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:
Sep. 10, 2024

Filed:

Oct. 17, 2017
Applicant:

Xilinx, Inc., San Jose, CA (US);

Inventors:

Yongjun Wu, San Jose, CA (US);

Jindrich Zejda, Saratoga, CA (US);

Elliott Delaye, San Jose, CA (US);

Ashish Sirasao, San Jose, CA (US);

Assignee:

XILINX, INC., San Jose, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 8/30 (2018.01); G06F 8/41 (2018.01); G06F 12/06 (2006.01); G06N 3/04 (2023.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06F 8/313 (2013.01); G06F 8/47 (2013.01); G06F 12/0646 (2013.01); G06N 3/04 (2013.01); G06N 20/00 (2019.01);
Abstract

Embodiments herein describe techniques for expressing the layers of a neural network in a software model. In one embodiment, the software model includes a class that describes the various functional blocks (e.g., convolution units, max-pooling units, rectified linear units (ReLU), and scaling functions) used to execute the neural network layers. In turn, other classes in the software model can describe the operation of each of the functional blocks. In addition, the software model can include conditional logic for expressing how the data flows between the functional blocks since different layers in the neural network can process the data differently. A compiler can convert the high-level code in the software model (e.g., C++) into a hardware description language (e.g., register transfer level (RTL)) which is used to configure a hardware system to implement a neural network accelerator.


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