Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning
Machine Intelligence Laboratory, Department of Mechano-Informatics, The University of Tokyo
arXiv:1503.05743 [cs.DC], (19 Mar 2015)
@article{miura2015implementation,
title={Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning},
author={Miura, Ken and Harada, Tatsuya},
year={2015},
month={mar},
archivePrefix={"arXiv"},
primaryClass={cs.DC}
}
Deep learning can achieve outstanding results in various fields. However, it requires so significant computational power that graphics processing units (GPUs) and/or numerous computers are often required for the practical application. We have developed a new distributed calculation framework called "Sashimi" that allows any computer to be used as a distribution node only by accessing a website. We have also developed a new JavaScript neural network framework called "Sukiyaki" that uses general purpose GPUs with web browsers. Sukiyaki performs 30 times faster than a conventional JavaScript library for deep convolutional neural networks (deep CNNs) learning. The combination of Sashimi and Sukiyaki, as well as new distribution algorithms, demonstrates the distributed deep learning of deep CNNs only with web browsers on various devices. The libraries that comprise the proposed methods are available under MIT license at this http URL.
March 20, 2015 by hgpu
