Patent · US Active

Method for distributed type training adaptation and apparatus in deep learning framework and AI accelerator card

US11714995B2 · kind B2 · utility

4Cited by

1References

17Claims

0Family size

Assignee

ZHEJIANG LAB · CN

Inventors

Hongsheng Wang · Elmhurst, US
Hujun Bao · Hangzhou City, CN
Wei Hua · Hangzhou City, CN
Weiqiang Jia · Hangzhou City, CN

Key dates

Filing date	May 9, 2022
Grant date	Aug 1, 2023
Priority date	—
Expiry date	Aug 13, 2042

Classification

Technology area (CPC G)Physics
CPC primaryG06N3/105
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Disclosed is a method for distributed type training adaptation and apparatus in a deep learning framework and an AI accelerator card. The method includes the following steps: S1: the deep learning framework supports single-card configuration in a newly added AI accelerator card, and sub-steps thereof are as follows: S11: the deep learning framework supports new hardware; S12: the deep learning framework supports a device thread of the new hardware; S13: the deep learning framework supports a memory operation of the new hardware; and S14: the deep learning framework supports an operator kernel function of the new hardware; S2: the deep learning framework supports multi-card configuration in the newly added AI accelerator card; S3: the deep learning framework supports tensor segmentation and multi-card distribution; and S4: the deep learning framework supports multi-card collective communication in the newly added AI accelerator card.

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