Samsung Electronics Co., Ltd.

Keshava Prasad Nagaraja

Dae-Hyun Kim

Kyoung-Hoon Kim

Hyunjung Kim

Hyun-Jung Kim

Suk-jin Kim

Hyun-jung Kim

Young-hwan Park

Dong-kwan Suh

Han-su Cho

Kyoung-hoon Kim

Younghwan Park

Kyounghoon Kim

Young-Hwan Park

Hansu Cho

Sukjin Kim

Dong-Kwan Suh

Suk-Jin Kim

Dongkwan Suh

Han-Su Cho

Disclosed is an electronic device. The An electronic device including a storage, and a processor configured to perform convolution processing on target data and kernel data based on stride information that indicates an interval at which the kernel data is applied to the target data stored in the storage, in which the processor is further configured to divide the target data into a plurality of pieces of sub-data based on first stride information, perform the convolution processing on the plurality of pieces of sub-data and a plurality of pieces of sub-kernel data respectively corresponding to the plurality of pieces of sub-data based on second stride information that is different from the first stride information, and combine a plurality of processing results, the plurality of pieces of sub-kernel data are obtained by dividing the kernel data based on the first stride information, and the second stride information indicates that the interval at which the kernel data is applied to the target data is 1.

Electronic device and control method thereof

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.

Electronic apparatus and control method thereof

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.

Processor and control methods thereof for performing deep learning

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Suwon-si, South Korea

Keshava Prasad Nagaraja