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滴滴机器学习平台架构演进 - InfoQ

滴滴机器学习平台架构演进-InfoQ
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Summary | 15 Annotations
GPU 的服务器选型
2020/07/22 04:56
资源统一管理
2020/07/22 04:59
避免重复性
2020/07/22 04:59
Caffe、TensorFlow、PyTorch
2020/07/22 05:00
Yarn 做了扩展以支持 GPU 资源维度
2020/07/22 05:00
Notebook、Jupyter 的交互接口
2020/07/22 05:00
复用性和规模化能力
2020/07/22 05:10
运行环境
2020/07/22 05:12
平台所要解决的问题
2020/07/22 05:14
技术选型
2020/07/22 05:14
大同小异
2020/07/22 05:17
减少重复、提高效率
2020/07/22 05:18
资源管理、环境管理
2020/07/22 10:35
数据共享
2020/07/22 10:35
GPU 拓扑、CPU 亲和性等硬件属性来提高性能
2020/07/22 10:38