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. 01, 2024

Filed:

Jul. 25, 2022
Applicant:

Hewlett Packard Enterprise Development Lp, Houston, TX (US);

Inventors:

Tobias Frederic Ziegler, Houston, TX (US);

Ron M. Roth, Palo Alto, CA (US);

Giacomo Pedretti, Cernusco sul Naviglio, IT;

Luca Buonanno, Houston, TX (US);

Pedro Henrique Rocha Bruel, Houston, TX (US);

Catherine Graves, Milpitas, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G11C 15/04 (2006.01); G11C 16/10 (2006.01); G11C 16/12 (2006.01); H03K 19/017 (2006.01);
U.S. Cl.
CPC ...
G11C 15/04 (2013.01); G11C 16/102 (2013.01); G11C 16/12 (2013.01); H03K 19/01742 (2013.01);
Abstract

Examples increase precision for aCAMs by converting an input signal (x) received by a circuit into a first analog voltage signal (V(x)) representing the most significant bits of the input signal (x) and a second analog voltage signal (V(x)) representing the least significant bits of the input signal (x). By dividing the input signal (x) bit-wise into the first analog voltage signal (V(x)) and the second analog voltage signal (V(x)), the circuit can utilize aCAM sub-circuits implementing a combination of Boolean operations to search the input signal (x) against 2programmable levels, where 'M' represents the number of programmable bits for each aCAM sub-circuit. Thus, using similar circuit hardware, example circuits square the number of programmable levels of conventional aCAMs (which generally only have 2programmable levels). Accordingly, examples provide new aCAMs that can carry out more complex computations than conventional aCAMs of comparable cost, size, and power consumption.


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