IP Library › Granted Patent US 12,216,530
Granted Patent B2
US 12,216,530 · App. 18/140,921 · Granted Feb 4, 2025

Data center monitoring and management operation for predicting memory failures within a data center

Inventor: Deepak NagarajeGowda (Cary, NC)
Assignee: Dell Products L.P.
G06F11/0772G06F11/0793
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Quick Facts
Patent No.
US 12,216,530
App. No.
18/140,921
Granted
Feb 4, 2025
Kind
B2
Abstract

A system, method, and computer-readable medium for performing a data center monitoring and management operation, The data center monitoring and management operation includes receiving data center data for a data center, the data center data comprising data center memory associated data; receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset memory associated data; providing the data center memory associated data and the data center asset memory associated data to a memory failure prediction model; and, training the memory failure prediction model using the data center memory associated data and the data center asset memory associated data.

Claims (52)

1. A computer-implementable method for performing a data center monitoring and management operation, comprising:

receiving data center data for a data center, the data center data comprising data center memory associated data;

receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset memory associated data;

providing the data center memory associated data and the data center asset memory associated data to a memory failure prediction model; and,

training the memory failure prediction model using the data center memory associated data and the data center asset memory associated data; and wherein

the data center asset memory associated data comprises a memory module capacity feature, a number of memory chips per memory module feature, a current age of the data center asset feature, a memory module density on the data center asset feature, and a processor utilization of each memory module feature.

2. The method of claim 1 , further comprising:

providing the memory failure prediction model to a memory failure prediction component; and,

predicting a memory failure within a data center asset using the memory failure prediction model.

3. The method of claim 2 , further comprising:

performing a remediation operation based upon the predicting a memory failure within the data center asset.

4. The method of claim 2 , wherein:

the predicting considers a plurality of memory failure error types, the plurality of memory failure error types comprising a correctable memory error type and an uncorrectable memory error type.

5. The method of claim 2 , wherein:

the predicting considers operational attributes of the data center asset.

6. A system comprising:

a processor;

a data bus coupled to the processor; and

a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for:

receiving data center data for a data center, the data center data comprising data center memory associated data;

receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset memory associated data;

providing the data center memory associated data and the data center asset memory associated data to a memory failure prediction model; and,

training the memory failure prediction model using the data center memory associated data and the data center asset memory associated data; and wherein

the data center asset memory associated data comprises a memory module capacity feature, a number of memory chips per memory module feature, a current age of the data center asset feature, a memory module density on the data center asset feature, and a processor utilization of each memory module feature.

7. The system of claim 6 , wherein the instructions executable by the processor are further configured for:

providing the memory failure prediction model to a memory failure prediction component; and,

predicting a memory failure within a data center asset using the memory failure prediction model.

8. The system of claim 7 , wherein the instructions executable by the processor are further configured for:

performing a remediation operation based upon the predicting a memory failure within the data center asset.

9. The system of claim 7 , wherein:

the predicting considers a plurality of memory failure error types, the plurality of memory failure error types comprising a correctable memory error type and an uncorrectable memory error type.

10. The system of claim 7 , wherein:

the predicting considers operational attributes of the data center asset.

11. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:

receiving data center data for a data center, the data center data comprising data center memory associated data;

receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset memory associated data;

providing the data center memory associated data and the data center asset memory associated data to a memory failure prediction model; and,

training the memory failure prediction model using the data center memory associated data and the data center asset memory associated data; and wherein

the data center asset memory associated data comprises a memory module capacity feature, a number of memory chips per memory module feature, a current age of the data center asset feature, a memory module density on the data center asset feature, and a processor utilization of each memory module feature.

12. The non-transitory, computer-readable storage medium of claim 11 , wherein the computer executable instructions are further configured for:

providing the memory failure prediction model to a memory failure prediction component; and,

predicting a memory failure within a data center asset using the memory failure prediction model.

13. The non-transitory, computer-readable storage medium of claim 12 , wherein the computer executable instructions are further configured for:

performing a remediation operation based upon the predicting a memory failure within the data center asset.

14. The non-transitory, computer-readable storage medium of claim 12 , wherein:

the predicting considers a plurality of memory failure error types, the plurality of memory failure error types comprising a correctable memory error type and an uncorrectable memory error type.

15. The non-transitory, computer-readable storage medium of claim 12 , wherein:

the predicting considers operational attributes of the data center asset.

16. The non-transitory, computer-readable storage medium of claim 11 , wherein:

the computer executable instructions are deployable to a client system from a server system at a remote location.

17. The non-transitory, computer-readable storage medium of claim 11 , wherein:

the computer executable instructions are provided by a service provider to a user on an on-demand basis.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 28, 2023
From: NAGARAJEGOWDA, DEEPAK
To: DELL PRODUCTS L.P.
Reel/Frame 063479/0085 →
Continuity (1)
Related Publication 20240362102A1 · Oct 31, 2024
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