ELECTRONIC APPARATUS AND CONTROL METHOD THEREOF

    公开(公告)号:US20190278828A1

    公开(公告)日:2019-09-12

    申请号:US16295599

    申请日:2019-03-07

    Abstract: An electronic apparatus is provided. The electronic apparatus includes a storage storing object data and kernel data, and a processor including a plurality of processing elements arranged in a matrix formation, wherein the processor is configured to input corresponding first elements among a plurality of first elements included in the object data into processing elements arranged in a first row among the plurality of processing elements, and input a plurality of second elements included in the kernel data sequentially into the processing elements arranged in the first row to perform operations between the corresponding first elements and the plurality of second elements, to identify a depth in which a first element and a second element have a non-zero value, and to input the first element and the second element corresponding to the identified depth into a calculator included in each of the processing elements arranged in the first row to perform a convolution operation.

    PROCESSOR AND CONTROL METHODS THEREOF
    2.
    发明申请

    公开(公告)号:US20190129885A1

    公开(公告)日:2019-05-02

    申请号:US16143922

    申请日:2018-09-27

    Abstract: A processor for performing deep learning is provided herein. The processor includes a processing element unit including a plurality of processing elements arranged in a matrix form including a first row of processing elements and a second row of processing elements. The processing elements are fed with filter data by a first data input unit which is connected to the first row processing elements. A second data input unit feeds target data to the processing elements. A shifter composed of registers feeds instructions to the processing elements. A controller in the processor controls the processing elements, the first data input unit and second data input unit to process the filter data and target data, thus providing sum of products (convolution) functionality.

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