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公开(公告)号:US11941514B2
公开(公告)日:2024-03-26
申请号:US17706734
申请日:2022-03-29
Applicant: ZHEJIANG LAB
Inventor: Hongsheng Wang , Hujun Bao , Guang Chen , Lingfang Zeng , Hongcai Cheng , Yong Li , Jian Zhu , Huanbo Zheng
Abstract: The present disclosure discloses a method for execution of a computational graph in a neural network model and an apparatus thereof, including: creating task execution bodies on a native machine according to a physical computational graph compiled and generated by a deep learning framework, and designing a solution for allocating a plurality of idle memory blocks to each task execution body, so that the entire computational graph participates in deep learning training tasks of different batches of data in a pipelining and parallelizing manner.