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. 31, 2023
Filed:
Nov. 30, 2021
Applicant:
Pure Storage, Inc., Mountain View, CA (US);
Inventors:
Brian Gold, Los Altos, CA (US);
Emily Potyraj, Houston, TX (US);
Ivan Jibaja, San Jose, CA (US);
Igor Ostrovsky, Mountain View, CA (US);
Roy Kim, Los Altos, CA (US);
Assignee:
PURE STORAGE, INC., Santa Clara, CA (US);
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 3/06 (2006.01); G06N 20/00 (2019.01); G06F 16/245 (2019.01); G06F 16/178 (2019.01); G06Q 30/0242 (2023.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06N 3/063 (2023.01); G06N 3/08 (2023.01); G06T 1/20 (2006.01); G06T 1/60 (2006.01); G06F 16/958 (2019.01); G06F 16/248 (2019.01);
U.S. Cl.
CPC ...
G06F 3/0679 (2013.01); G06F 3/0604 (2013.01); G06F 3/067 (2013.01); G06F 3/0608 (2013.01); G06F 3/0646 (2013.01); G06F 3/0649 (2013.01); G06F 9/4881 (2013.01); G06F 9/5027 (2013.01); G06F 16/1794 (2019.01); G06F 16/245 (2019.01); G06N 3/063 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06Q 30/0243 (2013.01); G06T 1/20 (2013.01); G06T 1/60 (2013.01); G06F 16/248 (2019.01); G06F 16/972 (2019.01); G06T 2200/28 (2013.01);
Abstract
Executing a machine learning model in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit ('GPU') servers, including: receiving, by a graphical processing unit ('GPU') server, a dataset transformed by a storage system that is external to the GPU server; and executing, by the GPU server, one or more machine learning algorithms using the transformed dataset as input.