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.
| Original language | English |
|---|---|
| Pages (from-to) | 113-119 |
| Number of pages | 7 |
| Journal | Journal of Computing Science and Engineering |
| Volume | 16 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2022 |
Keywords
- Convolutional neural networks
- Hardware accelerator
- Lowpower memory
- Mobile device
- Network compression
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