Accelerator in convolutional neural network and method for operating the same

A convolutional neural network and accelerator technology, applied in the field of accelerators, can solve the problems of memory storage space wasting memory access, external memory wasting energy, etc., and achieve the effect of reducing overall power consumption

Inactive Publication Date: 2018-02-06
SAMSUNG ELECTRONICS CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In this process, the overlapping part of the input image is copied into the memory to be stored repeatedly, and this leads to waste of memory storage space and unnecessary memory access
Accesses to external memory end up wasting energy

Method used

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  • Accelerator in convolutional neural network and method for operating the same
  • Accelerator in convolutional neural network and method for operating the same
  • Accelerator in convolutional neural network and method for operating the same

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Embodiment Construction

[0032] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this case, it should be noted that the same constituent elements are given the same reference numerals in the respective drawings. Also, detailed descriptions of known functions and configurations that may obscure the subject matter of the present disclosure will be omitted.

[0033] In explaining the embodiments of the present disclosure, descriptions of technical contents that are known in the art to which the present disclosure pertains and are not directly related to the present disclosure will be omitted. This is to more clearly divert the subject matter of the present disclosure without making it implicit by omitting unnecessary explanation.

[0034] For the same reason, in the drawings, the size and relative size of some constituent elements may be exaggerated, omitted, or briefly shown. In addition, the size of each constitue...

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Abstract

The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system witha technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. A Processing Element (PE) implemented in an accelerator in a convolutional neural network, which includes a first buffer configured to transfer input data to one other PE, and a second buffer configured to transmit to an outside output data that is processed on the basisof the input data; and an operation unit configured to generate output data.

Description

technical field [0001] The present disclosure relates to an accelerator for convolutional neural networks only, and more particularly, to a method and apparatus capable of performing multi-layer pooling to minimize access to external memory. Background technique [0002] To meet the increasing demands of wireless data traffic since the deployment of 4G communication systems, efforts have been made to develop improved 5G or pre-5G communication systems. Therefore, 5G or pre-5G communication system is also called "super 4G network" or "post-LTE system". 5G communication systems are considered to be implemented in higher frequency (mmWave) frequency bands (eg, 60GHz band) in order to achieve higher data rates. In order to reduce the propagation loss of radio waves and increase the transmission distance, beamforming, massive multiple-input multiple-output (MIMO), full-scale MIMO (FD-MIMO), array antennas, analog beamforming, massive Antenna technology. In addition, in the 5G ...

Claims

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Application Information

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IPC IPC(8): G06N3/08G06N3/063
CPCG06N3/063G06N3/084G06N3/045G06N3/08G06N3/02G06T1/20G06N3/04
Inventor 朴永焕金庆勋李承远赵韩秀金硕镇
Owner SAMSUNG ELECTRONICS CO LTD
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