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:
Nov. 28, 2023

Filed:

Oct. 13, 2020
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Saket Sathe, Mohegan Lake, NY (US);

Gregory Bramble, Larchmont, NY (US);

Long Vu, Chappaqua, NY (US);

Theodoros Salonidis, Wayne, PA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/50 (2006.01); G06N 20/00 (2019.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G06F 9/505 (2013.01); G06F 9/5044 (2013.01); G06F 9/5077 (2013.01); G06F 9/5094 (2013.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01);
Abstract

A method, a structure, and a computer system for predicting pipeline training requirements. The exemplary embodiments may include receiving one or more worker node features from one or more worker nodes, extracting one or more pipeline features from one or more pipelines to be trained, and extracting one or more dataset features from one or more datasets used to train the one or more pipelines. The exemplary embodiments may further include predicting an amount of one or more resources required for each of the one or more worker nodes to train the one or more pipelines using the one or more datasets based on one or more models that correlate the one or more worker node features, one or more pipeline features, and one or more dataset features with the one or more resources. Lastly, the exemplary embodiments may include identifying a worker node requiring a least amount of the one or more resources of the one or more worker nodes for training the one or more pipelines.


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