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. 14, 2023

Filed:

Apr. 24, 2017
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Gokcen Cilingir, Sunnyvale, CA (US);

Elmoustapha Ould-Ahmed-Vall, Chandler, AZ (US);

Rajkishore Barik, Santa Clara, CA (US);

Kevin Nealis, San Jose, CA (US);

Xiaoming Chen, Shanghai, CN;

Justin E. Gottschlich, Santa Clara, CA (US);

Prasoonkumar Surti, Folsom, CA (US);

Chandrasekaran Sakthivel, Sunnyvale, CA (US);

Abhishek Appu, El Dorado Hills, CA (US);

John C. Weast, Portland, OR (US);

Sara S. Baghsorkhi, San Jose, CA (US);

Barnan Das, San Jose, CA (US);

Narayan Biswal, Folsom, CA (US);

Stanley J. Baran, Elk Grove, CA (US);

Nilesh V. Shah, Folsom, CA (US);

Archie Sharma, Folsom, CA (US);

Mayuresh M. Varerkar, Folsom, CA (US);

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01); G06N 3/04 (2023.01); G06F 9/38 (2018.01); G06N 3/063 (2023.01); G06F 9/30 (2018.01); G06T 1/20 (2006.01); G06N 3/084 (2023.01);
U.S. Cl.
CPC ...
G06N 3/0454 (2013.01); G06F 9/3001 (2013.01); G06F 9/3017 (2013.01); G06F 9/3851 (2013.01); G06F 9/3887 (2013.01); G06F 9/3895 (2013.01); G06N 3/0445 (2013.01); G06N 3/063 (2013.01); G06N 3/084 (2013.01); G06T 1/20 (2013.01);
Abstract

An apparatus to facilitate neural network (NN) training is disclosed. The apparatus includes training logic to receive one or more network constraints and train the NN by automatically determining a best network layout and parameters based on the network constraints.


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