pattern Analysis in Drilling Reports with Deep Natural Language Processing , 2017, Day 3 Wed, September 26, 2018.
[13] Dong Yu,et al. On parallelizability of stochastic gradient descent for speech DNNS , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[14] Pradeep Dubey,et al. Distributed Deep Learning Using Synchronous Stochastic Gradient Descent , 2016, ArXiv.
[15] Tao Wang,et al. Deep learning with COTS HPC systems , 2013, ICML.
[16] Forrest N. Iandola,et al. How to scale distributed deep learning? , 2016, ArXiv.
[17] Marc'Aurelio Ranzato,et al. Building high-level features using large scale unsupervised learning , 2011, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[18] Rajeev Thakur,et al. Optimization of Collective Communication Operations in MPICH , 2005, Int. J. High Perform. Comput. Appl..
[19] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Alex Krizhevsky,et al. One weird trick for parallelizing convolutional neural networks , 2014, ArXiv.
[21] Anthony Skjellum,et al. A High-Performance, Portable Implementation of the MPI Message Passing Interface Standard , 1996, Parallel Comput..
[22] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[23] Mu Li. Proposal Scaling Distributed Machine Learning with System and Algorithm Co-design , 2016 .
[24] Yann LeCun,et al. Deep learning with Elastic Averaging SGD , 2014, NIPS.
[25] Jack Dongarra,et al. TOP500 Supercomputer sites 11/2000 , 2000 .
[26] Ronald M. Summers,et al. Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique , 2016 .
[27] Dong Yu,et al. 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs , 2014, INTERSPEECH.
[28] Robert A. van de Geijn,et al. On Global Combine Operations , 1994, J. Parallel Distributed Comput..
[29] James Demmel,et al. ImageNet Training by CPU: AlexNet in 11 Minutes and ResNet-50 in 48 Minutes , 2017 .
[30] Takuya Akiba,et al. Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes , 2017, ArXiv.
[31] Forrest N. Iandola,et al. FireCaffe: Near-Linear Acceleration of Deep Neural Network Training on Compute Clusters , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Yang You,et al. Scaling SGD Batch Size to 32K for ImageNet Training , 2017, ArXiv.