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Accelerating neural networks in hardware using interconnected crossbars

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Summary

The USPTO granted Patent US12596922B2 to Google LLC on April 7, 2026, covering a computing unit design for accelerating neural networks using interconnected analog crossbar circuits. The patent includes 20 claims relating to matrix weight operations performed on analog signals within crossbar architectures. Inventors are Pierre-Luc Cantin and Olivier Temam, with filing date March 21, 2024.

What changed

The USPTO has granted a new patent to Google LLC covering hardware acceleration of neural networks using interconnected analog crossbar circuits. The invention includes digital-to-analog and analog-to-digital conversion units integrated with multiple analog crossbar circuits that perform matrix weight operations on analog signals.

Technology companies developing AI accelerators, neural network hardware, or crossbar-based computing systems should consider this patent when assessing intellectual property landscape and potential licensing obligations for similar architectures.

What to do next

  1. Monitor for potential licensing requirements if developing similar neural network acceleration hardware
  2. Review patent claims for freedom-to-operate analysis in AI hardware development

Archived snapshot

Apr 7, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Grants

Accelerating neural networks in hardware using interconnected crossbars

Grant US12596922B2 Kind: B2 Apr 07, 2026

Assignee

Google LLC

Inventors

Pierre-Luc Cantin, Olivier Temam

Abstract

A computing unit for accelerating a neural network is disclosed. The computing unit include an input unit that includes a digital-to-analog conversion unit and an analog-to-digital conversion unit that is configured to receive an analog signal from the output of a last interconnected analog crossbar circuit of a plurality of analog crossbar circuits and convert the second analog signal into a digital output vector, and a plurality of interconnected analog crossbar circuits that include the first interconnected analog crossbar circuit and the last interconnected crossbar circuits, wherein a second interconnected analog crossbar circuit of the plurality of interconnected analog crossbar circuits is configured to receive a third analog signal from another interconnected analog crossbar circuit of the plurality of interconnected crossbar circuits and perform one or more operations on the third analog signal based on the matrix weights stored by the crosspoints of the second interconnected analog crossbar.

CPC Classifications

G06N 3/065 G06N 3/04 G06N 3/08 G06F 9/5027 G06F 17/16

Filing Date

2024-03-21

Application No.

18612881

Claims

20

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Last updated

Classification

Agency
USPTO
Published
April 7th, 2026
Instrument
Notice
Legal weight
Binding
Stage
Final
Change scope
Minor
Document ID
US12596922B2

Who this affects

Applies to
Technology companies Manufacturers
Industry sector
3341 Computer & Electronics Manufacturing
Activity scope
Neural network acceleration Analog crossbar computing AI hardware design
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence

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