Hanrui Wang

QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits

Jul 22, 2021
Hanrui Wang, Yongshan Ding, Jiaqi Gu, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han

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* 15 pages, 23 figures. Code available at https://github.com/mit-han-lab/pytorch-quantum

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SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning

Jan 04, 2021
Hanrui Wang, Zhekai Zhang, Song Han

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* Published as a conference paper in HPCA 2021; 15 pages, 23 figures

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Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

Aug 13, 2020
Haotian Tang, Zhijian Liu, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, Song Han

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* ECCV 2020. The first two authors contributed equally to this work. Project page: http://spvnas.mit.edu/

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HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

May 28, 2020
Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han

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* Accepted to ACL 2020. 14 pages, 12 figures. Code available at http://github.com/mit-han-lab/hardware-aware-transformers.git

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MicroNet for Efficient Language Modeling

May 16, 2020
Zhongxia Yan, Hanrui Wang, Demi Guo, Song Han

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* Accepted by PMLR

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GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning

Apr 30, 2020
Hanrui Wang, Kuan Wang, Jiacheng Yang, Linxiao Shen, Nan Sun, Hae-Seung Lee, Song Han

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* Accepted to the 57th Design Automation Conference (DAC 2020); 6 pages, 8 figures

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Learning to Design Circuits

Jan 17, 2019
Hanrui Wang, Jiacheng Yang, Hae-Seung Lee, Song Han

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* The first two authors contributed equally to this work

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Hanrui Wang

QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits

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SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning

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Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

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HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

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MicroNet for Efficient Language Modeling

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GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning

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Learning to Design Circuits

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