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In hardware-aware Differentiable Neural Architecture Search (DNAS), it is challenging to compute gradients of hardware metrics to perform architecture search.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Deep learning
Yann LeCun, Y. Bengio, and Geoffrey Hinton · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Eyeriss: An energy-efficient reconfigurable accelerator for deep convolutional neural networks
Yu-Hsin Chen, Tushar Krishna, Joel S Emer, and Vivienne Sze · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Going deeper with embedded FPGA platform for convolutional neural network
Jiantao Qiu, Jie Wang, Song Yao, Kaiyuan Guo, Boxun Li, Erjin Zhou, Jincheng Yu, Tianqi Tang, Ningyi Xu, Sen Song, et al · 2016
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Designing neural network architectures using reinforcement learning
Bowen Baker, Otkrist Gupta, Nikhil Naik, and Ramesh Raskar · 2017
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In-datacenter performance analysis of a tensor processing unit
Norman P Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, et al · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Exploring heterogeneous algorithms for accelerating deep convolutional neural networks on FPGAs
Qingcheng Xiao, Yun Liang, Liqiang Lu, Shengen Yan, and Yu-Wing Tai · 2017
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc V Le · 2017
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Progressive neural architecture search
Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan Yuille, Jonathan Huang, and Kevin Murphy · 2018
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Efficient neural architecture search via parameters sharing
Hieu Pham, Melody Guan, Barret Zoph, Quoc Le, and Jeff Dean · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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TGPA: tile-grained pipeline architecture for low latency CNN inference
Xuechao Wei, Yun Liang, Xiuhong Li, Cody Hao Yu, Peng Zhang, and Jason Cong · 2018
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DNNBuilder: an automated tool for building high-performance DNN hardware accelerators for FPGAs
Xiaofan Zhang, Junsong Wang, Chao Zhu, Yonghua Lin, Jinjun Xiong, Wen-mei Hwu, and Deming Chen · 2018
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ProxylessNAS: Direct neural architecture search on target task and hardware
Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, and Kurt Keutzer · 2019
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SNAS: stochastic neural architecture search
Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin · 2019
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Nas-bench-101: Towards reproducible neural architecture search
Chris Ying, Aaron Klein, Eric Christiansen, Esteban Real, Kevin Murphy, and Frank Hutter · 2019
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NAS-Bench-201: Extending the scope of reproducible neural architecture search
Xuanyi Dong and Yi Yang · 2020
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BRP-NAS: Prediction-based NAS using GCNs
Lukasz Dudziak, Thomas Chau, Mohamed Abdelfattah, Royson Lee, Hyeji Kim, and Nicholas Lane · 2020
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Standing on the shoulders of giants: Hardware and neural architecture co-search with hot start
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Han Cai, Ligeng Zhu, and Song Han · 2019
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Chamnet: Towards efficient network design through platform-aware model adaptation
Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, and Niraj K. Jha · 2019
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Searching for a robust neural architecture in four gpu hours
Xuanyi Dong and Yi Yang · 2019
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FPGA/DNN co-design: An efficient design methodology for iot intelligence on the edge
Cong Hao, Xiaofan Zhang, Yuhong Li, Sitao Huang, Jinjun Xiong, Kyle Rupnow, Wen-mei Hwu, and Deming Chen · 2019
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Searching for mobilenetv3
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, and Hartwig Adam · 2019
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Darts: Differentiable architecture search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2019
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Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V Le · 2019
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Weiwen Jiang, Lei Yang, Sakyasingha Dasgupta, Jingtong Hu, and Yiyu Shi · 2020
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Fbnetv2: Differentiable neural architecture search for spatial and channel dimensions
Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, et al · 2020
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AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs
Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Yongan Zhang, Yue Wang, Chaojian Li, Zetong Guan, Deming Chen, and Yingyan Lin · 2020
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HybridDNN: A framework for high-performance hybrid dnn accelerator design and implementation
Hanchen Ye, Xiaofan Zhang, Zhize Huang, Gengsheng Chen, and Deming Chen · 2020
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SkyNet: a hardware-efficient method for object detection and tracking on embedded systems
Xiaofan Zhang, Haoming Lu, Cong Hao, Jiachen Li, Bowen Cheng, Yuhong Li, Kyle Rupnow, Jinjun Xiong, Thomas Huang, Honghui Shi, Wen-mei Hwu, and Deming Chen · 2020
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DNN-chip predictor: An analytical performance predictor for DNN accelerators with various dataflows and hardware architectures
Yang Zhao, Chaojian Li, Yue Wang, Pengfei Xu, Yongan Zhang, and Yingyan Lin · 2020
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NATS-Bench: Benchmarking nas algorithms for architecture topology and size
Xuanyi Dong, Lu Liu, Katarzyna Musial, and Bogdan Gabrys · 2021
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Hw-nas-bench: Hardware-aware neural architecture search benchmark
Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, and Yingyan Lin · 2021
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Vitis High-Level Synthesis, 2021
Xilinx · 2021
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