JCSE, vol. 16, no. 2, pp.113-119, June, 2022

DOI: http://dx.doi.org/10.5626/JCSE.2022.16.2.113

Review of Optimal Convolutional Neural Network Accelerator Platforms for Mobile Devices

Hyun Kim
Department of Electrical and Information Engineering, Research Center for Electrical and Information Technology, Seoul National University of Science and Technology, Seoul, Korea

Abstract: 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.

Keyword: Convolutional neural networks; Mobile device; Network compression; Hardware accelerator; Lowpower

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