IP Library Granted Patent US 11,500,714
Granted Patent B2
US 11,500,714 · App. 17/182,177 · Granted Nov 15, 2022

Apparatus and method for regulating available storage of a data storage system

Inventors: Jay Sarkar (San Jose, CA); Cory Peterson (Kasson, MN)
Assignee: WESTERN DIGITAL TECHNOLOGIES, INC.
G06F11/079G06F11/0727G06F11/0751G06F11/0793G06F12/10G06N20/00G06F2212/1044G06F2212/657
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Quick Facts
Patent No.
US 11,500,714
App. No.
17/182,177
Granted
Nov 15, 2022
Kind
B2
Abstract

Apparatus, media, methods, and systems for data storage systems and methods for autonomously adapting data storage system performance, lifetime, capacity and/or operational requirements. A data storage system may comprise a controller and one or more non-volatile memory devices. The controller is configured to determine a category for a workload of one or more operations being processed by the data storage system using a machine-learned model. The controller is configured to determine an expected degradation of the one or more non-volatile memory devices. The controller is configured to adjust, based on the expected degradation and an actual usage of physical storage of the data storage system by a host system, an amount of physical storage of the data storage system available to the host system.

Claims (65)

1. A machine-implemented method for a data storage system comprising one or more non-volatile memories, the machine-implemented method comprising:

determining, using a machine-learned model, a category for a workload of one or more operations being processed by the data storage system, based on values associated with parameters for the machine-learned model, wherein the values change as the data storage system processes the one or more operations; and

based on the category, a projected degradation, and an actual storage usage of the data storage system, regulating an amount of available storage of the data storage system,

wherein:

the projected degradation is associated with the one or more non-volatile memories; and

the projected degradation is determined based on the category for the workload of the one or more operations being processed by the data storage system.

2. The machine-implemented method of claim 1 , wherein the category for the workload comprises an entropy type for the workload.

3. The machine-implemented method of claim 1 , wherein categories of workloads for the data storage system comprise the following:

a random workload type associated with reading or writing using randomly addressed memory blocks;

a sequential workload type associated with reading or writing using contiguously addressed memory blocks; and

a mixed workload type associated with reading or writing using randomly addressed memory blocks and contiguously addressed memory blocks.

4. The machine-implemented method of claim 1 , wherein regulating the amount of available storage comprises determining the projected degradation based on the category.

5. The machine-implemented method of claim 1 , wherein regulating the amount of available storage comprises:

determining, based on the category and the projected degradation, whether to adjust the amount of available storage of the data storage system for use by a host system;

responsive to determining the amount of available storage of the data storage system be adjusted:

computing, based on a usage history by the host system, an actual usage of physical storage of the data storage system, by the host system;

determining that the actual usage of the physical storage by the host system satisfies a threshold value; and

adjusting the amount of available storage of the data storage system.

6. The machine-implemented method of claim 1 , wherein regulating the amount of available storage comprises decreasing the amount of available storage of the data storage system.

7. The machine-implemented method of claim 6 , wherein decreasing the amount of available storage comprises reducing a maximum logical block address.

8. A data storage system, comprising:

one or more non-volatile memories;

one or more controllers configured to cause:

determining, using a machine-learned model, a category for a workload of one or more operations being processed by the data storage system, based on values associated with parameters for the machine-learned model, wherein the values change as the data storage system processes the one or more operations; and

based on the category, a projected degradation, and an actual storage usage of the data storage system, regulating an amount of available storage of the data storage system,

wherein:

the projected degradation is associated with the one or more non-volatile memories; and

the one or more controllers are configured to cause determining the projected degradation based on the category for the workload of the one or more operations being processed by the data storage system.

9. The data storage system of claim 8 , wherein the category for the workload comprises an entropy type for the workload.

10. The data storage system of claim 8 , wherein categories of workloads for the data storage system comprise the following:

a random workload type associated with reading or writing using randomly addressed memory blocks;

a sequential workload type associated with reading or writing using contiguously addressed memory blocks; and

a mixed workload type associated with reading or writing using randomly addressed memory blocks and contiguously addressed memory blocks.

11. The data storage system of claim 8 , wherein regulating the amount of available storage comprises determining the projected degradation based on the category.

12. The data storage system of claim 8 , wherein regulating the amount of available storage comprises:

determining, based on the category and the projected degradation, whether to adjust the amount of available storage of the data storage system for use by a host system;

responsive to determining the amount of available storage of the data storage system be adjusted:

computing, based on a usage history by the host system, an actual usage of physical storage of the data storage system, by the host system;

determining that the actual usage of the physical storage by the host system satisfies a threshold value; and

adjusting the amount of available storage of the data storage system.

13. The data storage system of claim 8 , wherein regulating the amount of available storage comprises decreasing the amount of available storage of the data storage system.

14. The data storage system of claim 13 , wherein decreasing the amount of available storage comprises reducing a maximum logical block address.

15. The data storage system of claim 8 , wherein regulating the amount of available storage comprises:

transferring an alert to a host system, wherein the alert indicates that the amount of available storage of the data storage system is adjustable;

receiving a message from the host system in response to the transferred alert; and

adjusting, based on the message, the amount of available storage of the data storage system.

16. An apparatus, comprising:

one or more non-volatile memories of a data storage system; and

means for determining, using a machine-learned model, a category for a workload of one or more operations being processed by the data storage system, based on values associated with parameters for the machine-learned model, wherein the values change as the data storage system processes the one or more operations; and

based on the category, a projected degradation, and an actual storage usage of the data storage system, means for regulating an amount of available storage of the data storage system,

wherein:

the projected degradation is associated with the one or more non-volatile memories; and

the apparatus comprises means for determining the projected degradation based on the category for the workload of the one or more operations being processed by the data storage system.

17. The apparatus of claim 16 , wherein the category for the workload comprises an entropy type for the workload.

18. The apparatus of claim 16 , wherein categories of workloads for the data storage system comprise the following:

a random workload type associated with reading or writing using randomly addressed memory blocks;

a sequential workload type associated with reading or writing using contiguously addressed memory blocks; and

a mixed workload type associated with reading or writing using randomly addressed memory blocks and contiguously addressed memory blocks.

19. The apparatus of claim 16 , wherein the means for regulating the amount of available storage comprises means for determining the projected degradation based on the category.

20. The apparatus of claim 16 , wherein the means for regulating the amount of available storage comprises:

means for determining, based on the category and the projected degradation, whether to adjust the amount of available storage of the data storage system for use by a host system;

responsive to determining the amount of available storage of the data storage system be adjusted:

means for computing, based on a usage history by the host system, an actual usage of physical storage of the data storage system, by the host system;

means for determining that the actual usage of the physical storage by the host system satisfies a threshold value; and

means for adjusting the amount of available storage of the data storage system.

Assignments (10)
PARTIAL RELEASE OF SECURITY INTERESTS Recorded Apr 25, 2025
From: JPMORGAN CHASE BANK, N.A., AS AGENT
To: SANDISK TECHNOLOGIES, INC.
Reel/Frame 071382/0001 →
SECURITY AGREEMENT Recorded Apr 25, 2025
From: SANDISK TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 071050/0001 →
PATENT COLLATERAL AGREEMENT Recorded Aug 23, 2024
From: SANDISK TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A., AS THE AGENT
Reel/Frame 068762/0494 →
CHANGE OF NAME Recorded Jun 27, 2024
From: SANDISK TECHNOLOGIES, INC.
To: SANDISK TECHNOLOGIES, INC.
Reel/Frame 067982/0032 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 29, 2024
From: WESTERN DIGITAL TECHNOLOGIES, INC.
To: SANDISK TECHNOLOGIES, INC.
Reel/Frame 067567/0682 →
PATENT COLLATERAL AGREEMENT - DDTL LOAN AGREEMENT Recorded Aug 21, 2023
From: WESTERN DIGITAL TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 067045/0156 →
PATENT COLLATERAL AGREEMENT - A&R LOAN AGREEMENT Recorded Aug 21, 2023
From: WESTERN DIGITAL TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 064715/0001 →
RELEASE OF SECURITY INTEREST AT REEL 056285 FRAME 0292 Recorded Feb 8, 2022
From: JPMORGAN CHASE BANK, N.A.
To: WESTERN DIGITAL TECHNOLOGIES, INC.
Reel/Frame 058982/0001 →
SECURITY INTEREST Recorded May 19, 2021
From: WESTERN DIGITAL TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A., AS AGENT
Reel/Frame 056285/0292 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 8, 2021
From: SARKAR, JAY; PETERSON, CORY
To: WESTERN DIGITAL TECHNOLOGIES, INC.
Reel/Frame 055524/0651 →
Continuity (2)
Continuation 16223041 · Dec 17, 2018
Related Publication 20210173731A1 · Jun 10, 2021