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.

Patent No.:

US 11995448 B1

Date of Patent:

May. 28, 2024

Filed:

Oct. 26, 2021

Method and apparatus for performing machine learning operations in parallel on machine learning hardware

Applicant:

Marvell Asia Pte Ltd, Singapore, SG;

Inventors:

Avinash Sodani, San Jose, CA (US);

Ulf Hanebutte, Gig Harbor, WA (US);

Chien-Chun Chou, Morgan Hill, CA (US);

Harri Hakkarainen, Los Gatos, CA (US);

Assignee:

Marvell Asia Pte Ltd, Singapore, SG;

Attorney:

Primary Examiner:

Philip Wang

Int. Cl.

CPC ...

G06F 8/41 (2018.01); G06F 9/30 (2018.01); G06F 9/38 (2018.01); G06F 15/78 (2006.01); G06F 17/16 (2006.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06F 15/80 (2006.01); G06N 5/04 (2023.01); G06N 20/20 (2019.01);

U.S. Cl.

CPC ...

G06F 9/3879 (2013.01); G06F 8/45 (2013.01); G06F 8/453 (2013.01); G06F 9/30174 (2013.01); G06F 9/3836 (2013.01); G06F 9/3851 (2013.01); G06F 9/3877 (2013.01); G06F 15/7807 (2013.01); G06F 17/16 (2013.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06F 9/3001 (2013.01); G06F 15/7864 (2013.01); G06F 15/8023 (2013.01); G06F 2212/602 (2013.01); G06N 5/04 (2013.01); G06N 20/20 (2019.01);

Abstract

A method includes receiving a first set of data. The method also includes receiving an instruction to determine a largest value within the first set of data. The first set of data is divided into a first plurality of data portions based on a hardware architecture of a first plurality of processing elements. The first plurality of data portions is mapped to the first plurality of processing elements. Each data portion of the first plurality of data portions is mapped exclusively to a processing element of the first plurality of processing elements. Each data portion of the first plurality of data portions is processed by its respective processing element to identify a largest value from each data portion of the first plurality of data portions, wherein the processing forms a first output data comprising the largest value from the each data portion of the first plurality of data portions.

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