MULTI-STREAM SSD QOS MANAGEMENT
    11.
    发明申请

    公开(公告)号:US20200167097A1

    公开(公告)日:2020-05-28

    申请号:US16775262

    申请日:2020-01-28

    Abstract: A system and method for satisfying Quality of Service (QoS) attributes for a stream using a storage device with multi-stream capability is described. The storage device may include memory to store data. A host interface may receive requests, some of which may be associated with a stream. A host interface layer may schedule the requests in a manner that may satisfy the

    MULTI-NON-VOLATILE MEMORY SOLID STATE DRIVE BLOCK-LEVEL FAILURE PREDICTION WITH SEPARATE LOG PER NON-VOLATILE MEMORY

    公开(公告)号:US20230037270A1

    公开(公告)日:2023-02-02

    申请号:US17964013

    申请日:2022-10-11

    Abstract: A storage device is disclosed. A first storage media may store data. The first storage media may be of a first storage type and may be organized into at least two blocks. A second storage media may also store data. The second storage media may be of a second storage type different from the first type, and may also be organized into at least two blocks. A controller may manage reading data from and writing data to the first storage media and the second storage media. Metadata storage may store device-based log data for errors in the storage device. The drive-based log data may include a first log data for the first storage media and a second log data for the second storage media. An identification circuit may identify a suspect block in the at least two blocks in the first storage media and the second storage media, responsive to the device-based log data.

    SYSTEMS, METHODS, AND DEVICES FOR FAULT RESILIENT STORAGE

    公开(公告)号:US20220291996A1

    公开(公告)日:2022-09-15

    申请号:US17827657

    申请日:2022-05-27

    Abstract: A method of operating a storage device may include determining a fault condition of the storage device, selecting a fault resilient mode based on the fault condition of the storage device, and operating the storage device in the selected fault resilient mode. The selected fault resilient mode may include one of a power cycle mode, a reformat mode, a reduced capacity read-only mode, a reduced capacity mode, a reduced performance mode, a read-only mode, a partial read-only mode, a temporary read-only mode, a temporary partial read-only mode, or a vulnerable mode. The storage device may be configured to perform a namespace capacity management command received from the host. The namespace capacity management command may include a resize subcommand and/or a zero-size namespace subcommand. The storage device may report the selected fault resilient mode to a host.

    FAULT RESILIENT STORAGE DEVICE
    18.
    发明申请

    公开(公告)号:US20220012145A1

    公开(公告)日:2022-01-13

    申请号:US17109053

    申请日:2020-12-01

    Abstract: A storage device, and a method for operating a storage device. In some embodiments, the storage device includes storage media, and the method includes: determining, by the storage device, that the storage device is in a first fault state from which recovery is possible by power cycling the storage device or by formatting the storage media; determining, by the storage device, that the storage device is in a second fault state from which partial recovery is possible by operating the storage device with reduced performance, with reduced capacity, or in a read-only mode; and operating the storage device with reduced performance, with reduced capacity, or in the read-only mode.

    SYSTEMS AND METHODS FOR PREDICTING STORAGE DEVICE FAILURE USING MACHINE LEARNING

    公开(公告)号:US20210264294A1

    公开(公告)日:2021-08-26

    申请号:US15931573

    申请日:2020-05-13

    Abstract: A method for predicting a time-to-failure of a target storage device may include training a machine learning scheme with a time-series dataset, and applying the telemetry data from the target storage device to the machine learning scheme which may output a time-window based time-to-failure prediction. A method for training a machine learning scheme for predicting a time-to-failure of a storage device may include applying a data quality improvement framework to a time-series dataset of operational and failure data from multiple storage devices, and training the scheme with the pre-processed dataset. A method for training a machine learning scheme for predicting a time-to-failure of a storage device may include training the scheme with a first portion of a time-series dataset of operational and failure data from multiple storage devices, testing the machine learning scheme with a second portion of the time-series dataset, and evaluating the machine learning scheme.

    MULTISTREAMING IN HETEROGENEOUS ENVIRONMENTS

    公开(公告)号:US20210232321A1

    公开(公告)日:2021-07-29

    申请号:US17229857

    申请日:2021-04-13

    Abstract: A storage device is disclosed. The storage device may include storage to store data, which may include a first storage of a first type and a second storage of a second type. The storage device may support a number of device streams, some of which associated with the first storage and some associated with the second storage. The storage device may also include a streaming capabilities analyzer that may inventory the streaming capabilities for the storage device. Finally, the storage device may include a transmitter to transmit the streaming capabilities of the storage device to a storage manager.

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