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. 22, 2024

Filed:

Nov. 05, 2021
Applicant:

Synopsys, Inc., Mountain View, CA (US);

Inventors:

Chaofan Wang, Santa Clara, CA (US);

Vaibhav Jain, Cupertino, CA (US);

Shekaripuram Venkatesh, Los Altos, CA (US);

Solaiman Rahim, San Francisco, CA (US);

Assignee:

Synopsys, Inc., Sunnyvale, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 30/337 (2020.01); G06F 30/27 (2020.01); G06F 30/33 (2020.01); G06F 18/2413 (2023.01); G06F 30/30 (2020.01); G06F 119/06 (2020.01); G06N 3/02 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01);
U.S. Cl.
CPC ...
G06F 30/33 (2020.01); G06F 30/27 (2020.01); G06F 18/24137 (2023.01); G06F 30/30 (2020.01); G06F 30/337 (2020.01); G06F 2119/06 (2020.01); G06N 3/02 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01);
Abstract

A method includes generating a plurality of input vectors based on input signals to an electric circuit, selecting a subset of the plurality of input vectors, and determining a plurality of datapoints based on the selected subset of the plurality of input vectors. Each datapoint of the plurality of datapoints indicates a power consumption of the electric circuit corresponding to an input vector of the selected subset of the input vectors. The method also includes generating, by a processor, a plurality of vector sequences based on the selected subset of the plurality of input vectors. Each vector sequence of the plurality of vector sequences includes a portion of the selected subset of the plurality of input vectors arranged chronologically. The method further includes training a machine learning model based on a first subset of the plurality of vector sequences and a corresponding first subset of the plurality of datapoints.


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