Samsung Electronics Co., Ltd.

Seoul National University

Channoh Kim

Yoojin Kim

Jun-Woo Jang

Hyunsun Park

Sungmin Kim

Jae Wook Lee

Sehwan Lee

Jaehyeok Kim

Hyun Sun Park

A memory mapping method includes storing a feature map including a plurality of sets of data used for a neural network operation in a memory, shifting a position of a portion of the data included in the feature map that is stored in the memory based on a parameter of the neural network operation, and outputting data requested by the neural network operation from the feature map in which the position of the portion is shifted based on a memory bandwidth.

Memory mapping method and apparatus

A computing method and device with data sharing are provided. The method includes loading, by a loader, input data of an input feature map stored in a memory in loading units according to a loading order, storing, by a buffer controller, the loaded input data in a reuse buffer of an address rotationally allocated according to the loading order, and transmitting, by each of a plurality of senders, to an executer respective input data corresponding to each output data of respective convolution operations among the input data stored in the reuse buffer, wherein portions of the transmitted respective input data overlap other.

Computing method and device with data sharing

A data transmission method for a convolution operation, and a convolution operation apparatus including a fetcher that includes a loader, at least one sender, a buffer controller, and a reuse buffer. The method includes loading, by the loader, input data of an input feature map according to a loading order, based on input data stored in the reuse buffer, a shape of a kernel to be used for a convolution operation, and two-dimensional (2D) zero-value information of weights of the kernel; storing, by the buffer controller, the loaded input data in the reuse buffer of an address cyclically assigned according to the loading order; and selecting, by each of the at least one sender, input data corresponding to each output data of a convolution operation among the input data stored in the reuse buffer, based on one-dimensional (1D) zero-value information of the weights, and outputting the selected input data.

Data transmission method for convolution operation, fetcher, and convolution operation apparatus

Provided is a computing device according to an embodiment of the present disclosure including an integrated register file configured to store a first variable type and a first variable value of a first variable, and a second variable type and a second variable value of a second variable, a calculator configured to perform a first calculation on the first and second variables according to the first and second variable types, and output a first calculation result, and a type rule table comprising a plurality of entries and, when there is an entry corresponding to a type of the first calculation, and the first and second variable types, configured to output a type of the first calculation result.

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Suwon-si, South Korea

Channoh Kim