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. 05, 2023

Filed:

Jan. 19, 2021
Applicant:

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

Inventors:

Owen Martin, Hopedale, MA (US);

Rasa Raghavan, Verona, WI (US);

Assignee:

Dell Products, L.P., Hopkinton, MA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 11/36 (2006.01); G06F 11/14 (2006.01); G06F 11/34 (2006.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01);
U.S. Cl.
CPC ...
G06F 11/3688 (2013.01); G06F 11/1407 (2013.01); G06F 11/3414 (2013.01); G06F 11/3692 (2013.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01);
Abstract

Different storage platforms and different applications generate different types of traffic. Separate learning processes are trained using live IO operations from different types of reference workloads. The reference workloads are based on multiple types of applications executing in multiple types of environments. Example applications may include Oracle, SAP, SQL, etc. Example environments may include finance/banking, retail, on-line transaction processing, healthcare, etc. Once the learning processes have been trained, trained model checkpoints describing the trained learning processes are stored in a reference workload repository. The trained model checkpoints are used in a testing environment to enable a test server to create a test model configured to generate simulated test IO operations to be applied to a storage system. The generated test IO operations simulate the workload from an intended application and environment where the storage system will be used.


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