Publications

Song, L., Y. Wu, X. Qian, H. Li, and Y. Chen. “ReBNN: in-situ acceleration of binarized neural networks in ReRAM using complementary resistive cell.” Ccf Transactions on High Performance Computing 1, no. 3–4 (December 1, 2019): 196–208. https://doi.org/10.1007/s42514-019-00014-8.

Li, B., M. Mao, X. Liu, T. Liu, Z. Liu, W. Wen, Y. Chen, and H. H. Li. “Thread batching for high-performance energy-efficient GPU memory design.” ACM Journal on Emerging Technologies in Computing Systems 15, no. 4 (December 1, 2019). https://doi.org/10.1145/3330152.

Yan, B., M. Liu, Y. Chen, K. Chakrabarty, and H. Li. “On Designing Efficient and Reliable Nonvolatile Memory-Based Computing-In-Memory Accelerators.” In Technical Digest International Electron Devices Meeting Iedm, Vol. 2019-December, 2019. https://doi.org/10.1109/IEDM19573.2019.8993562.

Xu, Y., Y. Li, S. Zhang, W. Wen, B. Wang, W. Dai, Y. Qi, Y. Chen, W. Lin, and H. Xiong. “Trained Rank Pruning for Efficient Deep Neural Networks.” In Proceedings 5th Workshop on Energy Efficient Machine Learning and Cognitive Computing Emc2 Nips 2019, 14–17, 2019. https://doi.org/10.1109/EMC2-NIPS53020.2019.00011.

Zhang, J., H. Yang, F. Chen, Y. Wang, and H. Li. “Exploring Bit-Slice Sparsity in Deep Neural Networks for Efficient ReRAM-Based Deployment.” In Proceedings 5th Workshop on Energy Efficient Machine Learning and Cognitive Computing Emc2 Nips 2019, 1–5, 2019. https://doi.org/10.1109/EMC2-NIPS53020.2019.00008.

Sangvai, Devdutta G., and Anthony J. Viera. Preface. Vol. 46, 2019. https://doi.org/10.1016/j.pop.2019.09.001.

Li, A., C. Wu, Y. Chen, and B. Ni. “An efficient mobile-edge collaborative system for video photorealistic style transfer.” In Proceedings of the 4th ACM IEEE Symposium on Edge Computing Sec 2019, 344–45, 2019. https://doi.org/10.1145/3318216.3363332.

Li, A., C. Wu, Y. Chen, and B. Ni. “Poster abstract: An efficient edge-assisted mobile system for video photorealistic style transfer.” In Proceedings of the 4th ACM IEEE Symposium on Edge Computing Sec 2019, 332–33, 2019. https://doi.org/10.1145/3318216.3364545.

Chen, F., W. Wen, L. Song, J. Zhang, H. H. Li, and Y. Chen. “How to obtain and run light and efficient deep learning networks.” In IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad, Vol. 2019-November, 2019. https://doi.org/10.1109/ICCAD45719.2019.8942106.

Yang, Q., J. Mao, Z. Wang, and H. Li. “DASNet: Dynamic activation sparsity for neural network efficiency improvement.” In Proceedings International Conference on Tools with Artificial Intelligence Ictai, 2019-November:1401–5, 2019. https://doi.org/10.1109/ICTAI.2019.00197.

Chaudhuri, A., B. Yan, Y. Chen, and K. Chakrabarty. “Hardware fault tolerance for binary RRAM crossbars.” In Proceedings International Test Conference, Vol. 2019-November, 2019. https://doi.org/10.1109/ITC44170.2019.9000179.

Yan, Bonan, Bing Li, Ximing Qiao, Cheng-Xin Xue, Meng‐Fan Chang, Yiran Chen, and Hai Helen Li. “Resistive Memory‐Based In‐Memory Computing: From Device and Large‐Scale Integration System Perspectives.” Advanced Intelligent Systems 1, no. 7 (November 2019). https://doi.org/10.1002/aisy.201900068.

Gan, Z. H., X. L. Chai, D. J. Han, and Y. R. Chen. “A chaotic image encryption algorithm based on 3-D bit-plane permutation.” Neural Computing and Applications 31, no. 11 (November 1, 2019): 7111–30. https://doi.org/10.1007/s00521-018-3541-y.

Bogdan, P., F. Chen, A. Deshwal, J. R. Doppa, B. K. Joardar, H. Li, S. Nazarian, L. Song, and Y. Xiao. “Taming extreme heterogeneity via machine learning based design of autonomous manycore systems.” In Proceedings of the International Conference on Hardware Software Codesign and System Synthesis Companion Codes Isss 2019, 2019. https://doi.org/10.1145/3349567.3357376.

Wu, C., A. Li, B. Li, and Y. Chen. “Efficiently Learning a Robust Self-Driving Model with Neuron Coverage Aware Adaptive Filter Reuse.” In IEEE Workshop on Signal Processing Systems Sips Design and Implementation, 2019-October:109–14, 2019. https://doi.org/10.1109/SiPS47522.2019.9020572.

Cheng, H. P., T. Zhang, Y. Yang, F. Yan, H. Teague, Y. Chen, and H. Li. “MSNet: Structural wired neural architecture search for internet of things.” In Proceedings 2019 International Conference on Computer Vision Workshop Iccvw 2019, 2033–36, 2019. https://doi.org/10.1109/ICCVW.2019.00254.

Wen, W., Y. Chen, and S. P. Mohanty. “Message from the General Chairs.” In Proceedings of IEEE Computer Society Annual Symposium on VLSI Isvlsi, 2019-July:xx, 2019. https://doi.org/10.1109/ISVLSI.2019.00005.

Xu, J., D. Feng, Y. Hua, W. Tong, J. Liu, C. Li, G. Xu, and Y. Chen. “Adaptive granularity encoding for energy-efficient non-volatile main memory.” In Proceedings Design Automation Conference, 2019. https://doi.org/10.1145/3316781.3317760.

Chen, F., L. Song, H. H. Li, and Y. Chen. “ZARA: A novel zero-free dataflow accelerator for generative adversarial networks in 3D ReRAM.” In Proceedings Design Automation Conference, 2019. https://doi.org/10.1145/3316781.3317936.

Liu, R., J. Yang, Y. Chen, and W. Zhao. “ESLAM: An energy-efficient accelerator for real-time ORB-SLAM on FPGA platform.” In Proceedings Design Automation Conference, 2019. https://doi.org/10.1145/3316781.3317820.

Barboza, E. C., N. Shukla, Y. Chen, and J. Hu. “Machine learning-based pre-routing timing prediction with reduced pessimism.” In Proceedings Design Automation Conference, 2019. https://doi.org/10.1145/3316781.3317857.

Mao, J., Q. Yang, A. Li, H. Li, and Y. Chen. “MobiEye: An efficient cloud-based video detection system for real-time mobile applications.” In Proceedings - Design Automation Conference, 2019. https://doi.org/10.1145/3316781.3317865.

Yan, B., Q. Yang, W. H. Chen, K. T. Chang, J. W. Su, C. H. Hsu, S. H. Li, et al. “RRAM-based Spiking Nonvolatile Computing-In-Memory Processing Engine with Precision-Configurable in Situ Nonlinear Activation.” In Digest of Technical Papers Symposium on VLSI Technology, 2019-June:T86–87, 2019. https://doi.org/10.23919/VLSIT.2019.8776485.

Inkawhich, N., W. Wen, H. H. Li, and Y. Chen. “Feature space perturbations yield more transferable adversarial examples.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2019-June:7059–67, 2019. https://doi.org/10.1109/CVPR.2019.00723.

Alyamkin, S., M. Ardi, A. C. Berg, A. Brighton, B. Chen, Y. Chen, H. P. Cheng, et al. “Low-Power Computer Vision: Status, Challenges, and Opportunities.” IEEE Journal on Emerging and Selected Topics in Circuits and Systems 9, no. 2 (June 1, 2019): 411–21. https://doi.org/10.1109/JETCAS.2019.2911899.