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. 03, 2026

Filed:

Jan. 27, 2022
Applicant:

Avago Technologies International Sales Pte. Limited, Singapore, SG;

Inventors:

Bhaswar Mitra, Santa Clara, CA (US);

Nitin Vinay Isloorkar, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06N 3/10 (2006.01); H04L 9/40 (2022.01); H04L 41/14 (2022.01); H04L 41/16 (2022.01);
U.S. Cl.
CPC ...
H04L 63/1416 (2013.01); G06N 3/10 (2013.01); H04L 41/145 (2013.01); H04L 41/16 (2013.01);
Abstract

Described herein are a device and a method for performing a network analysis. In one aspect, the device includes a reconfigurable neural network circuit to determine an indication of a predicted network characteristic. In one aspect, the reconfigurable neural network circuit includes a control circuit to select a packet attribute or a flow attribute of a raw packet stream from a pipeline, and determine a configuration setting corresponding to the packet attribute or the flow attribute. The configuration setting may indicate a configuration of the reconfigurable neural network circuit to implement a neural network. In one aspect, the reconfigurable neural network circuit includes a storage to provide neural network parameters of the neural network, according to the configuration setting. In one aspect, the reconfigurable neural network circuit includes computational circuits to perform computations based on the neural network parameters from the storage to determine the indication of the predicted network characteristic.


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