Publications

Zuodong Zhang, Meng Li, Yibo Lin, Runsheng Wang, Ru Huang (2023). READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.

Meng Li, Yixuan Hu, Tengyu Zhang, Renjie Wei, Yawen Zhang, Ru Huang, Runsheng Wang (2023). Not your father’s stochastic computing (SC)! Efficient yet Accurate End-to-End SC Accelerator Design. In International Conference on ASIC (ASICON) 2023.

Wenxuan Zeng, Meng Li, Wenjie Xiong, Tong Tong, Wen-jie Lu, Jin Tan, Runsheng Wang, Ru Huang (2023). MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention. In International Conference on Computer Vision (ICCV) 2023.

Shuzhang Zhong, Meng Li, Yun (Eric) Liang, Runsheng Wang, Ru Huang (2023). Memory-aware Scheduling for Complex Wired Networks with Iterative Graph Optimization. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.

Tianshi Xu, Meng Li, Runsheng Wang, Ru Huang (2023). Falcon: Accelerating Homomorphically Encrypted Convolutions for Efficient Private Mobile Network Inference. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.

Yixuan Hu, Tengyu Zhang, Meng Li, Renjie Wei, Liangzhen Lai, Yuan Wang, Runsheng Wang, Ru Huang (2023). Efficient Non-Linear Adder for Stochastic Computing with Approximate Spatial-Temporal Sorting Network. In Design Automation Conference (DAC) 2023.

Zuodong Zhang, Zizheng Guo, Yibo Lin, Meng Li, Runsheng Wang, Ru Huang (2023). AVATAR: An Aging- and Variation-Aware Dynamic Timing Analyzer for Error-Efficient Computing. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2023).

Zuodong Zhang, Meng Li, Yibo Lin, Runsheng Wang, Ru Huang (2023). READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2023 (extended abstract).

Yixuan Hu, Tengyu Zhang, Renjie Wei, Meng Li, Runsheng Wang, Yuan Wang, Ru Huang (2023). Accurate yet Efficient Stochastic Computing Neural Acceleration with High Precision Residual Fusion. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2023.

Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad (2022). BiT: Robustly Binarized Multi-distilled Transformer. In Conference on Neural Information Processing Systems (NeurIPs) 2022.

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Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin (2022). Depth Shrink: Empowering Hardware-Friendly Shallow Neural Networks. In Conference on Machine Learning (ICML) 2022.

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Haichuan Yang, Yuan Shangguan, Dilin Wang, Meng Li, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra (2022). Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet. In International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022.

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Xin Dong, Ziyun Li, Meng Li, Zhongnan Qu, Barbara De Salvo, Chiao Liu, Hsiang-Tsung Kung (2022). SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems. In Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Pan (2022). Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation. In Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

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Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra (2022). NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. In Conference on Learning Representations (ICLR) 2022.

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Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li, Haoran You, Meng Li, Vikas Chandra, Yingyan Lin (2021). DNA: Differentiable Network-Accelerator Co-Search. In International Symposium on Low Power Electronics and Design (ISLPED) 2021.

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Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra (2021). AlphaNet: Improved Training of Supernets with Alpha-Divergence. In Conference on Machine Learning (ICML) 2021 (Long Oral).

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Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra (2021). AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. In Conference on Computer Vision and Pattern Recognition (CVPR) 2021.

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Meng Li, Yilei Li, Vikas Chandra (2021). Improving efficiency in neural network accelerator using operands hamming distance optimization. In Asia and South Pacific Design Automation Conference (ASP-DAC) 2021.

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Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu (2020). KeepAugment: A Simple Information-Preserving Data Augmentation Approach. In Conference on Computer Vision and Pattern Recognition (CVPR) 2021.

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Lei Yang, Zheyu Yan, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi (2020). Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks. In ACM/IEEE Design Automation Conference (DAC) 2020.

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Meng Li, Kaveh Shamsi, Yier Jin, David Z Pan (2018). TimingSAT: Decamouflaging timing-based logic obfuscation. In IEEE International Test Conference (ITC) 2018.

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Meng Li, David Z. Pan (2018). A Synergistic Framework for Hardware IP Privacy and Integrity Protection. In Springer (2018).

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Meng Li, Bei Yu, Yibo Lin, Xiaoqing Xu, Wuxi Li, David Z. Pan (2018). A Practical Split Manufacturing Framework for Trojan Prevention via Simultaneous Wire Lifting and Cell Insertion. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2018).

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Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vikas Chandra (2018). Federated Learning with Non-IID Data. In arXiv:1806.00582 (2018).

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Meng Li, Bei Yu, Yibo Lin, Xiaoqing Xu, Wuxi Li, David Z. Pan (2018). A Practical Split Manufacturing Framework for Trojan Prevention via Simultaneous Wire Lifting and Cell Insertion. In Asia and South Pacific Design Automation Conference (ASP-DAC) 2018.

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Meng Li, Liangzhen Lai, Naveen Suda, Vikas Chandra, David Z. Pan (2018). PrivyNet: A Flexible Framework for Privacy-Preserving Deep Neural Network Training. In arXiv:1709:06161 (2018).

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Meng Li, Kaveh Shamsi, Travis Meade, Zheng Zhao, Bei Yu, Yier Jin, David Z Pan (2017). Provably secure camouflaging strategy for IC protection. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2018).

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Meng Li, Kaveh Shamsi, Travis Meade, Zheng Zhao, Bei Yu, Yier Jin, David Z Pan (2017). Provably secure camouflaging strategy for IC protection. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2017.

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Meng Li, Liangzhen Lai, Vikas Chandra, David Z. Pan (2017). Cross-level monte carlo framework for system vulnerability evaluation against fault attack. In ACM/IEEE Design Automation Conference (DAC) 2017.

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Kaveh Shamsi, Meng Li, Travis Meade, Zheng Zhao, David Z Pan, Yier Jin (2017). AppSAT: Approximately Deobfuscating Integrated Circuits. In IEEE International Symposium on Hardware Oriented Security and Trust (HOST) 2017 (Best Paper Award).

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Meng Li, Jin Miao, Kai Zhong, David Z Pan (2016). Practical public PUF enabled by solving max-flow problem on chip. In ACM/IEEE Design Automation Conference (DAC) 2016.

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Meng Li, Ye Wang, Michael Orshansky (2016). A monte carlo simulation flow for seu analysis of sequential circuits. In ACM/IEEE Design Automation Conference (DAC) 2016.

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Meng Li, Runsheng Wang, Jibin Zou, Ru Huang (2013). Characterization of Random Telegraph Noise in Scaled High-κ/Metal-Gate MOSFETs with SiO2/HfO2 Gate Dielectrics. In ECS Transactions, 52 (1) 941-946 (2013).

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