Western Digital Technologies, Inc.

Cory J Peterson

Jay Sarkar

Vidyabhushan Mohan

Yao Zhang

Amir Sanayei

David Robison Hall

Daniel Lee Helmick

Bernd Lamberts

Remmelt Pit

Kris Victor Schouterden

Shad Henry Thorstenson

Andy Larson

A Data Storage Device (DSD) includes a memory for storing data, and a controller configured to execute firmware or code to perform a task. While performing the task, the controller is further configured to assign unique identifiers to respective firmware or code portions that are executed to perform the task, and create a list or data structure including the unique identifier assigned to the firmware or code portion that created the task. A unique identifier is added to the list or data structure for each firmware or code portion executed for the task. The list or data structure indicates the order in which the firmware or code portions are executed.

Exception analysis for data storage devices

Systems and methods for solid-state storage drive-level failure prediction and health metric are described. A plurality of host-write commands are received at a solid-state storage device. A number of drive-writes per day based on the on the plurality of host-write commands is determined. An aggregated amount of degradation to one or more internal non-volatile memory components based on the number of drive-writes per day is determined. Using a machine-learned model, a probability of failure value based on a set of parameter data and the aggregated amount of degradation to the non-volatile memory component is generated. An alert is generated, based on the probability of failure value or degradation threshold.

Method and system involving degradation of non-volatile memory based on write commands and drive-writes

A method of error management includes, in response to a read request for first data from a first storage device of a plurality of storage devices under one or more common data protection schemes, receiving a read uncorrectable indication regarding the first data, obtaining uncorrected data and metadata of an LBA associated with the first data, and obtaining the same LBA from one or more other storage devices of the plurality. The method further includes comparing the uncorrected data with the data and metadata from the other storage devices, speculatively modifying the uncorrected data based, at least in part, on the other data to create a set of reconstructed first data codewords, and, in response to a determination that one of the reconstructed first data codewords has recovered the first data, issuing a write_raw command to rewrite the modified data and associated metadata to the first storage device.

Method and system for host-assisted data recovery assurance for data center storage device architectures

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.

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

Data storage systems and methods for autonomously adapting data storage system performance, capacity and/or operational requirements

Method and system for a storage (SSD) drive-level failure and health prediction leveraging machine learning on internal parametric data

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Rochester, MN, United States of America

Cory J Peterson