Publications

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.

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.

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.

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.

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.

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, 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.

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.

Lin, X., J. Pan, J. Xu, Y. Chen, and C. Zhuo. “Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 2022-January:166–71, 2022. https://doi.org/10.1109/ASP-DAC52403.2022.9712491.

Tang, M., X. Ning, Y. Wang, J. Sun, H. Li, and Y. Chen. “FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2022-June:10092–101, 2022. https://doi.org/10.1109/CVPR52688.2022.00986.

Zhang, Youhui, Yiran Chen, and Yuanyuan Mi. “Editorial: Machine learning for computational neural modeling and data analyses.” Frontiers in Computational Neuroscience 16 (January 2022): 978192. https://doi.org/10.3389/fncom.2022.978192.

Li, B., H. Lv, Y. Wang, and Y. Chen. “Security Threat to the Robustness of RRAM-based Neuromorphic Computing System.” In Proceedings 2022 IEEE International Symposium on Smart Electronic Systems Ises 2022, 267–71, 2022. https://doi.org/10.1109/iSES54909.2022.00061.

Inkawhich, N., J. Zhang, E. K. Davis, R. Luley, and Y. Chen. “Improving Out-of-Distribution Detection by Learning from the Deployment Environment.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 (January 1, 2022): 2070–86. https://doi.org/10.1109/JSTARS.2022.3146362.

Feng, G., B. Kim, and H. H. Li. “Bionic Robust Memristor-Based Artificial Nociception System for Robotics.” In Proceedings IEEE International Symposium on Circuits and Systems, 2022-May:3552–56, 2022. https://doi.org/10.1109/ISCAS48785.2022.9937461.

Wang, B., A. Li, M. Pang, H. Li, and Y. Chen. “GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs.” In Proceedings IEEE International Conference on Data Mining Icdm, 2022-November:498–507, 2022. https://doi.org/10.1109/ICDM54844.2022.00060.

Yan, B., J. L. Hsu, P. C. Yu, C. C. Lee, Y. Zhang, W. Yue, G. Mei, et al. “A 1.041-Mb/mm227.38-TOPS/W Signed-INT8 Dynamic-Logic-Based ADC-less SRAM Compute-in-Memory Macro in 28nm with Reconfigurable Bitwise Operation for AI and Embedded Applications.” In Digest of Technical Papers IEEE International Solid State Circuits Conference, 2022-February:188–90, 2022. https://doi.org/10.1109/ISSCC42614.2022.9731545.

Zhang, G. L., S. Zhang, H. H. Li, and U. Schlichtmann. “RRAM-based Neuromorphic Computing: Data Representation, Architecture, Logic, and Programming.” In Proceedings 2022 25th Euromicro Conference on Digital System Design Dsd 2022, 423–28, 2022. https://doi.org/10.1109/DSD57027.2022.00063.