公开(公告)号：US11782723B1

公开(公告)日：2023-10-10

申请号：US17992830

申请日：2022-11-22

Applicant: ZHEJIANG LAB

Inventor： Hongsheng Wang ,  Guang Chen ,  Lingfang Zeng ,  Aimin Pan

IPC: G06F8/40 ,  G06F9/38 ,  G06F8/41

CPC classification number: G06F9/3885 ,  G06F8/433 ,  G06F8/443

Abstract: Disclosed are an intermediate representation method and apparatus for parallel execution of graph computation. The method includes the following steps: S1: compiling a neural network into a computational graph on a computer; S2: defining branch states of tensor variables in the computational graph; S3: defining a data dependency relationship of the tensor variables in the computational graph; S4: defining a control dependency relationship of the tensor variables in the computational graph; S5: building a data dependency relationship graph of the tensor variables in the computational graph; S6: building a control dependency relationship graph of the tensor variables in the computational graph; and S7: transforming control dependencies into data dependencies. The present application derives, based on the dependency relationship, a parallel computing method that can execute the branch threads in parallel in the global computational graph, and optimizes the compilation efficiency of the computational graph.