Boyang Li

bli70@hawk.iit.edu

Stuart Bldg 007B

Department of Computer Science 

Illinois Institute of Technology 

10 W 31st, Chicago, IL 60616

I will get Ph.D. degree from  the computer science department of Illinois Institute of Technology in August 2023. I am advised by Prof. Zhiling Lan and Prof. Michael E. Papka. My research interests  focus on resource management on high performance computing systems.

Education:

Chicago, IL, US                 Ph.D in Computer Science                                                          Illinois Institute of Technology

Potsdam, NY, US             M.S  in Electrical Engineering                                                   Clarkson University

Tianjin, China                    B.S in Electronic Information Engineering                        Tianjin University

Skills:

Intership:


 Argonne National Lab            Research Aid               ALCF Group               Advisor: Sudheer Chunduri      2018.6-2018.8 

 Argonne National Lab            Research Aid               ALCF Group               Advisor: Kevin Harms                  2019.5-2019.8         

 Argonne National Lab       Research Aid               ALCF Group               Advisor: Eric Pershey                 2020.5-2020.7 


Publication:

Li, Boyang, Sudheer Chunduri, Kevin Harms, Yuping Fan, and Zhiling Lan. "The effect of system utilization on application performance variability." In Proceedings of the 9th International Workshop on Runtime and Operating Systems for Supercomputers, pp. 11-18. 2019.

Li, Boyang, Yuping Fan, Matthew Dearing, Zhiling Lan, Paul Rich, William Allcock, and Michael Papka. "MRSch: Multi-Resource Scheduling for HPC." In 2022 IEEE International Conference on Cluster Computing (CLUSTER), pp. 47-57. IEEE, 2022.

Li, Boyang, Yuping Fan, Michael E. Papka, and Zhiling Lan. "Encoding for Reinforcement Learning Driven Scheduling." In Workshop on Job Scheduling Strategies for Parallel Processing, pp. 68-87. Cham: Springer Nature Switzerland, 2022.

Fan, Yuping, Boyang Li, Dustin Favorite, Naunidh Singh, Taylor Childers, Paul Rich, William Allcock, Michael E. Papka, and Zhiling Lan. "Dras: Deep reinforcement learning for cluster scheduling in high performance computing." IEEE Transactions on Parallel and Distributed Systems 33, no. 12 (2022): 4903-4917.


Project:

Small: Toward Smart HPC through Active Learning and Intelligent Scheduling

IRON: Reducing Workload Interference on Massively Parallel Platforms

MINT: Multi-resource INtelligenT management of hybrid workloads