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:
Feb. 21, 2023

Filed:

Jun. 28, 2019
Applicant:

Emc Ip Holding Company Llc, Hopkinton, MA (US);

Inventors:

Tiago Salviano Calmon, Rio de Janeiro, BR;

Vinícius Michel Gottin, Rio de Janeiro, BR;

Eduardo Vera Sousa, Niterói, BR;

Assignee:

EMC IP Holding Company LLC, Hopkinton, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/46 (2006.01); G06F 9/50 (2006.01); G06N 3/08 (2023.01); G06F 9/52 (2006.01);
U.S. Cl.
CPC ...
G06F 9/505 (2013.01); G06F 9/52 (2013.01); G06N 3/08 (2013.01);
Abstract

Techniques are provided for adaptive resource allocation for multiple workloads. One method comprises obtaining a dynamic system model based on a relation between an amount of a resource for multiple iterative workloads and a predefined service metric; obtaining an instantaneous value of the predefined service metric; applying to a given controller associated with a given iterative workload of the multiple iterative workloads: (i) the dynamic system model, (ii) an interference effect of one or more additional iterative workloads on the given iterative workload, and (iii) a difference between the instantaneous value and a target value for the predefined service metric. The given controller applies an adjustment to the amount of the resource for the given iterative workload based at least in part on the difference. The resource allocation for the multiple iterative workloads can be performed in a sequence substantially in parallel with an execution of the iterative workloads.


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