- KungFu: Adaptive and High-performance Deep Learning at Scale.
Duration: 2018 - current
Description: We are developing a novel deep learning system that aims to achieve highest possible training and inference performance using GPUs/CPUs.
- Flare: High-performance and Self-tuning Stream Prcessing in Real-world Data Ingestion
Duration: 2015 - current
Description: Flare is a high-performance and self-tuning stream processing system that can handle large-scale data ingestion. Flare has been deployed within Microsoft production clusters.
[Related publications: Chi VLDB'18]
- NaaS: Network-as-a-Service in the Cloud
Duration: 2012 - 2016
Description: NaaS integrates current cloud computing offerings with secure access to the networking infrastructure, thus enabling the uses of application-specific network services to improve communication performance.
[Related publications: Emu ATC'17, FLICK ATC'16, NetEx HotCloud'16, MLNet HotCloud'15, NetAgg CoNEXT'14]
Chi: A Scalable and Programmable Control Plane for Distributed Stream Processing Systems
Luo Mai, Kai Zeng, Rahul Potharaju, Le Xu, Shivaram Venkataraman, Paolo Costa, Terry Kim, Saravanan Muthukrishnan, Vamsi Kuppa, Sudheer Dhulipalla, Sriram Rao
Proceedings of Very Large Data Base (PVLDB) 2018
TensorLayer: A Versatile Library for Efficient Deep Learning Development
Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo
ACM Multimedia 2017
[Best Open Source Software Award] [Github]
Emu: Rapid Prototyping of Networking Services
Nik Sultana, Salvator Galea, David Greaves, Marcin Wojcik, and Jonny Shipton, Richard Clegg, Luo Mai, Pietro Bressana and Robert Soule, Richard Mortier, Paolo Costa, Peter Pietzuch, Jon Crowcroft, Andrew W Moore, Noa Zilberman
The 2017 USENIX Annual Technical Conference (USENIX ATC '17)
Towards a Network Marketplace in a Cloud
Da Yu, Luo Mai, Somaya Arianfar, Rodrigo Fonseca, Orran Krieger, David Oran
The 8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud'16)
FLICK: Developing and Running Application-Specific Network Services
Abdul Alim, Richard G. Clegg, Luo Mai, Lukas Rupprecht, Eric Seckler, Paolo Costa, Peter Pietzuch, Alexander L. Wolf, Nik Sultana, Jon Crowcroft, Anil Madhavapeddy, Andrew Moore, Richard Mortier, Luis Oviedo, Masoud Koleni, Derek McAuley, Matteo Migliavacca
The 2016 USENIX Annual Technical Conference (USENIX ATC '16)
Optimizing Network Performance in Distributed Machine Learning
Luo Mai, Chuntao Hong, Paolo Costa
The 7th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud'15)
NetAgg: Using Middleboxes for Application-specific On-path Aggregation in Data Centres
Luo Mai, Lukas Rupprecht, Abdul Alim, Paolo Costa, Matteo Migliavacca, Peter Pietzuch, Alexander L. Wolf.
The 10th ACM International Conference on emerging Networking EXperiments and Technologies (CoNEXT'14)
[Best paper award nominee]
- Exploiting Time-Malleability in Cloud-based Batch Processing Systems
Luo Mai, Evangelia Kalyvianaki, Paolo Costa
The 7th ACM SIGOPS Workshop on Large-Scale Distributed Systems and Middleware (LADIS'13) co-located with SOSP'13
[Media coverage: The Register]
- Supporting Application-Specific In-Network Processing in Data Centres (Poster Track)
Luo Mai, Lukas Rupprecht, Paolo Costa, Matteo Migliavacca, Peter Pietzuch, Alexander L. Wolf
The 2013 ACM SIGCOMM Conference
Load Balanced Rendezvous Data Collection in Wireless Sensor Networks
Luo Mai, Longfei Shangguan, Chao Lang, Junzhao Du, Zhenjiang Li, and Mo Li.
The 8th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS'11)
[Best student paper award nominee]