公开(公告)号：US20230274129A1

公开(公告)日：2023-08-31

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

IPC: G06N3/063 ,  G06N3/08

CPC classification number: G06N3/063 ,  G06N3/08

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.