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:
Dec. 31, 2024

Filed:

Dec. 02, 2022
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Francesco Rossi, Sunnyvale, CA (US);

Gaurav Kapoor, Santa Clara, CA (US);

Michael R. Siracusa, Mountain View, CA (US);

William B. March, San Jose, CA (US);

Assignee:

Apple Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/46 (2006.01); G06F 8/41 (2018.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06N 3/02 (2006.01); G06N 3/063 (2023.01);
U.S. Cl.
CPC ...
G06F 9/50 (2013.01); G06F 8/451 (2013.01); G06F 9/485 (2013.01); G06F 9/5038 (2013.01); G06F 9/5044 (2013.01); G06N 3/02 (2013.01); G06N 3/063 (2013.01); G06F 2209/509 (2013.01);
Abstract

The subject technology provides for dynamic task allocation for neural network models. The subject technology determines an operation performed at a node of a neural network model. The subject technology assigns an annotation to indicate whether the operation is better performed on a CPU or a GPU based at least in part on hardware capabilities of a target platform. The subject technology determines whether the neural network model includes a second layer. The subject technology, in response to determining that the neural network model includes a second layer, for each node of the second layer of the neural network model, determines a second operation performed at the node. Further the subject technology assigns a second annotation to indicate whether the second operation is better performed on the CPU or the GPU based at least in part on the hardware capabilities of the target platform.


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