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.
Patent No.:
Date of Patent:
Oct. 19, 2021
Filed:
Aug. 09, 2019
Intel Corporation, Santa Clara, CA (US);
Hugues Labbe, Granite Bay, CA (US);
Darrel Palke, Portland, OR (US);
Sherine Abdelhak, Beaverton, OR (US);
Jill Boyce, Portland, OR (US);
Varghese George, Folsom, CA (US);
Scott Janus, Loomis, CA (US);
Adam Lake, Portland, OR (US);
Zhijun Lei, Hillsboro, OR (US);
Zhengmin Li, Hillsboro, OR (US);
Mike Macpherson, Portland, OR (US);
Carl Marshall, Portland, OR (US);
Selvakumar Panneer, Portland, OR (US);
Prasoonkumar Surti, Folsom, CA (US);
Karthik Veeramani, Hillsboro, OR (US);
Deepak Vembar, Portland, OR (US);
Vallabhajosyula Srinivasa Somayazulu, Portland, OR (US);
Intel Corporation, Santa Clara, CA (US);
Abstract
One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.