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:
Jan. 07, 2025

Filed:

Nov. 27, 2020
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Can Karakus, Redwood City, CA (US);

Rahul Raghavendra Huilgol, San Jose, CA (US);

Anirudh Subramanian, Redwood City, CA (US);

Fei Wu, Sunnyvale, CA (US);

Christopher Cade Daniel, San Jose, CA (US);

Akhil Mehra, Saratoga, CA (US);

Ajay Paidi, Newark, CA (US);

Yutong Zhang, Belmont, CA (US);

Indu Thangakrishnan, Santa Clara, CA (US);

Luis Alves Pereira Quintela, Mountain View, CA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 18/21 (2023.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06F 9/54 (2006.01); G06F 18/211 (2023.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06F 18/2163 (2023.01); G06F 9/4881 (2013.01); G06F 9/5066 (2013.01); G06F 9/54 (2013.01); G06F 18/211 (2023.01); G06N 20/00 (2019.01); G06F 2209/5017 (2013.01);
Abstract

Automatic partitioning of a machine learning model may be performed for training across multiple processing devices. A training job for a machine learning model may specify a number of partitions for a machine learning model. An optimization parameter may be determined for the machine learning model. Different partitions of the machine learning model to be trained across multiple processing devices may be determined based on the specified number of partitions and the optimization parameter. A schedule for executing the training job may be generated according to the respective partitions of the machine learning model. The training job may be executed according to the schedule.


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