The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 26, 2025

Filed:

Jun. 10, 2022
Applicants:

Baidu Usa Llc, Sunnyvale, CA (US);

Baidu.com Times Technology (Beijing) Co., Ltd., Beijing, CN;

Inventors:

Haofeng Kou, Sunnyvale, CA (US);

Davy Huang, Sunnyvale, CA (US);

Manjiang Zhang, Sunnyvale, CA (US);

Xing Li, Sunnyvale, CA (US);

Lei Wang, Beijing, CN;

Huimeng Zheng, Beijing, CN;

Zhen Chen, Beijing, CN;

Ruichang Cheng, Beijing, CN;

Assignees:

BAIDU USA LLC, Sunnyvale, CA (US);

BAIDU.COM TIMES TECHNOLOGY (BEIJING) CO., LTD., Ca Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/50 (2006.01); G06F 9/54 (2006.01); G06N 3/0442 (2023.01); G06N 3/0464 (2023.01); G06N 3/08 (2023.01); G06N 5/04 (2023.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01);
U.S. Cl.
CPC ...
G06F 9/5066 (2013.01); G06F 9/5016 (2013.01); G06F 9/5044 (2013.01); G06F 9/5061 (2013.01); G06F 9/544 (2013.01); G06N 3/0442 (2023.01); G06N 3/0464 (2023.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06F 2209/5017 (2013.01); G06F 2209/503 (2013.01);
Abstract

A system obtains a performance profile corresponding to times taken to perform an inferencing by a machine learning (ML) model using a different number of processing resources from a plurality of processing resources. The system determines one or more groupings of processing resources from the plurality of processing resources, each grouping includes one or more partitions. The system calculates performance speeds corresponding to each grouping based on the performance profile. The system determines a grouping having a best performance speed from the calculated performance speeds. The system partitions the processing resources based on the determined grouping to perform the inferencing.


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