Patent · US Active

Method for execution of computational graph in neural network model and apparatus thereof

US11941514B2 · kind B2 · utility

0Cited by

1References

13Claims

0Family size

Assignee

ZHEJIANG LAB · CN

Inventors

Hongsheng Wang · Elmhurst, US
Hujun Bao · Hangzhou City, CN
Guang Chen · Hangzhou City, CN
Lingfang ZENG · Hangzhou City, CN
Hongcai Cheng · Hangzhou City, CN
Yong Li · San Diego, US
Jian Ping Zhu · Lo Wu, CN
Huanbo Zheng · Hangzhou City, CN

Key dates

Filing date	Mar 29, 2022
Grant date	Mar 26, 2024
Priority date	—
Expiry date	Aug 12, 2042

Classification

Technology area (CPC Y)Emerging Cross-Sectional Technologies
CPC primaryY02D10/00
WIPO fieldComputer technology
WIPO sectorElectrical engineering

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.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.