Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks

11 Dec 2017Hao ZhangShizhen XuGraham NeubigWei DaiQirong HoGuangwen YangEric P. Xing

Recent deep learning (DL) models have moved beyond static network architectures to dynamic ones, handling data where the network structure changes every example, such as sequences of variable lengths, trees, and graphs. Existing dataflow-based programming models for DL---both static and dynamic declaration---either cannot readily express these dynamic models, or are inefficient due to repeated dataflow graph construction and processing, and difficulties in batched execution... (read more)

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