On-Device Dynamic DNN Inference through Spatial Sparsity Exploitation

Deep Neural Networks (DNNs) are crucial for applications like autonomous driving, augmented reality, and mixed reality. Growing concerns about latency and privacy increasingly require deploying task-specific networks on mobile and edge devices. Extensive research focuses on accelerating DNNs while p...

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Bibliographic Details
Published in:	GetMobile (New York, N.Y.) N.Y.), 2025-10, Vol.29 (3), p.35-38
Main Authors:	Liu, Renyuan, Leng, Yuyang, Tian, Shilei, Hu, Shaohan, Chen, Richard, Yao, Shuochao
Format:	Article
Language:	English
Subjects:	Computer systems organization Computer systems organization / Architectures Computer systems organization / Architectures / Other architectures Computer systems organization / Architectures / Other architectures / Neural networks Computing methodologies Computing methodologies / Machine learning Computing methodologies / Machine learning / Machine learning approaches Computing methodologies / Machine learning / Machine learning approaches / Neural networks Hardware Hardware / Emerging technologies Human-centered computing Human-centered computing / Ubiquitous and mobile computing Human-centered computing / Ubiquitous and mobile computing / Ubiquitous and mobile computing theory, concepts and paradigms Human-centered computing / Ubiquitous and mobile computing / Ubiquitous and mobile computing theory, concepts and paradigms / Mobile computing Human-centered computing / Ubiquitous and mobile computing / Ubiquitous and mobile devices Human-centered computing / Ubiquitous and mobile computing / Ubiquitous and mobile devices / Smartphones
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