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A Quantitative Exploration of Collaborative Pruning and Approximation Computing Towards Energy Efficient Neural Networks 期刊论文
IEEE DESIGN & TEST, 2020, 卷号: 37, 期号: 1, 页码: 36-45
作者:  He, Xin;  Yan, Guihai;  Lu, Wenyan;  Zhang, Xuan;  Liu, Ke
收藏  |  浏览/下载:40/0  |  提交时间:2020/12/10
Resilience  Energy consumption  Approximate computing  Collaboration  Computational modeling  Artificial neural networks  Optimization  Neural network  Energy efficient computing  Network pruning  Approximate computing  
Joint Design of Training and Hardware Towards Efficient and Accuracy-Scalable Neural Network Inference 期刊论文
IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, 2018, 卷号: 8, 期号: 4, 页码: 810-821
作者:  He, Xin;  Lu, Wenyan;  Yan, Guihai;  Zhang, Xuan
收藏  |  浏览/下载:229/0  |  提交时间:2019/04/03
Approximate computing  neural network accelerator  hardware-oriented training  sensitivity analysis  energy efficient architecture  near threshold voltage  approximate multiplier