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:
Feb. 21, 2023

Filed:

May. 11, 2021
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Divya Vijayaraghavan, Los Altos, CA (US);

Denica Larsen, Portland, OR (US);

Kooi Chi Ooi, Bukit Gambir, MY;

Lady Nataly Pinilla Pico, El Dorado Hills, CA (US);

Min Suet Lim, Gelugor Penang, MY;

Assignee:

INTEL CORPORATION, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/50 (2006.01); G06N 3/08 (2023.01); G06N 3/04 (2023.01); G06F 11/30 (2006.01); G06K 9/62 (2022.01);
U.S. Cl.
CPC ...
G06F 9/5044 (2013.01); G06F 9/5027 (2013.01); G06F 11/3024 (2013.01); G06K 9/6256 (2013.01); G06N 3/0445 (2013.01); G06N 3/08 (2013.01);
Abstract

Methods, apparatus, systems, and articles of manufacture for allocating a workload to an accelerator using machine learning are disclosed. An example apparatus includes a workload attribute determiner to identify a first attribute of a first workload and a second attribute of a second workload. An accelerator selection processor causes at least a portion of the first workload to be executed by at least two accelerators, accesses respective performance metrics corresponding to execution of the first workload by the at least two accelerators, and selects a first accelerator of the at least two accelerators based on the performance metrics. A neural network trainer trains a machine learning model based on an association between the first accelerator and the first attribute of the first workload. A neural network processor processes, using the machine learning model, the second attribute to select one of the at least two accelerators to execute the second workload.


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