MEMORY DEVICE AND OPERATION METHOD PERFORMED BY THE SAME

    公开(公告)号:US20230266913A1

    公开(公告)日:2023-08-24

    申请号:US17865824

    申请日:2022-07-15

    CPC classification number: G06F3/0655 G06F3/0604 G06F3/0679

    Abstract: A memory device and an operation method performed by the memory device are disclosed. The memory device includes a plurality of memories, and one or more memory banks including an in-memory operator configured to encode data stored in at least one of the plurality of memories, perform an assigned operation based on the encoded data, and decode the encoded data on which the operation is performed, and a memory controller configured to control the one or more memory banks.

    METHOD AND APPARATUS WITH DATA LOADING

    公开(公告)号:US20230140239A1

    公开(公告)日:2023-05-04

    申请号:US17868361

    申请日:2022-07-19

    Abstract: A processor-implemented method with data loading includes: dividing a training data set into a plurality of subsets based on sizes of a plurality of data files included in the training data set; loading, from each of the plurality of subsets, a portion of data files in the subset to a plurality of processors based on a proportion of a number of data files of the plurality of subsets in the subset and a batch size of distributed training; and reallocating, based on sizes of data files loaded to processors in a same group among the plurality of processors, the loaded data files to the processors in the same group.

    METHOD AND APPARATUS FOR PROCESSING CONVOLUTION OPERATION ON LAYER IN NEURAL NETWORK

    公开(公告)号:US20210279568A1

    公开(公告)日:2021-09-09

    申请号:US17015122

    申请日:2020-09-09

    Abstract: Disclosed are methods and apparatuses for processing a convolution operation on a layer in a neural network. The method includes extracting a first target feature vector from a target feature map, extracting a first weight vector matched with the first target feature vector from a first-type weight element, based on matching relationships for depth-wise convolution operations between target feature vectors of the target feature map and weight vectors of the first-type weight element, generating a first intermediate feature vector by performing multiplication between the first target feature vector and the first weight vector, generating a first hidden feature vector by accumulating the first intermediate feature vector and a second intermediate feature vector generated based on a second target feature vector, and generating a first output feature vector of an output feature map based on a point-wise convolution operation between the first hidden feature vector and a second-type weight element.

    METHOD AND APPARATUS WITH DATA LOADING
    10.
    发明公开

    公开(公告)号:US20240231944A1

    公开(公告)日:2024-07-11

    申请号:US18351737

    申请日:2023-07-13

    CPC classification number: G06F9/5055 G06F16/1724

    Abstract: A processor-implemented method with data loading includes: based on sizes of a plurality of data files in a training dataset, dividing the training dataset into a plurality of sub-sets; loading some data files in each sub-set into a plurality of processors; determining a packing combination of one or more data files loaded to processors in a same group among the plurality of processors, based on a ratio of a number of data files between the plurality of sub-sets and a batch size of distributed training; determining packed data files by packing the one or more data files according to the packing combination; and reallocating the packed data files to the processors in the same group.

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