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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.:

US 11347679 B1

PDFFull Text
Date of Patent:
May. 31, 2022

Filed:

Feb. 08, 2018

Hybrid system-on-chip for power and performance prediction and control

Applicant:

Alibaba Group Holding Limited, Grand Cayman, KY;

Inventors:

Jun Song, Tacoma, WA (US);

Yi Liu, Hangzhou, CN;

Lingling Jin, Sunnyvale, CA (US);

Guan Wang, Hangzhou, CN;

Ying Wang, Hangzhou, CN;

Hong Tang, Kirkland, WA (US);

Nan Zhang, Bellevue, WA (US);

Zhengxiong Tian, Hangzhou, CN;

Yu Zhou, Hangzhou, CN;

Chao Qian, Hangzhou, CN;

Shuiwang Liu, Hangzhou, CN;

Jun Ruan, Hangzhou, CN;

Bo Yang, Hangzhou, CN;

Lin Yu, Hangzhou, CN;

Jiangwei Huang, Hangzhou, CN;

Hong Zhou, Hangzhou, CN;

Yijun Lu, Seattle, WA (US);

Ling Xu, Hangzhou, CN;

Shiwei Li, Hangzhou, CN;

Xiaolin Meng, Hangzhou, CN;

Assignee:

Alibaba Group Holding Limited, George Town, KY;

Attorney:

Lee & Hayes, P.C.

Primary Examiner:

Tuan A Vu

Int. Cl.
CPC ...
G05D 17/00 (2006.01); G06F 15/78 (2006.01); G05B 19/042 (2006.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06N 5/02 (2006.01); G06F 16/2458 (2019.01); G06F 3/06 (2006.01); G06F 9/448 (2018.01); H04L 12/12 (2006.01); H04L 9/06 (2006.01);
U.S. Cl.
CPC ...
G06F 15/7807 (2013.01); G05B 19/042 (2013.01); G06F 3/064 (2013.01); G06F 9/4484 (2018.02); G06F 9/4881 (2013.01); G06F 9/5011 (2013.01); G06F 16/2471 (2019.01); G06N 5/02 (2013.01); G05B 2219/2639 (2013.01); H04L 9/0618 (2013.01); H04L 12/12 (2013.01);
Abstract

Systems and methods for a hybrid system-on-chip usable for predicting performance and power requirements of a host server include a big cores module, including central processing units, for receiving and pre-processing performance and power metrics data of the host server and to allocate computing resources, a small cores module, including massively parallel processing units, for mapping each instance associated with host server in the performance and power metrics data to a corresponding massively parallel processing unit based on the allocated computing resources for a per-instance metrics calculation, and an artificial intelligence (AI) accelerator for calculating performance and power prediction results based on the per-instance calculations from the small cores module.

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