Liu Ke - RankMe

23 papers A* 5A 4Journal 12Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerating Confidential Recommendation Model Inference With Near-Memory Processing. IEEE Trans. Dependable Secur. Comput. Wenjie Xiong, Liu Ke, Maxim Ostapenko, Yongmin Tai, Yeongon Cho, Joon-Ho Song, Jinin So, Kyungsoo Kim, Yongsuk Kwon, Jin Jung, Jieun Lee, Byeongho Kim, Shinhaeng Kang, Sukhan Lee, Jeonghyeon Cho, Kyomin Sohn, Xuan Zhang, Hsien-Hsin S. Lee, G. Edward Suh
2024	A*	`conf`	Toward Efficient Inference for Mixture of Experts. NeurIPS Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Shruti Bhosale, Hsien-Hsin S. Lee, Carole-Jean Wu, Benjamin Lee
2023	J	`jnl`	Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference. CoRR Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Hsien-Hsin S. Lee, Anjali Sridhar, Shruti Bhosale, Carole-Jean Wu, Benjamin Lee
2022	J	`jnl`	Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems. CoRR Hanieh Hashemi, Wenjie Xiong, Liu Ke, Kiwan Maeng, Murali Annavaram, G. Edward Suh, Hsien-Hsin S. Lee
2022	J	`jnl`	DisaggRec: Architecting Disaggregated Systems for Large-Scale Personalized Recommendation. CoRR Liu Ke, Xuan Zhang, Benjamin Lee, G. Edward Suh, Hsien-Hsin S. Lee
2022	A*	`conf`	Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation. HPCA Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin S. Lee, Xuan Zhang
2022	J	`jnl`	Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation. CoRR Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin S. Lee, Xuan Zhang
2022	A*	`conf`	MeNDA: a near-memory multi-way merge solution for sparse transposition and dataflows. ISCA Siying Feng, Xin He, Kuan-Yu Chen, Liu Ke, Xuan Zhang, David T. Blaauw, Trevor N. Mudge, Ronald G. Dreslinski
2022	J	`jnl`	Near-Memory Processing in Action: Accelerating Personalized Recommendation With AxDIMM. IEEE Micro Liu Ke, Xuan Zhang, Jinin So, Jong-Geon Lee, Shinhaeng Kang, Sukhan Lee, Songyi Han, Yeongon Cho, Jin Hyun Kim, Yongsuk Kwon, Kyungsoo Kim, Jin Jung, IlKwon Yun, Sung Joo Park, Hyunsun Park, Joon-Ho Song, Jeonghyeon Cho, Kyomin Sohn, Nam Sung Kim, Hsien-Hsin S. Lee
2022	A*	`conf`	SecNDP: Secure Near-Data Processing with Untrusted Memory. HPCA Wenjie Xiong, Liu Ke, Dimitrije Jankov, Michael Kounavis, Xiaochen Wang, Eric Northup, Jie Amy Yang, Bilge Acun, Carole-Jean Wu, Ping Tak Peter Tang, G. Edward Suh, Xuan Zhang, Hsien-Hsin S. Lee
2021	J	`jnl`	Evaluating Neural Network-Inspired Analog-to-Digital Conversion With Low-Precision RRAM. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Weidong Cao, Liu Ke, Ayan Chakrabarti, Xuan Zhang
2021	J	`jnl`	SecNDP: Secure Near-Data Processing with Untrusted Memory. IACR Cryptol. ePrint Arch. Wenjie Xiong, Liu Ke, Dimitrije Jankov, Michael Kounavis, Xiaochen Wang, Eric Northup, Jie Amy Yang, Bilge Acun, Carole-Jean Wu, Ping Tak Peter Tang, G. Edward Suh, Xuan Zhang, Hsien-Hsin S. Lee
2020	J	`jnl`	A Quantitative Exploration of Collaborative Pruning and Approximation Computing Towards Energy Efficient Neural Networks. IEEE Des. Test Xin He, Guihai Yan, Wenyan Lu, Xuan Zhang, Liu Ke
2020	A*	`conf`	RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing. ISCA Liu Ke, Udit Gupta, Benjamin Youngjae Cho, David Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Meng Li, Bert Maher, Dheevatsa Mudigere, Maxim Naumov, Martin Schatz, Mikhail Smelyanskiy, Xiaodong Wang, Brandon Reagen, Carole-Jean Wu, Mark Hempstead, Xuan Zhang
2019	A	`conf`	Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices. ICCAD Weidong Cao, Liu Ke, Ayan Chakrabarti, Xuan Zhang
2019	J	`jnl`	Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices. CoRR Weidong Cao, Liu Ke, Ayan Chakrabarti, Xuan Zhang
2019	J	`jnl`	RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing. CoRR Liu Ke, Udit Gupta, Carole-Jean Wu, Benjamin Youngjae Cho, Mark Hempstead, Brandon Reagen, Xuan Zhang, David M. Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Meng Li, Bert Maher, Dheevatsa Mudigere, Maxim Naumov, Martin Schatz, Mikhail Smelyanskiy, Xiaodong Wang
2019	A	`conf`	SparseBNN: Joint Algorithm/Hardware Optimization to Exploit Structured Sparsity in Binary Neural Network. FPGA Xin He, Liu Ke, Xuan Zhang
2018	A	`conf`	AxTrain: Hardware-Oriented Neural Network Training for Approximate Inference. ISLPED Xin He, Liu Ke, Wenyan Lu, Guihai Yan, Xuan Zhang
2018	J	`jnl`	AxTrain: Hardware-Oriented Neural Network Training for Approximate Inference. CoRR Xin He, Liu Ke, Wenyan Lu, Guihai Yan, Xuan Zhang
2018	A	`conf`	NNest: Early-Stage Design Space Exploration Tool for Neural Network Inference Accelerators. ISLPED Liu Ke, Xin He, Xuan Zhang
2016	—	`conf`	Fast-Gaussian SIFT and its hardware architecture for keypoint detection. APCCAS Liu Ke, Jun Wang, Xijun Zhao, Fan Liang
2016	—	`conf`	Fast-Gaussian SIFT for Fast and Accurate Feature Extraction. PCM (2) Liu Ke, Jun Wang, Zhixian Ye