JavaScript-based深度学习平台的开发及其在分布式训练中的应用
Development of JavaScript-based deep learning platform and application to distributed training
摘要：
深度学习在处理大数据方面越来越受到关注。现有的深度学习框架必须建立在专门的计算机系统上。因此，获得足够的计算资源需要高昂的部署和维护成本。在这项工作中，我们实现了一个矩阵库和使用JavaScript的深度学习框架。它可以在普通个人电脑和智能手机上运行的Web浏览器上运行。使用JavaScript，深度学习可以在各种各样的环境中完成，而无需安装软件。利用WebCL框架中的GPGPU，我们的框架可以训练大规模的卷积神经网络，如VGGNet和ResNet。在实验中，我们通过使用Web浏览器作为客户端以分布式方式训练VGGNet来展示其实用性。
英文摘要：
Deep learning is increasingly attracting attention for processing big data. Existing frameworks for deep learning must be set up to specialized computer systems. Gaining sufficient computing resources therefore entails high costs of deployment and maintenance. In this work, we implement a matrix library and deep learning framework that uses JavaScript. It can run on web browsers operating on ordinary personal computers and smartphones. Using JavaScript, deep learning can be accomplished in widely diverse environments without the necessity for software installation. Using GPGPU from WebCL framework, our framework can train large scale convolutional neural networks such as VGGNet and ResNet. In the experiments, we demonstrate their practicality by training VGGNet in a distributed manner using web browsers as the client.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
