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Distributed Training of Deep Neural Networks: Theoretical and Practical Limits of Parallel Scalability
Free access| ArXiv | 2016 -
Balancing the Communication Load of Asynchronously Parallelized Machine Learning Algorithms
Free access| ArXiv | 2015 -
Asynchronous parallel stochastic gradient descent: A numeric core for scalable distributed machine learning algorithms
Free access| Fraunhofer Publica | 2015 -
Balancing the communication load of asynchronously parallelized machine learning algorithms
Free access| Fraunhofer Publica | 2015 -
Using GPI-2 for distributed memory paralleliziation of the caffe toolbox to speed up deep neural network training
Free access| Fraunhofer Publica | 2017
