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Dr. Tong Shu

Assistant Professor

University of North Texas

Department of Computer Science and Engineering

Email: Tong.Shu@unt.edu

Education

  • PhD, New Jersey Institute of Technology, 2017
    Major: Computer Science
    Specialization: Parallel and Distributed Computing
    Dissertation: Performance Optimization and Energy Efficiency of Big-data Computing Workflows

Professional Positions

    Academic - Post-Secondary

  • Assistant Professor, University of North Texas. University of North Texas. (2022 - Present).

Teaching

Teaching Experience

    University of North Texas

  • CSCE 4110 - Algorithms, 1 course.
  • CSCE 4610 - Computer Systems Architecture, 1 course.
  • CSCE 4890 - Directed Study, 2 courses.
  • CSCE 5218 - Deep Learning, 3 courses.
  • CSCE 5610 - Computer System Architecture, 1 course.
  • CSCE 5934 - Directed Study, 1 course.
  • CSCE 6940 - Individual Research, 4 courses.

Teaching at Other Institutions

  • Southern Illinois University Carbondale, CS 600 Doctoral Dissertation, Summer 2022.
  • Southern Illinois University Carbondale, CS 520 Advanced Topics in Parallel and Distributed Computing, Spring 2022.
  • Southern Illinois University Carbondale, CS 590 Readings, Spring 2022.
  • Southern Illinois University Carbondale, CS 485 Computer Graphics, Fall 2021.
  • Southern Illinois University Carbondale, CS 590 Readings, Fall 2021.
  • Southern Illinois University Carbondale, CS 311 Theory and Implementation of Programming, Fall 2021.
  • Southern Illinois University Carbondale, CS 590 Readings, Spring 2021.
  • Southern Illinois University Carbondale, CS 311 Theory and Implementation of Programming, Spring 2021.
  • Southern Illinois University Carbondale, CS 485 Computer Graphics, Fall 2020.

Awards and Honors

  • NSF Award, National Science Foundation. (November 9, 2022).

Research

Published Intellectual Contributions

    Conference Proceeding

  • Zhang, Y., Pandey, D., Wu, D., Kundu, T., Li, R., Shu, T. (2023). Accuracy-Constrained Efficiency Optimization and GPU Profiling of CNN Inference for Detecting Drainage Crossing Locations. 1780-1788. Denver, CO, USA, Workshops of ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SC-W). https://dl.acm.org/doi/10.1145/3624062.3624260
  • Li, Y., Baik, J., Rahman, M., Anagnostopoulos, I., Li, R., Shu, T. (2023). Pareto Optimization of CNN Models via Hardware-Aware Neural Architecture Search for Drainage Crossing Classification on Resource-Limited Devices. 1767-1775. Denver, CO, USA, Workshops of ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SC-W). https://dl.acm.org/doi/10.1145/3624062.3624258
  • Kundu, T., Shu, T. (2023). HIOS: Hierarchical Inter-Operator Scheduler for Real-Time Inference of DAG-Structured Deep Learning Models on Multiple GPUs. 95-106. Santa Fe, NM, USA, IEEE International Conference on Cluster Computing (Cluster). https://ieeexplore.ieee.org/document/10319967
  • Caldwell, J., Feng, W., Byun, M., Albert, M.V., Shu, T., Ji, Y. (2023). Exploring Power and Thermal Dynamics in the Summit Supercomputer: A Data Visualization Study. 7th Annual Smoky Mountains Computational Sciences Data Challenge (SMCDC).
  • Haleem, Y., Wagenvoord, I., Wei, Q., Xiao, T., Shu, T., Ji, Y. (2023). Understanding Nationwide Power Outage and Restoration for Future Prediction. 7th Annual Smoky Mountains Computational Sciences Data Challenge (SMCDC).
  • Shu, T., Guo, Y., Wozniak, J., Ding, X., Foster, I., Kurc, T. (2021). Bootstrapping In-Situ Workflow Auto-Tuning via Combining Performance Models of Component Applications. 28: 1-15. St. Louis, MO, USA, ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC). https://dl.acm.org/doi/10.1145/3458817.3476197

    • Journal Article

  • Foster, I., Ainsworth, M., Bessac, J., Cappello, F., Choi, J., Di, S., Di, Z., Gok, A., Guo, H., Huck, K., Kelly, C., Klasky, S., Kleese Van Dam, K., Liang, X., Mehta, K., Parashar, M., Peterka, T., Pouchard, L., Shu, T., Tugluk, O., Van Dam, H., Wan, L., Wolf, M., Wozniak, J., Xu, W., Yakushin, I., Yoo, S., Munson, T. (2021). Online Data Analysis and Reduction: An Important Co-design Motif for Extreme-scale Computers. International Journal of Higher Performance Computing Applications. 35 (6) 617-635. SAGE.
  • Shu, T., Wu, C. (2020). Energy-efficient Mapping of Large-scale Workflows under Deadline Constraints in Big Data Computing Systems. Future Generation Computer Systems. 110 515-530. Elsevier. https://www.sciencedirect.com/science/article/abs/pii/S0167739X17300468

    • Poster

  • Shu, T., Guo, Y., Wozniak, J., Ding, X., Foster, I., Kurc, T. (2021). POSTER: In-situ Workflow Auto-tuning through Combining Component Models. 467–468. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP) 2021. https://dl.acm.org/doi/10.1145/3437801.3441615

Presentations Given

    Invited Talk

  • Shu, T. (Presenter), Research Experiences for Undergraduates (REU), Workflow-Based Performance Modeling and Prediction for Interactive Deep Learning Applications, Clarkson University, Virtual zoom meeting, United States of America. (2022 - 2022).
  • Shu, T. (Presenter), Graduate Seminar in Computer Science, Improving the Performance and Robustness of Workflows at Exascale, Wayne State University, Virtual zoom meeting, United States of America. (2020).

    • Oral Presentation

  • Shu, T. (Presenter), ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), Bootstrapping In-Situ Workflow Auto-Tuning via Combining Performance Models of Component Applications, ACM/IEEE, St. Louis, MO, USA, United States of America. (2021 - 2021).
  • Shu, T. (Presenter), ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), POSTER: In-situ Workflow Auto-tuning through Combining Component Models, ACM, Virtual event, Korea, South. (2021).

    • Poster

  • Shu, T. (Presenter), 2023 NSF Cybertraining Principal Investigator Meeting, CyberTraining: Pilot: Research Workforce Development for Deep Learning Systems in Advanced GPU Cyberinfrastructure, NSF, Houston, TX, USA, United States of America. (2023 - 2023).

Contracts, Grants, Sponsored Research

    Grant - Research

  • Shu, T. (Principal), "Collaborative Research: CyberTraining: Pilot: Research Workforce Development for Deep Learning Systems in Advanced GPU Cyberinfrastructure," sponsored by National Science Foundation, Federal, $201262 Funded. (2022 - 2024).

Service

University Service

  • Committee Member, Ph.D. Admission Committee. (September 1, 2023 - August 31, 2024).
  • Other (Course Coordinator), CSCE 4610 Computer Architecture Course Coordinator. (November 21, 2022 - May 31, 2024).
  • Committee Member, Tenure-Track/Tenured Faculty Search Committee. (November 9, 2022 - May 31, 2023).
  • Committee Member, Graduate Program Committee. (August 16, 2021 - May 15, 2022).
  • Committee Member, Committee of Lab, Equipment and Computing Facilities. (August 17, 2020 - May 15, 2022).

Professional Service

  • Workshop Organizer, SC23 Workshop on Software and Hardware Co-design of Deep Learning Systems in Accelerators (SHDA). Denver, Colorado. (February 13, 2023 - November 12, 2023).
  • Committee Member, ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC) 2023. Denton, Texas. (August 13, 2023 - September 10, 2023).
  • Committee Member, IEEE International Conference on Cluster Computing (Cluster) 2023. Denton, Texas. (May 16, 2023 - July 4, 2023).
  • Committee Member, ACM International Conference on Parallel Processing (ICPP) 2023. Denton, Texas. (April 23, 2023 - June 15, 2023).
  • Reviewer, Grant Proposal, NSF CyberTraining Implementation Medium Review Panel for NSF 22-574. Denton, Texas. (April 24, 2023 - May 26, 2023).
  • Reviewer, Grant Proposal, NSF CSSI Elements Review Panel for NSF 22-632. Denton, Texas. (February 14, 2023 - March 17, 2023).
  • Reviewer, Journal Article, IEEE Transactions on Parallel and Distributed Systems. Carbondale, Illinois. (January 1, 2020 - February 19, 2023).
  • Committee Member, IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid) 2023. Denton, Texas. (December 13, 2022 - January 26, 2023).
  • Committee Member, ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC) 2022. Denton, Texas. (April 1, 2022 - November 18, 2022).
  • Committee Member, IEEE/ACM International Conference on Utility and Cloud Computing (UCC) 2022. Denton, Texas. (September 1, 2022 - October 15, 2022).
  • Reviewer, Journal Article, Wiley Networks. Carbondale, Illinois. (August 10, 2021 - May 20, 2022).
  • Reviewer, Grant Proposal, NSF OAC Core Review Panel for NSF 21-616. Carbondale, Illinois. (February 11, 2022 - March 23, 2022).
  • Reviewer, Journal Article, Wiley Concurrency and Computation: Practice and Experience. Carbondale, Illinois. (January 23, 2021 - October 22, 2021).
  • Committee Member, The 16th Workshop on Workflows in Support of Large-Scale Science (WORKS) in conjunction with ACM/IEEE Supercomputing Conference 2021. Carbondale, Illinois. (July 15, 2021 - September 24, 2021).
  • Reviewer, Book, Elsevier/Morgan Kaufmann. Carbondale, Illinois. (July 19, 2021 - August 21, 2021).
  • Reviewer, Journal Article, IEEE Transactions on Industrial Informatics. Carbondale, Illinois. (August 8, 2020 - September 7, 2020).
  • Committee Member, IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC) 2020. Carbondale, Illinois. (March 14, 2020 - September 4, 2020).
  • Committee Member, IEEE International Conference on Distributed Computing Systems (ICDCS) 2020. Lemont, Illinois. (January 15, 2020 - March 31, 2020).