Review of Optimal Convolutional Neural Network Accelerator Platforms for Mobile Devices

Hyun Kim

doi:10.5626/JCSE.2022.16.2.113

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한국정보과학회
Journal of Computing Science and Engineering 학술저널
Journal of Computing Science and Engineering Vol.16 No.2
2022.6 113 - 119 (7page)
DOI : 10.5626/JCSE.2022.16.2.113

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Hyun Kim (Seoul National University of Science and Technology)

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초록·키워드

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In recent years, convolutional neural networks (CNNs) have achieved remarkable performance enhancement, and researchers have endeavored to use CNN applications on power-constrained mobile devices. Accordingly, low-power and high-performance CNN accelerators for mobile devices are receiving significant attention. This paper presents the overall process of designing optimal CNN accelerator platforms for mobile devices based on algorithm, architecture, and memory system co-design while introducing various existing studies related to specific research fields.

#Convolutional neural networks #Mobile device #Network compression #Hardware accelerator #Low-power memory

참고문헌 (52)

참고문헌 신청

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