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A 25.1-TOPS/W Sparsity-Aware Hybrid CNN-GCN Deep Learning SoC for Mobile Augmented Reality

A 25.1-TOPS/W Sparsity-Aware Hybrid CNN-GCN Deep Learning SoC for Mobile Augmented Reality 150 150
Author(s): Wen-Cong Huang, I-Ting Lin, Ying-Sheng Lin, Wen-Ching Chen, Liang-Yi Lin, Nian-Shyang Chang, Chun-Pin Lin, Chi-Shi Chen, Chia-Hsiang Yang

Abstract:

Augmented reality (AR) has been applied to various mobile applications. Modern AR algorithms include neural networks, such as convolutional neural networks (CNNs) and graph convolutional networks (GCNs). The high computational complexity of these networks poses challenges for real-time operation on energy-constrained devices. This article presents the first energy-efficient hybrid CNN-GCN …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2024
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2024.3391665
Publisher: IEEE

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A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching

A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching 150 150
Author(s): Xiaoyu Feng, Wenyu Sun, Chen Tang, Xinyuan Lin, Jinshan Yue, Huazhong Yang, Yongpan Liu

Abstract:

Voxel-based point cloud networks composed of multiple kinds of sparse convolutions (SCONVs) play an essential role in emerging applications such as autonomous driving and visual navigation. Many researchers have proposed sparse processors for image applications. However, they cannot properly deal with three problems in the point cloud, including low efficiency …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 12
Year of Publication: 2024
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2024.3386878
Publisher: IEEE

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