Publications

Chen, Y., and Q. Qiu. “Guest Editorial: IEEE TC Special Issue on Software, Hardware and Applications for Neuromorphic Computing.” IEEE Transactions on Computers 71, no. 11 (November 1, 2022): 2705–6. https://doi.org/10.1109/TC.2022.3208389.

Ogbogu, C., A. I. Arka, B. K. Joardar, J. R. Doppa, H. Li, K. Chakrabarty, and P. P. Pande. “Accelerating Large-Scale Graph Neural Network Training on Crossbar Diet.” IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 11 (November 1, 2022): 3626–37. https://doi.org/10.1109/TCAD.2022.3197342.

Henkel, J., H. Li, A. Raghunathan, M. B. Tahoori, S. Venkataramani, X. Yang, and G. Zervakis. “Approximate computing and the efficient machine learning expedition.” In IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad, 2022. https://doi.org/10.1145/3508352.3561105.

Pan, J., C. C. Chang, Z. Xie, J. Hu, and Y. Chen. “Robustify ML-based lithography hotspot detectors.” In IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad, 2022. https://doi.org/10.1145/3508352.3549389.

Xie, Z., S. Li, M. Ma, C. C. Chang, J. Pan, Y. Chen, and J. Hu. “DEEP: Developing extremely efficient runtime on-chip power meters.” In IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad, 2022. https://doi.org/10.1145/3508352.3549427.

Sengupta, P., A. Tyagi, Y. Chen, and J. Hu. “How good is your verilog RTL code? A quick answer from machine learning.” In IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad, 2022. https://doi.org/10.1145/3508352.3549375.

Wang, C., D. Feng, W. Tong, J. Liu, B. Wu, and Y. Chen. “Space-Time-Efficient Modeling of Large-Scale 3-D Cross-Point Memory Arrays by Operation Adaption and Network Compaction.” IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 10 (October 1, 2022): 3479–91. https://doi.org/10.1109/TCAD.2021.3123591.

Chandra, V., Y. Chen, and S. Yoo. “Introduction to the Special Section on Energy-Efficient AI Chips.” ACM Transactions on Design Automation of Electronic Systems 27, no. 5 (September 21, 2022). https://doi.org/10.1145/3538502.

Zhang, J., J. Tang, Y. Chen, J. Liu, J. Ye, M. Wolf, V. Narayanan, M. Srivastava, M. I. Jordan, and V. Bahl. “The 5th Artificial Intelligence of Things (AIoT) Workshop.” In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 4912–13, 2022. https://doi.org/10.1145/3534678.3542911.

Li, Z., Q. Zheng, B. Yan, R. Huang, B. Li, and Y. Chen. “ASTERS: Adaptable Threshold Spike-timing Neuromorphic Design with Twin-Column ReRAM Synapses.” In Proceedings Design Automation Conference, 1099–1104, 2022. https://doi.org/10.1145/3489517.3530591.

Yang, H., X. Yang, N. Z. Gong, and Y. Chen. “HERO: Hessian-Enhanced Robust Optimization for Unifying and Improving Generalization and Quantization Performance.” In Proceedings Design Automation Conference, 25–30, 2022. https://doi.org/10.1145/3489517.3530678.

Pan, J., C. C. Chang, Z. Xie, A. Li, M. Tang, T. Zhang, J. Hu, and Y. Chen. “Towards Collaborative Intelligence: Routability Estimation based on Decentralized Private Data.” In Proceedings Design Automation Conference, 961–66, 2022. https://doi.org/10.1145/3489517.3530578.

Hanson, E., S. Li, H. H. Li, and Y. Chen. “Cascading Structured Pruning: Enabling High Data Reuse for Sparse DNN Accelerators.” In Proceedings International Symposium on Computer Architecture, 522–35, 2022. https://doi.org/10.1145/3470496.3527419.

Li, T., N. Jing, Z. Mao, and Y. Chen. “A Hybrid-Grained Remapping Defense Scheme Against Hard Failures for Row-Column-NVM.” IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 6 (June 1, 2022): 1842–54. https://doi.org/10.1109/TCAD.2021.3097288.

Taylor, B., Q. Zheng, Z. Li, S. Li, and Y. Chen. “Processing-in-Memory Technology for Machine Learning: From Basic to ASIC.” IEEE Transactions on Circuits and Systems II Express Briefs 69, no. 6 (June 1, 2022): 2598–2603. https://doi.org/10.1109/TCSII.2022.3168404.

Yang, X., B. Taylor, A. Wu, Y. Chen, and L. O. Chua. “Research Progress on Memristor: From Synapses to Computing Systems.” IEEE Transactions on Circuits and Systems I Regular Papers 69, no. 5 (May 1, 2022): 1845–57. https://doi.org/10.1109/TCSI.2022.3159153.

Mao, J., Q. Yang, A. Li, K. W. Nixon, H. Li, and Y. Chen. “Toward Efficient and Adaptive Design of Video Detection System with Deep Neural Networks.” ACM Transactions on Embedded Computing Systems 21, no. 3 (May 1, 2022). https://doi.org/10.1145/3484946.

Chen, Y., and Y. Wang. “A survey of architectures of neural network accelerators.” Scientia Sinica Informationis 52, no. 4 (April 1, 2022): 596–611. https://doi.org/10.1360/SSI-2021-0409.

Li, H. H., A. R. Alameldeen, and O. Mutlu. “Guest Editors' Introduction: Near-Memory and In-Memory Processing.” IEEE Design and Test 39, no. 2 (April 1, 2022): 46–47. https://doi.org/10.1109/MDAT.2021.3124742.

Chen, Yiran, and Hai Helen Li. “SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms.” Office of Scientific and Technical Information (OSTI), February 26, 2022. https://doi.org/10.2172/1846568.

Chen, Y., and S. Reda. “ISLPED 2021: The 25th Anniversary!.” In IEEE Design and Test, 39:92–93, 2022. https://doi.org/10.1109/MDAT.2021.3128437.

Yang, X., H. Yang, J. Zhang, H. H. Li, and Y. Chen. “On Building Efficient and Robust Neural Network Designs.” In Conference Record Asilomar Conference on Signals Systems and Computers, 2022-October:317–21, 2022. https://doi.org/10.1109/IEEECONF56349.2022.10051891.

Zhang, J., Y. Chen, and H. Li. “Privacy Leakage of Adversarial Training Models in Federated Learning Systems.” In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2022-June:107–13, 2022. https://doi.org/10.1109/CVPRW56347.2022.00021.

Cheng, H. P., F. Liang, M. Li, B. Cheng, F. Yan, H. Li, V. Chandra, and Y. Chen. “ScaleNAS: Multi-Path One-Shot NAS for Scale-Aware High-Resolution Representation.” In Proceedings of Machine Learning Research, Vol. 188, 2022.

Gao, Z., M. Tang, A. Li, and Y. Chen. “An Audio Frequency Unfolding Framework for Ultra-Low Sampling Rate Sensors.” In Proceedings International Symposium on Quality Electronic Design Isqed, Vol. 2022-April, 2022. https://doi.org/10.1109/ISQED54688.2022.9806149.