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:
Sep. 11, 2018

Filed:

Nov. 08, 2017
Applicant:

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

Inventors:

Aaron K. Baughman, Silver Spring, MD (US);

Thomas B. Harrison, Holly Springs, NC (US);

Cody A. Clements, Clifton Springfield, MO (US);

Michael P. Lazos, Manchester, NH (US);

Robert J. Lewis, Chapel Hill, NC (US);

Brian M. O'Connell, Cary, NC (US);

Mary C. Zabriskie, Durham, NC (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/36 (2006.01); G06F 11/34 (2006.01); H04L 12/26 (2006.01); G06F 9/50 (2006.01); H04L 12/24 (2006.01);
U.S. Cl.
CPC ...
G06F 11/3457 (2013.01); G06F 9/5072 (2013.01); H04L 41/083 (2013.01); H04L 43/50 (2013.01);
Abstract

A method and associated systems for optimizing a computing platform. A processor joins sets of configurable parameters into groups that each identifies a configuration of the computing environment or of a component or subsystem of the computing environment. The processor generates a set of variations of each group, where each variation identifies a candidate configuration of the component, subsystem, or platform, and where each candidate configuration identifies a distinct set of values of the group of parameters associated with that component, subsystem, or platform. Each configuration of this first generation of configurations undergoes a massively parallel iterative procedure that generates a next generation of configurations by performing operations upon the first generation that are similar to those of a natural-selection process. The procedure repeats until successive generations converge, within resource constraints, to a fittest generation that represents an optimal or most nearly optimal configuration of the computing platform.


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