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. 14, 2025

Filed:

Jan. 03, 2020
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Andrew S. Cassidy, San Jose, CA (US);

Rathinakumar Appuswamy, San Jose, CA (US);

John V. Arthur, Mountain View, CA (US);

Pallab Datta, San Jose, CA (US);

Steve Esser, San Jose, CA (US);

Myron D. Flickner, San Jose, CA (US);

Dharmendra S. Modha, San Jose, CA (US);

Jun Sawada, Austin, TX (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/063 (2023.01); G06N 5/04 (2023.01);
U.S. Cl.
CPC ...
G06N 3/063 (2013.01); G06N 5/04 (2013.01);
Abstract

A neural inference chip includes a global weight memory; a neural core; and a network connecting the global weight memory to the at least one neural core. The neural core comprises a local weight memory. The local weight memory comprises a plurality of memory banks. Each of the plurality of memory banks is uniquely addressable by at least one index. The neural inference chip is adapted to store in the global weight memory a compressed weight block comprising at least one compressed weight matrix. The neural inference chip is adapted to transmit the compressed weight block from the global weight memory to the core via the network. The core is adapted to decode the at least one compressed weight matrix into a decoded weight matrix and store the decoded weight matrix in its local weight memory. The at core is adapted to apply the decoded weight matrix to a plurality of input activations to produce a plurality of output activations.


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