Data management for efficient low power mode handling in a storage device

    公开(公告)号:US11604592B2

    公开(公告)日:2023-03-14

    申请号:US17339547

    申请日:2021-06-04

    Abstract: A method and apparatus for identifying data that is to be accessible in a low power state of a data storage device, and store this data in a physical (or logical) block that will be accessible in a low power state of the data storage device. Low power accessible data may be identified by host metadata of the data, indicating access is needed in a low power state. In other embodiments, the data storage device may learn the power state in which data should be accessible. In these embodiments, a controller stores information regarding the power state of a namespace in which the data is stored as an indicator to make the data accessible in a low power state. Alternatively, the controller stores a previous power state in which the data was accessed as an indicator to make the data accessible in a low power state.

    DATA SHAPING TO REDUCE ERROR RATES IN SOLID STATE MEMORY DEVICES

    公开(公告)号:US20190258423A1

    公开(公告)日:2019-08-22

    申请号:US15900531

    申请日:2018-02-20

    Abstract: Systems and methods are described for reducing error rates on data storage devices by applying data shaping to data written to such devices in order to avoid error-prone states on cells within the devices. Different states of individual cells (such as those representing different bit patterns) may have different propensities for error, and these propensities may vary during operation of a device. Thus, a device as disclosed herein may determine error-prone states for a cell or group of cells, and apply data shaping to data written to such cells to reduce the likelihood that writing the data places the cell or cells into an error-prone state. Data shaping may be used, for example, to increase the occurrence of “0” bits within input data, thus avoiding error-prone low voltage states that may be used to represent a series of “1” bits.

    Machine Learning Supplemented Storage Device Calibration

    公开(公告)号:US20220121985A1

    公开(公告)日:2022-04-21

    申请号:US17180247

    申请日:2021-02-19

    Abstract: Methods are provided for deploying machine learning operations within existing storage devices for streamlining various calibration processes. Machine learning operations are specifically designed to generate inference data as a substitute for various measurements taken during calibration. These operations may be verified through additional sample measurements and rolled back when the results of the machine learning operations are outside of a range of approved values. Storage devices designed to utilize machine learning methods within calibration processes can include a non-volatile memory for storing data, executable instructions, and a processor to conduct a variety of steps. The steps can include executing an application stored in the non-volatile memory and receiving a request for measurement data from the application. The steps can further determine if the requested data is suitable for substitution by an inference and subsequently select at least one machine learning model for generating a suitable inference.

    Data driven ICAD graph generation

    公开(公告)号:US10862512B2

    公开(公告)日:2020-12-08

    申请号:US16452466

    申请日:2019-06-25

    Abstract: A storage device may include a decoder configured to connect bits to a content node based on content-aware decoding process. The content-aware decoding process may be dynamic and determine connection structures of bits and content nodes based on patterns in data. In some cases, the decoder may connect non-adjacent bits to a content node based on a content-aware decoding process. In other cases, the decoder may connect a first number of bits to a first content node and a second number of bits to a second content node. In such cases, the first number of bits and the second number of bits are a different number.

    MEMORY DEVICE WITH ENHANCED ERROR CORRECTION

    公开(公告)号:US20200235757A1

    公开(公告)日:2020-07-23

    申请号:US16254575

    申请日:2019-01-22

    Abstract: Disclosed herein are memory devices, systems, and methods of content-aware decoding of encoded data. In one aspect, an encoded data chunk is received and one or more characteristics, such as source statistics, are determined. A similar data chunk (that may, e.g., contain data of a similar type) with comparable statistics may be sought. The similar data chunk may, for example, have source statistics that are positively correlated to the source statistics of the encoded data chunk to be decoded. Decoder parameters for the encoded data may be set to correspond with decoder parameters suited to the similar data chunk. The encoded data chunk is decoded using the new decoder parameters. Decoding encoded data based on content can enhance performance, reducing decoding latency and/or power consumption.

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