Major Research Problems
SAIL is devoted to creative computer system design and problem solving. Our mission is to build powerful micro data centers that support emerging intelligent digital services for the next 10 years and beyond.
Some of our on-going data center system research projects are described as follows:
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Multimodal Intelligent Computing The advancement of AI and IoT technologies has boosted the development of multimodal computing, which refers to the complex computing process of federating multiple modalitie (e.g., image, audio, text, etc). It is important to build efficient systems for handling this type of new workload. Representative Papers: ISCA, RTSS, Euro-Par |
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Graph Computing and Sampling As a ubiquitous data structure, graph holds the information of entities and the relationship between them. Graph computing and sampling are important procedures for understanding graphs. It is critical for parallel and distributed computing systems to better support graph big data. Representative Papers: TC, TACO, TPDS, PACT |
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Cloud-Native System Platform Emerging cloud-native development model allows users to focus on the task logic while abstracting away the low-level complexity from users. It is important for future data centers to fully unleash the scalability, elasticity, and flexibility of cloud-native infrastructures. Representative Papers: TC, SoCC, IPDPS, ICPP |
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Server Memory Management The ever-growing memory demand of applications pose important challenges to today's data centers. The continuous advancement of new storage and memory devices motivates the development and optimization of more efficient server memory management strategies. Representative Papers: TC, HPCA, IPDPS, ICCD |
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Server Power Management Green consciousness is quickly making its way into computer design. We have strong incentives to limit system power to improve sustainability and cost-effectiveness. Datacenters need appropriate power management strategies to reduce energy consumption while ensuring quality of service. Representative Papers: ISCA, SC, ICPP, ICCD |
Acknowledgement
The members of SAIL would like to thank our research sponsors and collaborators:
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