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Michigan State University
Michigan State University

ICER Institute for Cyber-Enabled Research
The Institute for Cyber-Enabled Research (ICER) > Research Services > Academic Research Consulting Services (ARCS) >

Xiaoge Wang

Portrait of Xiaoge WangDr. Xiaoge Wang

Research Consultant, MSU Institute for Cyber-Enabled Research
Biomedical & Physical Sciences Building
wangx147@msu.edu

Link to CV


Bio: Dr. Xiaoge Wang is a Research Consultant in the Institute for Cyber-Enabled Research. Dr. Wang has over 20 years of experience in scientific computing, especially in the development of parallel algorithms for various science and engineering applications. She draws on her knowledge of machine learning applications, numerical linear algebra, and statistical modeling to assist HPCC users with their computing needs. Prior to joining ICER in 2015, Dr. Wang received her Ph.D. in computer science from the University of Illinois at Champaign-Urbana in 1994. At present, in addition to supporting MSU students, staff, and faculty she continues to pursue research relating to the development of parallel algorithms, performance optimization, and parallelization of computer programs for large-scale computational science and engineering.

Research interests:

  • Parallel and distributed computing, including algorithm design, implementation, performance modeling and tuning, testing and evaluation, GPU programming with OpenMP and OpenACC.
  • Development of numerical methods and software to solve problems arising from the mathematical model of applications, especially those involving linear algebra and large sparse matrix computation.
  • Data management, data movement, data sharing, data analysis and machine learning methods in solving scientific and engineering problems.
  • Applications of high performance computing in any areas, including following the advancement of computer technology, exploring the potential of application programs on the machines with new technology, and massive scale of processors and accelerators. Managing the large scale of workflow, customize and scale up the computation from personal computer to computer cluster, and from computer cluster to cloud.

Research and technical skills:

  • Programming languages: Python, shell, Perl, Fortran, C and C++, Matlab.
  • Parallel programming with MPI and OpenMP; some GPU programming experience with CUDA.
  • Familiar with FFTW, BLAS, LAPACK, ScaLAPACK numerical libraries include the algorithms implemented.
  • Workflow automation with Bash and Perl scripting and Snakemake.
  • Scientific expertise in numerical analysis, and parallel computing.

Selected publications:

  1. Rahul Biswas, etc. Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data, PHYSICAL REVIEW D 88, 062003 (2013).
  2. Hu Yong, Xiaomeng Huang, Xiaoge Wang, etc. “A Scalable Barotropic Mode Solver for the Parallel Ocean Program“, Euro-Par 2013 Parallel Processing Lecture Notes in Computer Science Volume 8097, 2013, pp. 739-750.
  3. Z. He, G. Shen, Y. Yamazaki, X. Wang, “Performance Optimization of Multiparticle Beam Dynamics Code IMPACT-Z on Nvidia GPGPU”, Proceedings of IPAC2016, Busan, Korea, Page 3110-3113
  4. Qian Zhou, Fan Ye, Xiaoge Wang, Yuanyuan Yang, “Automatic Construction of Garage Maps for Future Vehicle Navigation Service'', in IEEE ICC 2016