Samsung Electronics Co., Ltd.

Seoul National University

Deokjin Joo

Namjoon Kim

Sehwan Lee

Joonho Song

Kiyoung Choi

Sujeong Jo

Hossein Moradian Sardroudi

A method of processing an add operation in a processing apparatus includes acquiring sub-operands from input operands each having an n-bit precision, acquiring intermediate addition results by performing add operations of sub-operands in parallel by using adders, bit-shifting each of the intermediate addition results such that the intermediate addition results correspond to original bit positions in the input operands, and outputting a final addition result of the add operations of the input operands based on the bit-shifted intermediate addition results.

Processing apparatus and method of processing add operation therein

A method of performing an operation in a neural network apparatus may include acquiring operation groups each comprising at least one input feature map and at least one kernel, and tag information corresponding to each of the operation groups, determining an operating unit in an idle state from among operating units, performing, at the operating unit in the idle state, a convolution operation between an input feature map and a kernel included in a operation group from among the operation groups to create an intermediate feature map, determining, based on tag information corresponding to the operation group, a post-processing unit from among post-processing units, and creating, at the post-processing unit, an output feature map using the intermediate feature map.

Apparatus and method for performing a recognition operation in a neural network

A processor-implemented method of performing convolution operations in a neural network includes generating a plurality of first sub-bit groups and a plurality of second sub-bit groups, respectively from at least one pixel value of an input feature map and at least one predetermined weight, performing a convolution operation on a first pair that includes a first sub-bit group including a most significant bit (MSB) of the at least one pixel value and a second sub-bit group including an MSB of the at least one predetermined weight, based on the plurality of second sub-bit groups, obtaining a maximum value of a sum of results for convolution operations of remaining pairs excepting the first pair, and based on a result of the convolution operation on the first pair and the maximum value, determining whether to perform the convolution operations of the remaining pairs.

Method and apparatus with neural network convolution operations

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Seongnam-si, South Korea

Deokjin Joo