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:
Nov. 04, 2025

Filed:

Oct. 03, 2022
Applicant:

Xilinx, Inc., San Jose, CA (US);

Inventors:

Satish Bachina, Hyderabad, IN;

Karthic P, Chennai, IN;

Vishal Tripathi, Kanpur, IN;

Srinivasan Dasasathyan, Secunderabad, IN;

Assignee:

XILINX, INC., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 30/32 (2020.01); G06F 30/327 (2020.01); G06F 30/3308 (2020.01); G06F 30/3323 (2020.01); G06F 30/337 (2020.01); G06F 30/367 (2020.01); G06F 30/392 (2020.01); G06F 30/398 (2020.01); G06N 3/042 (2023.01); G06N 3/08 (2023.01); G06N 5/01 (2023.01); G06N 5/02 (2023.01); G06N 5/04 (2023.01); G06N 7/01 (2023.01); G06N 7/02 (2006.01); G06N 20/00 (2019.01); G06F 30/27 (2020.01); G06F 119/06 (2020.01);
U.S. Cl.
CPC ...
G06F 30/32 (2020.01); G06F 30/27 (2020.01); G06F 30/327 (2020.01); G06F 30/3308 (2020.01); G06F 30/3323 (2020.01); G06F 30/337 (2020.01); G06F 30/367 (2020.01); G06F 30/392 (2020.01); G06F 30/398 (2020.01); G06F 2119/06 (2020.01); G06N 3/042 (2023.01); G06N 3/08 (2013.01); G06N 5/01 (2023.01); G06N 5/02 (2013.01); G06N 5/04 (2013.01); G06N 7/01 (2023.01); G06N 7/023 (2013.01); G06N 20/00 (2019.01);
Abstract

Multiple classifier models are applied to features of a circuit design after processing the design through a first phase of an implementation flow. Each classifier model is associated with one of multiple directives, the directives are associated with a second phase of the implementation flow, and each classifier model returns a value indicative of likelihood of improving a quality metric. Regressor models of each set of a plurality of sets of regressor models are applied to the features. Each directive is associated with one of the sets of regressor models, and a combined score from each set of regressor models indicates a likelihood of satisfying a constraint. The directives are ranked based on the values indicated by the classifier models and scores from the sets of regressor models, and the circuit design is processed n the second phase of the implementation flow by the design tool using the directive having the highest rank.


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