Ming Yang

Ming Yang

Bio

I am a Software Engineer at Microsoft Azure. I received a B.E. degree in Software Engineer from Tongji University in 2015, an M.S. degree and a Ph.D. degree in Computer Science from the University of North Carolina at Chapel Hill in 2018 and 2020, respectively. I was advised by Dr. James H. Anderson during my Ph.D. study.

I defended my dissertation titled "Sharing GPUs for Real-Time Autonomous-Driving Systems" in July 2020.

Email: yang@cs.unc.edu

Papers

  1. T. Amert, M. Yang, S. Nandi, T. Vu, J. Anderson, and F. D. Smith, “The Price of Schedulability in Multi-Object Tracking: The History-vs.-Accuracy Trade-Off”, Proceedings of the 23rd International Symposium on Real-Time Distributed Computing, pp. 124-133, May 2020. PDF.
  2. M. Yang, S. Wang, J. Bakita, T. Vu, F. D. Smith, J. Anderson, J.-M. Frahm, “Re-thinking CNN Frameworks for Time-Sensitive Autonomous-Driving Applications: Addressing an Industrial Challenge”, Proceedings of the 25th IEEE Real-Time and Embedded Technology and Applications Symposium, pp. 305-317, April 2019. PDF. Slides.
  3. M. Yang, T. Amert, K. Yang, N. Otterness, J. Anderson, F. D. Smith, and S. Wang, “Making OpenVX Really `Real Time'”, Proceedings of the 39th IEEE Real-Time Systems Symposium, pp. 80-93, December 2018. PDF. Slides.
  4. M. Yang, N. Otterness, T. Amert, J. Bakita, J. Anderson, and F. D. Smith, “Avoiding Pitfalls when Using NVIDIA GPUs for Real-Time Tasks in Autonomous Systems”, Proceedings of the 30th Euromicro Conference on Real-Time Systems, pp. 20:1-20:21, July 2018. PDF. Slides.
  5. T. Amert, N. Otterness, M. Yang, J. Anderson, and F. D. Smith, “GPU Scheduling on the NVIDIA TX2: Hidden Details Revealed”, Proceedings of the 38th IEEE Real-Time Systems Symposium, pp. 93-104, December 2017. PDF.
  6. M. Yang and J. Anderson, “Response-Time Bounds for Concurrent GPU Scheduling”, Proceedings of 29th Euromicro Conference on Real-Time Systems Work in Progress Session, pp. 13-15, June 2017. PDF.
  7. N. Otterness, M. Yang, T. Amert, J. Anderson, and F. D. Smith, “Inferring the Scheduling Policies of an Embedded CUDA GPU”, Proceedings of 13th Annual Workshop on Operating Systems Platforms for Embedded Real-Time Applications, pp. 47-52, June 2017. PDF.
  8. N. Otterness, M. Yang, S. Rust, E. Park, J. Anderson, F. D. Smith, A. Berg, and S. Wang, “An Evaluation of the NVIDIA TX1 for Supporting Real-Time Computer-Vision Workloads”, Proceedings of the 23rd IEEE Real-Time and Embedded Technology and Applications Symposium, 353-363, April 2017. PDF.
  9. K. Yang, M. Yang, and J. Anderson, “Reducing Response-Time Bounds for DAG-Based Task Systems on Heterogeneous Multicore Platforms”,  Proceedings of the 24th International Conference on Real-Time Networks and Systems, pp. 349-358, October 2016. PDF. Longer version with additional graphs: PDF.
  10. N. Otterness, V. Miller, M. Yang, J. Anderson, and F. D. Smith, “GPU Sharing for Image Processing in Embedded Real-Time Systems”, Proceedings of 12th Annual Workshop on Operating Systems Platforms for Embedded Real-Time Applications, pp. 23-29, July 2016. PDF. Longer version with more data: PDF.
  11. C. Nemitz, K. Yang, M. Yang, P. Ekberg, and J. Anderson, “Multiprocessor Real-Time Locking Protocols for Replicated Resources”, Proceedings of the 28th Euromicro Conference on Real-Time Systems, pp. 50-60, July 2016. PDF. Version with online appendices: PDF.

Work Experience

Research Intern at General Motors R&D, Autonomous Driving, Summer 2016/2017/2018.
Software Engineer Intern at Aurora Innovation, System Infrastructure, Summer 2019.
Software Engineer at Microsoft, Azure Core, August 2020--present.

Misc.

Slides: CUDA programming model

Reviewed: JSS'18, ECRTS'18, TII'17