Song Huang

Ph.D. Student

Dependable Computing System Lab

Department of Computer Science and Engineering

University of North Texas, Denton, TX 76203


[Education] [Research] [Skills] [Working Experience] [University Employment] [Publications] [Song's Resume]
  • Ph.D. Student: Computer Science and Engineering

              University of North Texas, TX 76203, U.S. (2013 - Now)

  • M.S.: Computer Science and Information System

             Texas A&M University – Commerce, TX75429, U.S. (2011- 2013)

  • B.S.: Network Engineering

             Guangdong University of Technology, Guangdong, China (2002 - 2006)


I am working in the Dependable Computing System Lab, under direction of Dr. Song Fu.

My research interests include power management on HPC system, disk failure analysis and prediction, fault tolerance strategies on HPC Systems, performance characterizing and modeling, statistical learning and data mining, information retrieval, Programmer Optimized Source Code programming method and Algorithm Analaysis.

 Technical Skills
  • Programming Languages: Proficient: C/C++, Python, Java; Familiar: R Programming, Scala
  • Cloud and HPC Computing: OpenStack, AWS, MiniNet, MPI, OpenMP, CUDA programming.
  • Data Science: Spark with Python and Scala, , Scikit Learn, TensorFlow, Hadoop Ecosystem.
  • Others: MySQL, PostgreSQL, MongoDB, Cassandra, Design Pattern, CMM 3
 Working Experience
  • Cisco Systems, Inc(June, 2016 --- August, 2016)

          Research Intern

  • Los Alamos National Laboratory(June, 2015 --- November, 2015)

          Research Student

  • Guangdong Century Jiahua Trading co., ltd(July, 2008 --- December, 2010)

          IT Team Lead

  • Two(Guangzhou) IT Co., Ltd(July, 2006 --- July, 2008)

          Software Developer

 University Employment
  • Research Assistant:
    • Disk failure analysis and prediction.
    • OpenStack network failure analysis.
    • Power efficiency on large scale computer systems.
  • Teaching Assistant: Computer Science and Engineering (Lab Assistant for CSCE1020, CSCE1030)
  • Teaching Assistant: Computer Science and Information System, Texas A&M University-Commerce (Lab Assistant for CSCE1020, CSCE1030)
  1. Song Huang, "Ph.D.Forum: Research on Power Saving and Energy Efficiency for Data-Centric Computing on Production HPC Systems", in Proceedings of The Eighth International Green and Sustainable Computing Conference (IGSC), October, 2017
  2. Song Huang, S. Fu, W. Shi and D. Tiwari, "Poster: Proactive Disk Failure Management and Data Protection for Highly Available Storage Systems", ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC), July 2017
  3. Song Huang, zhiang deng, song fu, "quantifying entity criticality for fault impact analysis and dependability enhancement in software-defined networks ", 35th ieee international performance computing and Communications Conference(IPCCC). Las Vegas, December 2016.
  4. Song Huang,Song Fu, Scott Pakin and Michael Lang, "Characterizing Power and Energy Efficiency of Legion Runtime and Applications: An Early Experience", IEEE International Green and Sustainable Computing Conference (IGSC), November 2016.
  5. Song Huang, Song Fu, Quan Zhang, Weisong Shi, “Characterizing Disk Failures with Quantified Disk Degradation Signatures: An Early Experience”, in Proc. of IEEE International Symposium on Workload Characterization (IISWC), 10 pages, October 2015.
  6. Song Huang, Song Fu, Nathan DeBardeleben, Qiang Guan, and Chengzhong Xu, “Differentiated Failure Remediation with Action Selection for Resilient Computing”, in Proc. of the 21st IEEE/IFIP International Symposium on Dependable Computing (PRDC), 10 pages, November 2015
  7. Song Huang, Michael Lang, Scott Pakin, and Song Fu, “Measurement and Characterization of Haswell Power and Energy Consumption”, in Proceedings of the 3rd International Workshop on Energy Efficient Supercomputing (E2SC '15), in conjunction of IEEE/ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 10 pages, November, 2015.
  8. Xiajun Wang, Song Huang, Song Fu and Krishna Kavi, “Characterizing Workload of Web Applications on Virtualized Servers”, Big Data Benchmarks, Performance Optimization, and Emerging Hardware, pp 98-108, Springer, November 2014.
 Useful Links

UNT Microsoft Software Download