Samsung Electronics Co., Ltd.

Songyi Han

Jiwon Kang

Seungwon Lee

Jongmin Baek

Sanghoon Ahn

Wookyung You

Naein Lee

Byunghee Kim

Byung-Kwon Cho

Hak-Sun Lee

Vietha Nguyen

YoungWoo Cho

Minkyoung Cho

Jiwon Yun

Young-ju Park

Inoue Naoya

Hyunsun Park

A processor-implemented method of performing a convolution operation is provided. The method includes obtaining input feature map data and kernel data, determine the kernel data based on a number of input channels of the input feature map, a number of output channels of an output feature map, and a number of groups of the input feature map data and a number of groups of the kernel data related to the convolution operation, and performing the convolution operation based on the input feature map data and the determined kernel data.

Neural network method and apparatus

A neural network apparatus for performing a matrix multiplication operation includes a memory having at least one program stored therein and a processor to perform one or more operations by executing the at least one program. The processor can determine whether to divide an initial weight in one of a column direction and a row direction according to whether a reshape operation and a transpose operation are performed before or after a matrix multiplication operation and generate division weights by dividing the initial weight by a head count in the determined direction. Also, the processor can generate intermediate feature maps by performing a matrix multiplication operation between the input feature map and the division weights and generate a final feature map based on the intermediate feature maps.

Apparatus and method of performing matrix multiplication operation of neural network

A method of updating a neural network model by a terminal device, includes training a local model using a local data set collected by a terminal device to generate a trained local model; receiving, from a server, an independent identically distributed (i.i.d.) global data set, the i.i.d. global data set being a data set sampled for each class in a plurality of predefined classes; implementing the trained local model by inputting the i.i.d. global data set and transmitting final inference results of the implemented trained local model to the server; and receiving, from the server, a global model updated based on the final inference results of the inference.

Method and system with neural network model updating

A semiconductor device includes an interlayer insulating layer including a first insulating layer on a substrate, and a plurality of interconnections in the first insulating layer. The interlayer insulating layer includes a first region, and a second region including an air gap. The air gap is defined between a pair of the interconnections in the second region. A top surface of the first insulating layer of the first region is lower than a top surface of at least one of the interconnections in the first region.

Planarized interlayer dielectric with air gap isolation

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Hwaseong-si, South Korea

Songyi Han