Designing adaptive neural networks for energy-constrained image classification-Reference-Cited by-同舟云学术

Designing adaptive neural networks for energy-constrained image classification

Published:2018-11-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference on Computer-Aided Design
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Author:

Stamoulis Dimitrios¹,Chin Ting-Wu (Rudy)¹,Prakash Anand Krishnan¹,Fang Haocheng¹,Sajja Sribhuvan¹,Bognar Mitchell¹,Marculescu Diana¹

Affiliation:

1. Carnegie Mellon University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3240765.3240796

Reference33 articles.

1. E. Cai etal 2016. Exploring aging deceleration in FinFET-based multi-core systems. In ICCAD. IEEE 1--8. 10.1145/2966986.2967039 E. Cai et al. 2016. Exploring aging deceleration in FinFET-based multi-core systems. In ICCAD. IEEE 1--8. 10.1145/2966986.2967039

2. Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks

3. Z. Chen D. Stamoulis and D. Marculescu. 2017. Profit: priority and power/performance optimization for many-core systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2017). Z. Chen D. Stamoulis and D. Marculescu. 2017. Profit: priority and power/performance optimization for many-core systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2017).

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