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:
Mar. 07, 2023

Filed:

Jun. 27, 2018
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Sudipta Sengupta, Redmond, WA (US);

Poorna Chand Srinivas Perumalla, Seattle, WA (US);

Dominic Rajeev Divakaruni, Seattle, WA (US);

Nafea Bshara, Cupertino, CA (US);

Leo Parker Dirac, Seattle, WA (US);

Bratin Saha, Cupertino, CA (US);

Matthew James Wood, Seattle, WA (US);

Andrea Olgiati, Gilroy, CA (US);

Swaminathan Sivasubramanian, Sammamish, WA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 9/50 (2006.01); G06N 5/04 (2006.01); G06F 9/455 (2018.01); G06N 3/04 (2006.01); G06N 3/063 (2006.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 9/45558 (2013.01); G06F 9/5027 (2013.01); G06F 9/5044 (2013.01); G06F 9/5077 (2013.01); G06N 3/0454 (2013.01); G06N 3/063 (2013.01); G06N 5/04 (2013.01); G06F 9/5055 (2013.01); G06F 2009/4557 (2013.01); G06F 2009/45583 (2013.01); G06F 2009/45595 (2013.01);
Abstract

Implementations detailed herein include description of a computer-implemented method. In an implementation, the method at least includes receiving an application instance configuration, an application of the application instance to utilize a portion of an attached accelerator during execution of a machine learning model and the application instance configuration including: an indication of the central processing unit (CPU) capability to be used, an arithmetic precision of the machine learning model to be used, an indication of the accelerator capability to be used, a storage location of the application, and an indication of an amount of random access memory to use.


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