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:
Oct. 08, 2024

Filed:

Dec. 19, 2018
Applicant:

Cavium, Llc, Santa Clara, CA (US);

Inventors:

Avinash Sodani, San Jose, CA (US);

Ulf Hanebutte, Gig Harbor, WA (US);

Senad Durakovic, Palo Alto, CA (US);

Hamid Reza Ghasemi, Sunnyvale, CA (US);

Chia-Hsin Chen, Santa Clara, CA (US);

Assignee:

Marvell Asia Pte Ltd, Singapore, SG;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/10 (2019.01); 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); 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 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 programmable hardware system for machine learning (ML) includes a core and a streaming engine. The core receives a plurality of commands and a plurality of data from a host to be analyzed and inferred via machine learning. The core transmits a first subset of commands of the plurality of commands that is performance-critical operations and associated data thereof of the plurality of data for efficient processing thereof. The first subset of commands and the associated data are passed through via a function call. The streaming engine is coupled to the core and receives the first subset of commands and the associated data from the core. The streaming engine streams a second subset of commands of the first subset of commands and its associated data to an inference engine by executing a single instruction.


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