arXiv · 1605.08325
Theano-MPI: a Theano-based Distributed Training Framework
Abstract
We develop a scalable and extendable training framework that can utilize GPUs across nodes in a cluster and accelerate the training of deep learning models based on data parallelism. Both synchronous and asynchronous training are implemented in our framework, where parameter exchange among GPUs is based on CUDA-aware MPI. In this report, we analyze the convergence and capability of the framework to reduce training time when scaling the synchronous training of AlexNet and GoogLeNet from 2 GPUs to 8 GPUs. In addition, we explore novel ways to reduce the communication overhead caused by exchanging parameters. Finally, we release the framework as open-source for further research on distributed deep learning
Explore related subjects
Keep this discovery
He Ma, Fei Mao, Graham W. Taylor. 2016-05-26. Theano-MPI: a Theano-based Distributed Training Framework. https://arxiv.org/abs/1605.08325
Cite the original work for its findings. Save a collection to share your selection of sources.