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. 19, 2024

Filed:

Oct. 05, 2022
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Elmoustapha Ould-Ahmed-Vall, Chandler, AZ (US);

Sara S. Baghsorkhi, San Jose, CA (US);

Anbang Yao, Beijing, CN;

Kevin Nealis, San Jose, CA (US);

Xiaoming Chen, Shanghai, CN;

Altug Koker, El Dorado Hills, CA (US);

Abhishek R. Appu, El Dorado Hills, CA (US);

John C. Weast, Portland, OR (US);

Mike B. Macpherson, Portland, OR (US);

Dukhwan Kim, San Jose, CA (US);

Linda L. Hurd, Cool, CA (US);

Ben J. Ashbaugh, Folsom, CA (US);

Barath Lakshmanan, Chandler, AZ (US);

Liwei Ma, Beijing, CN;

Joydeep Ray, Folsom, CA (US);

Ping T. Tang, Edison, NJ (US);

Michael S. Strickland, Sunnyvale, CA (US);

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 1/20 (2006.01); G06F 7/483 (2006.01); G06F 9/30 (2018.01); G06F 9/38 (2018.01); G06F 9/50 (2006.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/063 (2023.01); G06N 3/084 (2023.01); G06N 20/00 (2019.01); G06T 1/60 (2006.01); G06F 3/14 (2006.01); G06T 15/00 (2011.01);
U.S. Cl.
CPC ...
G06T 1/20 (2013.01); G06F 7/483 (2013.01); G06F 9/30014 (2013.01); G06F 9/30185 (2013.01); G06F 9/3863 (2013.01); G06F 9/5044 (2013.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/063 (2013.01); G06N 3/084 (2013.01); G06N 20/00 (2019.01); G06F 3/14 (2013.01); G06T 1/60 (2013.01); G06T 15/005 (2013.01);
Abstract

One embodiment provides a multi-chip module accelerator usable to execute tensor data processing operations a multi-chip module. The multi-chip module may include a memory stack including multiple memory dies and parallel processor circuitry communicatively coupled to the memory stack. The parallel processor circuitry may include multiprocessor cores to execute matrix multiplication and accumulate operations. The matrix multiplication and accumulate operations may include floating-point operations that are configurable to include two-dimensional matrix multiply and accumulate operations involving inputs that have differing floating-point precisions. The floating-point operations may include a first operation at a first precision and a second operation at a second precision. The first operation may include a multiply having at least one 16-bit floating-point input and the second operation may include an accumulate having a 32-bit floating-point input.


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