摘要
为解决铁路客运营销深度学习平台Tensorflow框架存在的环境配置复杂,资源利用率低、模型设计周期长等问题,提出了基于Kubernetes容器的PaaS平台构建TensorFlow容器的统一资源调度管理及API访问控制服务架构。经平台实践证明,该架构为客运营销提供了可靠、稳定的分析环境,降低了模型的训练难度,提高了模型的训练效率。
In order to solve the problems of complex environment configuration,low resource utilization and long model design cycle existing in Tensorflow framework of the deep learning platform for railway passenger marketing,this paper proposed a PAAS platform based on Kubernetes container to build a unified resource scheduling management and API access control service framework of Tensorflow container.The platform practice shows that the framework provides a reliable and stable analysis environment for passenger transport marketing,reduces the training difficulty of the model,and improves the training efficiency of the model.
作者
郝晓培
单杏花
李永
王炜炜
HAO Xiaopei;SHAN Xinghua;LI Yong;WANG Weiwei(Institute of Computing Technologies,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China;Beijing Jingwei Information Technology Co.Ltd.,Beijing 100081,China)
出处
《铁路计算机应用》
2021年第1期57-61,共5页
Railway Computer Application
基金
中国铁道科学研究院集团有限公司电子计算技术研究所创新基金(DZYF18-13)。
