- FungFu: Towards Adaptive Deep Learning.
Duration: 2018 - current
Abstract: more details are coming later.
- TensorLayer: A Versatile Deep Learning Library for Developers and Scientists.
Duration: 2016 - current
Abstract: TensorLayer is a popular open-source deep learning library based on Google TensorFlow. It provides flexible yet high-performance modules that can help the entire deep learning development workflow. It has attracted 100,000 downloads and 4000 stars on Github, and is awarded the 2017 best open-source software by ACM Multimedia Community.
[Code repository: GitHub]
- Flare: Adaptive Stream Processing in Large-scale Data Ingestion
Duration: 2015 - current
Abstract: Questioning, debugging and reasoning a big cluster through massive logs is critical for spawning data-driven decisions. We are exploring how to build a scalable analytics system for collecting, computing and delivering event summaries to numerous data stakeholders at an interactive speed. Flare is a research project during incubation. It is supported by Microsoft Research, Bing Ads and Azure.
[More details: Chi VLDB'18]
- NaaS: Network-as-a-Service in the Cloud
Duration: 2012 - 2016
Abstract: NaaS integrates current cloud computing offerings with direct yet secure access to the network infrastructure by tenants. With NaaS, tenants can easily develop and execute application-specific network services, such as custom routing, in-network data aggregation, redundancy elimination and smart caching, in order to improve communication performance. NaaS is a completed research project. It was supported by Google and UK EPSRC.
[More details: Emu ATC'17, FLICK ATC'16, NetEx HotCloud'16, MLNet HotCloud'15, NetAgg CoNEXT'14]
Towards Efficient Big Data Processing in Data Centres
PhD Thesis, Imperial College London
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]
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]