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:
Jan. 07, 2025

Filed:

Sep. 30, 2020
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Rathijit Sen, Madison, WI (US);

Alekh Jindal, Sammamish, WA (US);

Anish Yatin Pimpley, Somerville, MA (US);

Shuo Li, Newton, MS (US);

Anubha Srivastava, McAllen, TX (US);

Vishal Lalchand Rohra, Boston, MA (US);

Yi Zhu, Boston, MA (US);

Hiren Shantilal Patel, Bothell, WA (US);

Shi Qiao, Mercer Island, WA (US);

Marc Todd Friedman, Seattle, WA (US);

Clemens Alden Szyperski, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); G06F 16/2453 (2019.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06F 16/24545 (2019.01); G06N 20/00 (2019.01);
Abstract

Solutions for optimizing job runtimes via prediction-based token allocation includes receiving training data comprising historical run data, the historical run data comprising job characteristics, runtime results, and a token count for each of a plurality of prior jobs, and the job characteristics comprising an intermediate representation and job graph data; based at least on the training data, training a token estimator, the token estimator comprising a machine learning (ML) model; receiving job characteristics for a user-submitted job; based at least on the received job characteristics, generating, with the token estimator, token prediction data for the user-submitted job; selecting a token count for the user-submitted job, based at least on the token prediction data; identifying the selected token count to an execution environment; and executing, with the execution environment, the user-submitted job in accordance with the selected token count.


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