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    Deep solid state device (deep-SSD): a neural network based persistent data storage
    1.
    发明授权
    Deep solid state device (deep-SSD): a neural network based persistent data storage 有权

    公开(公告)号：US11449268B2

    公开(公告)日：2022-09-20

    申请号：US16430408

    申请日：2019-06-03

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Ramdas P. Kachare ,  Manali Sharma

    IPC: G06F3/06 ,  G06N3/08

    Abstract: According to one general aspect, an apparatus may include a host interface circuit configured to receive a memory access request, wherein the memory access request is associated with a data set. The apparatus may include a non-volatile memory storage circuit configured to create and store a transformed data set. The apparatus may include a translation circuit comprising at least one machine learning circuit. The translation circuit may be configured to: in response to a write memory access, convert an original version of the data set to the transformed data set, and in response to a read memory access, convert the transformed data set to a reconstructed data set.

    In-storage-based data processing using machine learning
    2.
    发明授权
    In-storage-based data processing using machine learning 有权

    公开(公告)号：US11443142B2

    公开(公告)日：2022-09-13

    申请号：US16826066

    申请日：2020-03-20

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Sompong Paul Olarig ,  Chandranil Chakraborttii ,  Manali Sharma ,  Praveen Krishnamoorthy

    IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08 ,  G06V10/56

    Abstract: A programmable data storage device configured to process images via an embedded processor is disclosed. The processor identifies luminance and chrominance data of a received image, and retrieves a first machine learning model stored in the storage device. The first model is applied for making a first prediction about the image based on luminance data, and a first determination is made in regards to a criterion. In response to making the first determination, a first label associated with the first prediction is returned. A second determination is also made in regards to the criterion. In response to making the second determination, a second machine learning model stored in the storage device is retrieved. The second machine learning model is applied for making a second prediction about the image based on the color data associated with the image, and a second label associated with the second prediction is determined.

    IN-STORAGE-BASED DATA PROCESSING USING MACHINE LEARNING
    5.
    发明申请
    IN-STORAGE-BASED DATA PROCESSING USING MACHINE LEARNING 有权

    公开(公告)号：US20210256311A1

    公开(公告)日：2021-08-19

    申请号：US16826066

    申请日：2020-03-20

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Sompong Paul Olarig ,  Chandranil Chakraborttii ,  Manali Sharma ,  Praveen Krishnamoorthy

    IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08 ,  G06K9/46

    Abstract: A programmable data storage device configured to process images via an embedded processor is disclosed. The processor identifies luminance and chrominance data of a received image, and retrieves a first machine learning model stored in the storage device. The first model is applied for making a first prediction about the image based on luminance data, and a first determination is made in regards to a criterion. In response to making the first determination, a first label associated with the first prediction is returned. A second determination is also made in regards to the criterion. In response to making the second determination, a second machine learning model stored in the storage device is retrieved. The second machine learning model is applied for making a second prediction about the image based on the color data associated with the image, and a second label associated with the second prediction is determined.

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