Theano-Based Large-Scale Visual Recognition with Multiple GPUs
Abstract
In this report, we describe a Theano-based AlexNet (Krizhevsky et al., 2012) implementation and its naive data parallelism on multiple GPUs. Our performance on 2 GPUs is comparable with the state-of-art Caffe library (Jia et al., 2014) run on 1 GPU. To the best of our knowledge, this is the first open-source Python-based AlexNet implementation to-date.
Cite
Text
Ding et al. "Theano-Based Large-Scale Visual Recognition with Multiple GPUs." International Conference on Learning Representations, 2015.Markdown
[Ding et al. "Theano-Based Large-Scale Visual Recognition with Multiple GPUs." International Conference on Learning Representations, 2015.](https://mlanthology.org/iclr/2015/ding2015iclr-theano/)BibTeX
@inproceedings{ding2015iclr-theano,
title = {{Theano-Based Large-Scale Visual Recognition with Multiple GPUs}},
author = {Ding, Weiguang and Wang, Ruoyan and Mao, Fei and Taylor, Graham W.},
booktitle = {International Conference on Learning Representations},
year = {2015},
url = {https://mlanthology.org/iclr/2015/ding2015iclr-theano/}
}