Qian Li

Research Assistant

Computer Science Department · Stanford University

DBOS: A Database-oriented Operating System

I am currently working on DBOS, where we propose a radically new cluster-OS design based on data-centric architecture: all operating system state should be represented uniformly as database tables, and operations on this state should be made via queries from otherwise stateless tasks. This design makes it easy to scale and evolve the OS without whole-system refactoring. We are currently working on building a complete end-to-end prototype of DBOS.
[project website]

INFaaS: A Model-less and Managed Inference Serving System

I have built INFaaS: an INFerence-as-a-Service platform that makes ML inference accessible and easy-to-use by abstracting resource management and model selection. By leveraging heterogeneous compute resources and efficient sharing, INFaaS achieves high throughput and low SLO violations while minimizing cost.
[project website]

Thanks to the First-Year Rotation Program, I was honored to have worked with two amazing groups during 2017-2018.

Winter Rotation (Advisor: Prof. John Ousterhout )
Arachne: Towards Core-Aware Scheduling. We are building a low-latency user-level thread library.
[code]
Memcached-A: We used Arachne to restructure Memcached that reduces performance interference and provides finer-grain load-balancing; achieved lower tail latency and higher SLO-compliant throughput.
[code] [benchmark code]

Autumn Rotation (Advisor: Prof. Christos Kozyrakis )
Thousand Island Scanner: Scaling Video Analysis on AWS Lambda. Presented a scalable video analysis framework that uses AWS Lambda to efficiently meet computational needs while minimizing unused resources by quickly scaling up and down.
[code]