Luo Mai

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 33

Top Venues

Imperial College London, UK (PHD)

Education History

Imperial College London, UK

PHD

Publications

Yao Fu, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, Luo Mai
ServerlessLLM: Low-Latency Serverless Inference for Large Language Models. OSDI (2024)
Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. CoRR (2024)
Leyang Xue, Yao Fu, Zhan Lu, Luo Mai, Mahesh K. Marina
MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving. CoRR (2024)
Yao Fu, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, Luo Mai
ServerlessLLM: Locality-Enhanced Serverless Inference for Large Language Models. CoRR (2024)
Muning Wen, Runji Lin, Hanjing Wang, Yaodong Yang, Ying Wen, Luo Mai, Jun Wang, Haifeng Zhang, Weinan Zhang
Large Sequence Models for Sequential Decision-Making: A Survey. CoRR (2023)
Muning Wen, Runji Lin, Hanjing Wang, Yaodong Yang, Ying Wen, Luo Mai, Jun Wang, Hai-Feng Zhang, Weinan Zhang
Large sequence models for sequential decision-making: a survey. Frontiers Comput. Sci. 17 (6) (2023)
Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. CoRR (2023)
Hanjing Wang, Man-Kit Sit, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. ICML (2023)
Zeyuan Tan, Xiulong Yuan, Congjie He, Man-Kit Sit, Guo Li, Xiaoze Liu, Baole Ai, Kai Zeng, Peter R. Pietzuch, Luo Mai
Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness. CoRR (2023)
Marcel Wagenländer, Guo Li, Bo Zhao, Luo Mai, Peter R. Pietzuch
TENPLEX: Changing Resources of Deep Learning Jobs using Parallelizable Tensor Collections. CoRR (2023)
Chijun Sima, Yao Fu, Man-Kit Sit, Liyi Guo, Xuri Gong, Feng Lin, Junyu Wu, Yongsheng Li, Haidong Rong, Pierre-Louis Aublin, Luo Mai
Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update. OSDI (2022)
Jie Ren, Wenteng Liang, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu
MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment. ECCV (37) (2022)
Bo Liu, Xidong Feng, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning. NeurIPS (2022)
Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang
TorchOpt: An Efficient Library for Differentiable Optimization. CoRR (2022)
Yixiao Guo, Jiawei Liu, Guo Li, Luo Mai, Hao Dong
Fast and Flexible Human Pose Estimation with HyperPose. ACM Multimedia (2021)
Yixiao Guo, Jiawei Liu, Guo Li, Luo Mai, Hao Dong
Fast and Flexible Human Pose Estimation with HyperPose. CoRR (2021)
Jie Ren, Wenteng Liang, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu
MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment. CoRR (2021)
Zihan Ding, Tianyang Yu, Hongming Zhang, Yanhua Huang, Guo Li, Quancheng Guo, Luo Mai, Hao Dong
Efficient Reinforcement Learning Development with RLzoo. ACM Multimedia (2021)
Le Xu, Shivaram Venkataraman, Indranil Gupta, Luo Mai, Rahul Potharaju
Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo. NSDI (2021)
Marcel Wagenländer, Luo Mai, Guo Li, Peter R. Pietzuch
Spotnik: Designing Distributed Machine Learning for Transient Cloud Resources. HotCloud (2020)
Le Xu, Shivaram Venkataraman, Indranil Gupta, Luo Mai, Rahul Potharaju
Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo. CoRR (2020)
Luo Mai, Guo Li, Marcel Wagenländer, Konstantinos Fertakis, Andrei-Octavian Brabete, Peter R. Pietzuch
KungFu: Making Training in Distributed Machine Learning Adaptive. OSDI (2020)
Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Luo Mai, Hao Dong
RLzoo: A Comprehensive and Adaptive Reinforcement Learning Library. CoRR (2020)
Luo Mai, Alexandros Koliousis, Guo Li, Andrei-Octavian Brabete, Peter R. Pietzuch
Taming Hyper-parameters in Deep Learning Systems. ACM SIGOPS Oper. Syst. Rev. 53 (1) (2019)
Alexandros Koliousis, Pijika Watcharapichat, Matthias Weidlich, Luo Mai, Paolo Costa, Peter R. Pietzuch
Crossbow: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers. Proc. VLDB Endow. 12 (11) (2019)
Alexandros Koliousis, Pijika Watcharapichat, Matthias Weidlich, Luo Mai, Paolo Costa, Peter R. Pietzuch
CROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers. CoRR (2019)
Luo Mai, Kai Zeng, Rahul Potharaju, Le Xu, Steve Suh, Shivaram Venkataraman, Paolo Costa, Terry Kim, Saravanam Muthukrishnan, Vamsi Kuppa, Sudheer Dhulipalla, Sriram Rao
Chi: A Scalable and Programmable Control Plane for Distributed Stream Processing Systems. Proc. VLDB Endow. 11 (10) (2018)
Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo
TensorLayer: A Versatile Library for Efficient Deep Learning Development. CoRR (2017)
Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo
TensorLayer: A Versatile Library for Efficient Deep Learning Development. ACM Multimedia (2017)
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
Extending programs with debug-related features, with application to hardware development. CoRR (2017)
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
Emu: Rapid Prototyping of Networking Services. USENIX Annual Technical Conference (2017)
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
FLICK: Developing and Running Application-Specific Network Services. USENIX Annual Technical Conference (2016)
Da Yu, Luo Mai, Somaya Arianfar, Rodrigo Fonseca, Orran Krieger, David Oran
Towards a Network Marketplace in a Cloud. HotCloud (2016)
Luo Mai, Chuntao Hong, Paolo Costa
Optimizing Network Performance in Distributed Machine Learning. HotCloud (2015)
Luo Mai, Lukas Rupprecht, Abdul Alim, Paolo Costa, Matteo Migliavacca, Peter R. Pietzuch, Alexander L. Wolf
NetAgg: Using Middleboxes for Application-specific On-path Aggregation in Data Centres. CoNEXT (2014)
Luo Mai, Lukas Rupprecht, Paolo Costa, Matteo Migliavacca, Peter R. Pietzuch, Alexander L. Wolf
Supporting application-specific in-network processing in data centres. SIGCOMM (2013)
Junzhao Du, Hui Liu, Longfei Shangguan, Luo Mai, Kai Wang, Shucong Li
Rendezvous Data Collection Using a Mobile Element in Heterogeneous Sensor Networks. Int. J. Distributed Sens. Networks 8 (2012)
Luo Mai, Longfei Shangguan, Chao Lang, Junzhao Du, Hui Liu, Zhenjiang Li, Mo Li
Load Balanced Rendezvous Data Collection in Wireless Sensor Networks. MASS (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Luo Mai