Luo Mai - RankMe

53 papers A* 13A 2B 1Misc 1Journal 28Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	BitDecoding: Unlocking Tensor Cores for Long-Context LLMs with Low-Bit KV Cache. HPCA Dayou Du, Shijie Cao, Jianyi Cheng, Luo Mai, Ting Cao, Mao Yang
2026	A	`ed.`	Proceedings of the 21st European Conference on Computer Systems, EuroSys 2026, McEwan Hall/The University of Edinburgh, Edinburgh, Scotland, UK, April 27-30, 2026 EuroSys Antonio Barbalace, Luo Mai, Roxana Geambasu, Peter R. Pietzuch
2025	J	`jnl`	HybridServe: Efficient Serving of Large AI Models with Confidence-Based Cascade Routing. CoRR Leyang Xue, Yao Fu, Luo Mai, Mahesh K. Marina
2025	—	`conf`	Manage the Workloads not the Cluster: Designing a Control Plane for Large-Scale AI Clusters. EuroMLSys Ruiqi Lai, Siyu Cao, Leqi Li, Luo Mai, Dmitrii Ustiugov
2025	J	`jnl`	MoE-Gen: High-Throughput MoE Inference on a Single GPU with Module-Based Batching. CoRR Tairan Xu, Leyang Xue, Zhan Lu, Adrian Jackson, Luo Mai
2025	J	`jnl`	RAGBoost: Efficient Retrieval-Augmented Generation with Accuracy-Preserving Context Reuse. CoRR Yinsicheng Jiang, Yeqi Huang, Liang Cheng, Cheng Deng, Xuan Sun, Luo Mai
2025	J	`jnl`	TokenScale: Timely and Accurate Autoscaling for Disaggregated LLM Serving with Token Velocity. CoRR Ruiqi Lai, Hongrui Liu, Chengzhi Lu, Zonghao Liu, Siyu Cao, Siyang Shao, Yixin Zhang, Luo Mai, Dmitrii Ustiugov
2025	J	`jnl`	WaferLLM: A Wafer-Scale LLM Inference System. CoRR Congjie He, Yeqi Huang, Pei Mu, Ziming Miao, Jilong Xue, Lingxiao Ma, Fan Yang, Luo Mai
2025	A*	`conf`	WaferLLM: Large Language Model Inference at Wafer Scale. OSDI Congjie He, Yeqi Huang, Pei Mu, Ziming Miao, Jilong Xue, Lingxiao Ma, Fan Yang, Luo Mai
2024	A*	`conf`	Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. ICML Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina
2024	J	`jnl`	Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. CoRR Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina
2024	J	`jnl`	MoE-CAP: Cost-Accuracy-Performance Benchmarking for Mixture-of-Experts Systems. CoRR Yao Fu, Yinsicheng Jiang, Yeqi Huang, Ping Nie, Zhan Lu, Leyang Xue, Congjie He, Man-Kit Sit, Jilong Xue, Li Dong, Ziming Miao, Kai Zou, Edoardo M. Ponti, Luo Mai
2024	J	`jnl`	MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving. CoRR Leyang Xue, Yao Fu, Zhan Lu, Luo Mai, Mahesh K. Marina
2024	J	`jnl`	PH-Dropout: Practical Epistemic Uncertainty Quantification for View Synthesis. CoRR Chuanhao Sun, Thanos Triantafyllou, Anthos Makris, Maja Drmac, Kai Xu, Luo Mai, Mahesh K. Marina
2024	J	`jnl`	ServerlessLLM: Locality-Enhanced Serverless Inference for Large Language Models. CoRR Yao Fu, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, Luo Mai
2024	A*	`conf`	ServerlessLLM: Low-Latency Serverless Inference for Large Language Models. OSDI Yao Fu, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, Luo Mai
2024	A*	`conf`	Tenplex: Dynamic Parallelism for Deep Learning using Parallelizable Tensor Collections. SOSP Marcel Wagenländer, Guo Li, Bo Zhao, Luo Mai, Peter R. Pietzuch
2023	A*	`conf`	GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. ICML Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai
2023	J	`jnl`	GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. CoRR Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai
2023	J	`jnl`	Large Sequence Models for Sequential Decision-Making: A Survey. CoRR Muning Wen, Runji Lin, Hanjing Wang, Yaodong Yang, Ying Wen, Luo Mai, Jun Wang, Haifeng Zhang, Weinan Zhang
2023	J	`jnl`	Large sequence models for sequential decision-making: a survey. Frontiers Comput. Sci. Muning Wen, Runji Lin, Hanjing Wang, Yaodong Yang, Ying Wen, Luo Mai, Jun Wang, Hai-Feng Zhang, Weinan Zhang
2023	J	`jnl`	Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness. CoRR Zeyuan Tan, Xiulong Yuan, Congjie He, Man-Kit Sit, Guo Li, Xiaoze Liu, Baole Ai, Kai Zeng, Peter R. Pietzuch, Luo Mai
2023	J	`jnl`	TENPLEX: Changing Resources of Deep Learning Jobs using Parallelizable Tensor Collections. CoRR Marcel Wagenländer, Guo Li, Bo Zhao, Luo Mai, Peter R. Pietzuch
2023	J	`jnl`	TorchOpt: An Efficient Library for Differentiable Optimization. J. Mach. Learn. Res. Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang
2022	A*	`conf`	A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning. NeurIPS Bo Liu, Xidong Feng, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang
2022	A*	`conf`	Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update. OSDI Chijun Sima, Yao Fu, Man-Kit Sit, Liyi Guo, Xuri Gong, Feng Lin, Junyu Wu, Yongsheng Li, Haidong Rong, Pierre-Louis Aublin, Luo Mai
2022	—	`conf`	MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment. ECCV (37) Jie Ren, Wenteng Liang, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu
2022	J	`jnl`	TorchOpt: An Efficient Library for Differentiable Optimization. CoRR Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang
2021	A*	`conf`	Efficient Reinforcement Learning Development with RLzoo. ACM Multimedia Zihan Ding, Tianyang Yu, Hongming Zhang, Yanhua Huang, Guo Li, Quancheng Guo, Luo Mai, Hao Dong
2021	A*	`conf`	Fast and Flexible Human Pose Estimation with HyperPose. ACM Multimedia Yixiao Guo, Jiawei Liu, Guo Li, Luo Mai, Hao Dong
2021	J	`jnl`	Fast and Flexible Human Pose Estimation with HyperPose. CoRR Yixiao Guo, Jiawei Liu, Guo Li, Luo Mai, Hao Dong
2021	J	`jnl`	MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment. CoRR Jie Ren, Wenteng Liang, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu
2021	Misc	`conf`	Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo. NSDI Le Xu, Shivaram Venkataraman, Indranil Gupta, Luo Mai, Rahul Potharaju
2020	A*	`conf`	KungFu: Making Training in Distributed Machine Learning Adaptive. OSDI Luo Mai, Guo Li, Marcel Wagenländer, Konstantinos Fertakis, Andrei-Octavian Brabete, Peter R. Pietzuch
2020	J	`jnl`	Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo. CoRR Le Xu, Shivaram Venkataraman, Indranil Gupta, Luo Mai, Rahul Potharaju
2020	J	`jnl`	RLzoo: A Comprehensive and Adaptive Reinforcement Learning Library. CoRR Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Luo Mai, Hao Dong
2020	—	`conf`	Spotnik: Designing Distributed Machine Learning for Transient Cloud Resources. HotCloud Marcel Wagenländer, Luo Mai, Guo Li, Peter R. Pietzuch
2019	J	`jnl`	CROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers. CoRR Alexandros Koliousis, Pijika Watcharapichat, Matthias Weidlich, Luo Mai, Paolo Costa, Peter R. Pietzuch
2019	J	`jnl`	Crossbow: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers. Proc. VLDB Endow. Alexandros Koliousis, Pijika Watcharapichat, Matthias Weidlich, Luo Mai, Paolo Costa, Peter R. Pietzuch
2019	J	`jnl`	Taming Hyper-parameters in Deep Learning Systems. ACM SIGOPS Oper. Syst. Rev. Luo Mai, Alexandros Koliousis, Guo Li, Andrei-Octavian Brabete, Peter R. Pietzuch
2018	J	`jnl`	Chi: A Scalable and Programmable Control Plane for Distributed Stream Processing Systems. Proc. VLDB Endow. Luo Mai, Kai Zeng, Rahul Potharaju, Le Xu, Steve Suh, Shivaram Venkataraman, Paolo Costa, Terry Kim, Saravanam Muthukrishnan, Vamsi Kuppa, Sudheer Dhulipalla, Sriram Rao
2017	—	`conf`	Emu: Rapid Prototyping of Networking Services. USENIX ATC Nik Sultana, Salvator Galea, David Greaves, Marcin Wójcik, Jonny Shipton, Richard G. Clegg, Luo Mai, Pietro Bressana, Robert Soulé, Richard Mortier, Paolo Costa, Peter R. Pietzuch, Jon Crowcroft, Andrew W. Moore, Noa Zilberman
2017	J	`jnl`	Extending programs with debug-related features, with application to hardware development. CoRR Nik Sultana, Salvator Galea, David Greaves, Marcin Wójcik, Noa Zilberman, Richard G. Clegg, Luo Mai, Richard Mortier, Peter R. Pietzuch, Jon Crowcroft, Andrew W. Moore
2017	A*	`conf`	TensorLayer: A Versatile Library for Efficient Deep Learning Development. ACM Multimedia Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo
2017	J	`jnl`	TensorLayer: A Versatile Library for Efficient Deep Learning Development. CoRR Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo
2017	—	`—`	Towards efficient big data processing in data centres. Luo Mai
2016	—	`conf`	FLICK: Developing and Running Application-Specific Network Services. USENIX ATC Abdul Alim, Richard G. Clegg, Luo Mai, Lukas Rupprecht, Eric Seckler, Paolo Costa, Peter R. Pietzuch, Alexander L. Wolf, Nik Sultana, Jon Crowcroft, Anil Madhavapeddy, Andrew W. Moore, Richard Mortier, Masoud Koleini, Luis Oviedo, Matteo Migliavacca, Derek McAuley
2016	—	`conf`	Towards a Network Marketplace in a Cloud. HotCloud Da Yu, Luo Mai, Somaya Arianfar, Rodrigo Fonseca, Orran Krieger, David Oran
2015	—	`conf`	Optimizing Network Performance in Distributed Machine Learning. HotCloud Luo Mai, Chuntao Hong, Paolo Costa
2014	A	`conf`	NetAgg: Using Middleboxes for Application-specific On-path Aggregation in Data Centres. CoNEXT Luo Mai, Lukas Rupprecht, Abdul Alim, Paolo Costa, Matteo Migliavacca, Peter R. Pietzuch, Alexander L. Wolf
2013	A*	`conf`	Supporting application-specific in-network processing in data centres. SIGCOMM Luo Mai, Lukas Rupprecht, Paolo Costa, Matteo Migliavacca, Peter R. Pietzuch, Alexander L. Wolf
2012	J	`jnl`	Rendezvous Data Collection Using a Mobile Element in Heterogeneous Sensor Networks. Int. J. Distributed Sens. Networks Junzhao Du, Hui Liu, Longfei Shangguan, Luo Mai, Kai Wang, Shucong Li
2011	B	`conf`	Load Balanced Rendezvous Data Collection in Wireless Sensor Networks. MASS Luo Mai, Longfei Shangguan, Chao Lang, Junzhao Du, Hui Liu, Zhenjiang Li, Mo Li